Public Policy and Clean Energy Private Equity Investment ...

Public Policy and Clean Energy Private Equity Investment
DISSERTATION
of the University of St. Gallen,
Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG)
to obtain the title of
Doctor Oeconomiae
submitted by
Mary Jean Bürer
from
The Netherlands and the United States of America
Approved on the application of
Prof. Dr. Thomas Dyllick-Brenzinger
and
Prof. Dr. Rolf Wüstenhagen
Dissertation no. 3421
Zürich 2008
0

Abstract
Using empirical data collected on 60 private equity funds via surveys and
interviews with fund managers, this thesis has identified how both investors’
investment decisions and risk management practices are related to policy.
Regulatory risk management strategies identified included various forms of
active and passive risk management. An active approach was associated with
funds that were more concentrated in the clean energy sector, and active
approaches dominated among the sample.
In terms of policy preferences, the results confirm that investors believe clean
energy or climate policies (market-pull or technology-push policies) provide
more of an upside than a down-side for investors. Yet, several fund managers
said they would never invest in a portfolio company if it were 100% dependent
on a given policy. Investors say they need policy consistency and find that the
clean energy market’s greatest hindering factors are high capital expenditure,
the lack of a track record and the longer lead times for clean energy
technologies. In terms of policies, market-pull policies are preferred over
technology-push policies, except that grants for demonstration projects (a
technology-push option) are very highly regarded as well. Feed-in tariffs (a
market-pull option) are the most favored policy type to stimulate continued
finance of innovative clean energy ventures, while fund managers felt CO2
emissions trading is less effective in stimulating innovative clean energy
technology investment. This research work also investigated how a variety of
private equity fund characteristics related to funds’ policy preferences and their
regulatory risk management approaches.
1

Zusammenfassung
Aufbauend auf einer empirischen Untersuchung von 60 Private Equity Fonds
mittels Fragenbögen und Interviews mit Fondsmanagern wurde in dieser Arbeit
der Zusammenhang zwischen Energiepolitik, Investitionsentscheidungen und
Risikomanagementstrategien untersucht. Die identifizierten regulatorischen
Risikomanagementstrategien beinhalteten verschiedene Formen von passivem
und aktivem Risikomanagement. Ein aktiver Ansatz wurde insbesondere von
jenen Fonds gewählt, die sich auf den Clean Energy-Sektor fokussierten.
Insgesamt waren aktive Risikomanagement-Ansätze in der untersuchten
Stichprobe häufiger als passive.
Im Hinblick auf Politikpräferenzen zeigen die Ergebnisse, dass die befragten
Investoren in Politikinstrumenten zur Förderung von erneuerbaren Energien
und Klimaschutz (Market Pull- oder Technology Push-Instrumente) mehr
Chancen als Risiken sehen. Dennoch gaben viele Fondsmanager an, dass sie
niemals in ein Portfoliounternehmen investieren würden, wenn dieses zu 100%
von einer bestimmten Regulierung abhängig wäre. Die befragten Investoren
erachten Beständigkeit in der Energie- und Klimapolitik für nötig. Die grössten
Hindernisse für die Entwicklung des Marktes für nachhaltige Energie sehen sie
in hoher Kapitalintensität, in einem Mangel an erfolgreichen
Vorgängerprojekten und in den langen Entwicklungszeiten für neue
Energietechnologien. Hinsichtlich der Politikinstrumente werden Market Pull-
Instrumente gegenüber Technology Push-Instrumenten generell bevorzugt.
Eine Ausnahme bilden Investitionszuschüsse für Demonstrationsprojekte
(Technology Push), welche auch als sehr wirksam eingestuft werden.
Einspeisevergütungen (Market Pull) sind das beliebteste Politikinstrument, um
die weitere Finanzierung von innovativen nachhaltigen Energie-Unternehmen
voranzutreiben. Den CO2-Emissionshandel stuften die befragten
Fondsmanager hingegen als weniger wirksames Instrument zur Stimulierung
von Investitionen in innovative Energietechnologien ein. Die vorliegende
Arbeit geht auch darauf ein, welche Eigenschaften der untersuchten Private
Equity Fonds mit bestimmten Politikpräferenzen und regulatorischen
Risikomanagementansätzen korrelieren.
2

Acknowledgements
I would like to thank Professor Dr. Thomas Dyllick and Professor Dr. Rolf
Wüstenhagen for the opportunity to undertake this doctoral thesis at the
University of St. Gallen. In particular, I would like to thank Professor Dr. Rolf
Wuestenhagen for his priceless research supervision, as well as invariable
support, throughout my thesis research. I also would like to thank and
acknowledge the support of the GFF at the University of St. Gallen for
financing my research in 2006. In addition, I thank Professor Christopher Tucci
of EPFL for supporting my visiting scholar year at EPFL (2006-2007). I must
not forget to also thank the sixty+ firms that participated in this study for their
time and interest in this work. Last, but not at all least, I would like to
recognize my husband, Meinrad Bürer, for his precious support.
3

Table of Contents
Abstract 0
Zusammenfassung .................................................................................................. 2
Acknowledgements ................................................................................................. 3
1 Introduction ......................................................................................... 11
1.1 Motivation for and contribution of this work ................................... 13
1.2 Scope of the work ............................................................................. 15
1.3 Developing the research questions ................................................... 17
2 Conceptual development of this Thesis ............................................. 21
2.1 Regulatory influences on VC/PE investments ................................. 27
3 The context of the Thesis .................................................................... 31
3.1 Defining Private Equity and Venture Capital .................................. 31
3.2 Clean energy private equity investment ........................................... 33
4 Literature Review on Policy and Innovation .................................... 39
4.1 The innovation chain, the investment cycle, and policy .................. 39
4.2 International policy, CO2 emissions trading and CDM/JI ............... 44
4.3 National or state policy ..................................................................... 50
4.3.1 Renewable energy targets ...................................................................... 50
4.3.2 Policies for renewable electricity promotion ........................................ 51
4.4 Market-pull policies studied ............................................................. 56
4.4.1 Feed-in Tariffs ....................................................................................... 61
4.5 Regulatory issues studied ................................................................. 64
4.6 Technology-push policies studied .................................................... 67
4.7 General policy attributes .................................................................. 68
4.8 Assessing policies’ performance ...................................................... 69
4.8.1 Performance of support schemes ........................................................... 69
4.8.2 What does existing empirical work tell us? .......................................... 76
4.9 Concluding remarks on policies ....................................................... 82
5 Research approach and methodology ............................................... 86
5.1 Research questions ........................................................................... 86
5.2 Research approach ............................................................................ 88
5.3 Research process and methodology ................................................. 92
5.3.1 Data collection and participants ............................................................ 92
5.3.2 More details on the data collection process and approach .................. 101
5.3.3 Response rates ..................................................................................... 104
5.3.4 A few limitations of the research method ........................................... 108
6 Characteristics of funds .................................................................... 110
4

6.1 Basic characteristics of funds ......................................................... 110
6.2 Further analysis of fund characteristics .......................................... 127
7 Analysis of policy preferences .......................................................... 131
7.1 Overview of policies considered .................................................... 131
7.2 Findings about market-pull policies ............................................... 133
7.2.1 Overall findings ................................................................................... 134
7.2.2 Policy findings by fund characteristics ............................................... 138
7.2.3 Detailed analysis of views on Feed-in Tariffs ..................................... 155
7.2.4 Detailed analysis of views on CO2 Emissions Trading ...................... 170
7.3 Findings about technology-push policies ....................................... 181
7.3.1 Overall findings ................................................................................... 182
7.3.2 Specific findings .................................................................................. 186
7.4 Conclusions from a market-pull vs. technology-push policy
comparison .................................................................................................. 195
7.5 Findings about regulatory issues .................................................... 199
7.6 Findings on international policy ..................................................... 203
7.7 Findings on nuclear power ............................................................. 204
8 Findings on Regulatory Risk Management approaches ................ 206
8.1 A typology of regulatory risk approaches ...................................... 206
8.2 Illustration of RRM approaches and key differences ..................... 213
8.2.1 Active regulatory risk management .................................................... 215
8.2.2 Passive regulatory risk management ................................................... 218
8.2.3 Summary of regulatory risk management approaches observed ......... 221
8.3 RRM approaches analyzed by fund characteristics ........................ 222
8.3.1 RRM approaches by fund type and size .............................................. 222
8.3.2 RRM approach and other management aspects .................................. 224
8.3.3 RRM approach by clean energy hindering factors .............................. 225
8.3.4 RRM approach and policy preferences ............................................... 226
8.4 Conclusions on RRM approaches .................................................. 229
9 Overall Conclusion ............................................................................ 233
9.1 Conclusions for Policy-Makers ...................................................... 233
9.2 Conclusions on Regulatory Risk Management .............................. 236
10 Limitations and Further Research .................................................. 239
11 References .......................................................................................... 240
Annex 1: Survey Questions ................................................................................. 256
Annex 2: Fund characteristics defined ................................................................ 270
Annex 3: Further analysis of fund characteristics - Supplemental information
to section 6.2 ........................................................................................ 282
Annex 4: Regulatory Risk Management Strategies ............................................ 310
Curriculum Vitae ............................................................................................... 320
5

List of Figures
Figure 1: Estimated Global Clean Energy Private Equity Investment 2001-2006 12
Figure 2: Intersection of various disciplines relevant to this thesis work .............. 22
Figure 3: Attributes for Cleantech Cluster Development ...................................... 23
Figure 4: Wind power capacity additions (MWs per year) in the United States ... 25
Figure 5: Regulatory risk at different stages of the VC investment value chain ... 28
Figure 6: The investment chain and stages of investment along the chain ............ 33
Figure 7: Total clean energy investment growth in recent years ........................... 34
Figure 8: Global investment in sustainable energy by type, 2004-2006 ............... 35
Figure 9: Estimated Global Venture & Private Equity Investment by type,
2001-2006 .............................................................................................. 36
Figure 10: Global Investment in CE Estimated Annualised Total, 2006 .............. 37
Figure 11: Clean Energy Venture / Private Equity, by country, 2001 – 2005 ....... 37
Figure 12: The Cash Flow Valley of Death as a function of development stage
(Time), with typical investors shown for the various stages ................. 39
Figure 13: Investment and innovation chain, with corresponding policies ........... 40
Figure 14: European Emissions Trading Scheme (for CO2) and price
development .......................................................................................... 48
Figure 15: Renewable Electricity Policies in EU Member States as of February
2007 ....................................................................................................... 62
Figure 16: Estimation of administrative barriers in the renewable energy
deployment in the EU ............................................................................ 65
Figure 17: Effectiveness indicator for the market development of onshore wind
for selected EU-member states in 2004 ................................................. 73
Figure 18: Comparison of support for onshore wind power for selected EU
Member States in 2004 .......................................................................... 74
Figure 19: Normalized level of support for onshore wind in selected EU
Member States in 2004 .......................................................................... 75
Figure 20: Effectiveness indicator in relation to the annual expected profit for
onshore wind in 2004 ............................................................................ 75
Figure 21: Installed Capacity in Germany and the UK (1990 - 2003) .................. 78
Figure 22: Existing World Capacity for Solar PV, total and grid-connected only 79
Figure 23: Solar PV stocks soared from beginning of 2005 .................................. 80
Figure 24: Prices of solar modules and newly installed capacity (Germany) ....... 80
Figure 25: Share prices then slumped in 2006 ....................................................... 81
Figure 26: Research process for this thesis ............................................................ 89
Figure 27: Relationship between fund characteristics and investment decisions:
Step 1 of the basic research approach ................................................... 91
Figure 28: Relationship between the variables and the fund’s regulatory risk
management approach - Step 2 of the basic research approach ............ 91
Figure 29: Potential interaction between policy and regulatory risk
management – Step 3 of the basic research approach ........................... 92
Figure 30: Fund characteristics, fund particularities and clean energy views and
preferences ............................................................................................. 97
Figure 31: Number of respondents by type of respondent ................................... 104
Figure 32: Stages that funds invest in .................................................................. 111
6

Figure 33: Overall regional focus for all funds .................................................... 111
Figure 34: Regional focus of investment by location of funds ............................ 112
Figure 35: Number among all respondents choosing a particular country in
terms of best policy environment by technology ................................ 114
Figure 36: Number among U.S. only respondents choosing particular best
policy environments by technology .................................................... 115
Figure 37: Location of funds by region ............................................................... 116
Figure 39: Share of fund types ............................................................................. 119
Figure 40: Share of firm type backing the funds ................................................. 120
Figure 42: Share of core investor types in full sample ........................................ 122
Figure 43: Clean energy technology investments by type of core investors ....... 123
Figure 44: Fund sizes among the sample ............................................................. 124
Figure 45: Firm sizes among the sample ............................................................. 124
Figure 46: Number of firms by size and by stage of investment ......................... 125
Figure 47: Market-Pull Policies and scores (overall scores for all funds) ........... 134
Figure 48: Mean values and standard deviations for market-pull policies .......... 136
Figure 49: Dispersion of scores for all market-pull policies (for all funds) ........ 136
Figure 50: Frequency of each rating for all market-pull policies (all funds) ....... 137
Figure 51: Mean scores for market-pull policies, by stage of investment focus . 141
Figure 52: Mean scores for market-pull policies, by type of fund ...................... 143
Figure 53: Mean scores for market-pull policies, by fund size ........................... 144
Figure 54: Firm sizes per fund size category ....................................................... 145
Figure 55: The influence of a variety of stakeholders on fund managers’ views
about public policies ............................................................................ 146
Figure 56: Mean scores for market pull policies, by type of investor of
prevalence in each fund (LPs) ............................................................. 147
Figure 57: Market-pull policy views by type of firm .......................................... 148
Figure 58: Mean scores for market-pull policies, by firm size ............................ 149
Figure 59: Information sources for funds with minority policy views among the
sample .................................................................................................. 150
Figure 60: Mean scores for market-pull policy views, by region-focus .............. 151
Figure 61: Exposure to Policy-makers and companies for funds with
experience, compared to funds with less experience .......................... 152
Figure 62: Market-Pull Policy views by climate change as a key driver or not .. 154
Figure 63: Number of funds which found feed-in tariffs effective, or not .......... 157
Figure 64: Level of clean energy funding compared to total VC/PE funding for
funds grouped by rating of FiTs .......................................................... 161
Figure 65: Average firm size for funds which find CO2 emission trading
effective (or not) .................................................................................. 163
Figure 66: Other market-pull policy views of funds that found feed-in tariffs
effective, or not .................................................................................... 165
Figure 67: Expected time to exit (average values) among funds that found FiTs
effective and did not find FiTs effective ............................................. 167
Figure 68: Number of funds for each firm type by rating for CO2 emissions
trading .................................................................................................. 173
7

Figure 69: Number of funds for each fund type by rating for CO2 emissions
trading .................................................................................................. 174
Figure 70: Number of funds for each stages of investment focus by rating on
CO2 trading ......................................................................................... 175
Figure 71: Fund size (on average) for groups of funds with a given rating for
CO2 trading ......................................................................................... 176
Figure 72: Other views on market-pull policies for funds grouped by rating on
CO2 trading ......................................................................................... 177
Figure 73: Perceived hindering factors for funds grouped by rating on CO2
trading .................................................................................................. 178
Figure 74: Geographical location of funds grouped by rating on CO2 trading .. 179
Figure 75: International policy views for funds grouped by rating on CO2
trading .................................................................................................. 180
Figure 76: Technology-Push Policies (overall scores for all funds) .................... 182
Figure 77: Average (mean) scores for technology-push policies with
corresponding standard deviations added to the mean and dispersions
among scores for each policy .............................................................. 184
Figure 78: Dispersions of scores for technology-push policies (for all funds) .... 184
Figure 80: Mean scores for technology-push policies, by stage of investment
focus .................................................................................................... 187
Figure 81: Mean scores for technology-push policies, by fund type ................... 188
Figure 82: Views of experienced clean energy fund managers (invested pre-
2000) .................................................................................................... 189
Figure 83: Mean scores for technology-push policies, by fund size ................... 190
Figure 84: Technology-push policy views by type of firm ................................. 191
Figure 85: Mean scores for technology-push policies, by firm size .................... 192
Figure 86: Mean scores for Technology-push policies, by core investor type
(LPs) of prevalence in each fund ......................................................... 193
Figure 87: Technology-Push policy views by country of management .............. 194
Figure 88 : Mean scores for technology-push policies, by region-focus ............. 195
Figure 89: Average scores of average overall market-pull and technology-push
policies ................................................................................................. 196
Figure 90: Number of funds answering “N/A” for each regulatory issue ........... 200
Figure 91: Levels of satisfaction with regard to regulatory issues ...................... 200
Figure 92: Mean scores for regulatory issues by stage of investment ................. 201
Figure 93: Mean scores for satisfaction levels with regulatory issues, by
country of management ....................................................................... 202
Figure 94: Mean scores on satisfaction levels for handling of regulatory issues,
by regional focus ................................................................................. 202
Figure 95: Choice preferences for all funds with regard to international climate
policy options ...................................................................................... 203
Figure 96: Number of funds responding for preferred international policy
option by the driver they mentioned as being most important among
the four................................................................................................. 204
Figure 97: Number of respondents that viewed nuclear energy as competing .... 205
8

Figure 98: Number of funds that investigated policy and invested in clean
energy .................................................................................................. 208
Figure 99: Typology of Venture Investors' Regulatory Risk Management
Strategies ............................................................................................. 209
Figure 100: Frequency of direct interactions between VCs and policy makers
vs. portfolio companies ....................................................................... 217
Figure 101: Regulatory risk management approaches by Fund Type ................. 223
Figure 102: Regulatory risk management approaches by average fund size ....... 224
Figure 103: Proportion of clean energy funding for active (left) and passive
(right) RRM categories of funds ......................................................... 224
Figure 104: Regulatory risk management approaches by Team Background ..... 225
Figure 105: Regulatory risk management approaches by Clean Energy
Hindering Factors ................................................................................ 226
Figure 106: Market-Pull policy preferences by regulatory risk management
approaches ........................................................................................... 227
Figure 107: Number of funds that rated CO2 emissions trading 1-5 for
regulatory risk management approaches ............................................. 228
Figure 108: Technology-Push policy preferences by regulatory risk
management approaches ...................................................................... 229
Figure A3 -1: Qualification of management team ............................................... 283
Figure A3 -2: Backgrounds of importance to different types of funds ................ 283
Figure A3 -3: Number of funds developed pre-2000 and post-2000 ................... 285
Figure A3-4: Country location for the most experienced clean energy funds ..... 285
Figure A3 -5: Number of funds corresponding to the approximate amount of
times the fund was a lead investor on a given funding round ............. 286
Figure A3 -6: Frequency of meetings between Partners and staff with Policymakers
or portfolio companies ............................................................ 288
Figure A3 -9 : Important information sources for all funds ................................ 289
Figure A3 -10 : Information sources by stage of investment .............................. 290
Figure A3 -11: Typical time to exit for funds ...................................................... 290
Figure A3 -12: Typical time to exit by region-focus (Europe vs. North
America) .............................................................................................. 291
Figure A3 -13: Frequency of times each driver type was mentioned as 1st, 2nd,
3rd, and 4th .......................................................................................... 292
Figure A3 -14 : Drivers for clean energy investment by clean energy funding
size ....................................................................................................... 294
Figure A3 -16 : Perceived hindering factors (overall scores) .............................. 295
Figure A3 -17: Hindering factors by region focus ............................................... 296
Figure A3 -18 : Perceived hindering factors by fund type .................................. 297
Figure A3 -19: Hindering factors by country of fund management .................... 299
Figure A3 -20 : Perceived hindering factors by fund size ................................... 300
Figure A3 -21 : Perceived hindering factors by type of firm ............................... 301
Figure A3 -23 : Perceived hindering factors by type of core investor type ......... 304
9

List of Tables
Table 1: Non-EU countries with renewable energy targets (REN21, 2005) ......... 51
Table 2: Renewable Energy Promotion Policies (REN21, 2005) .......................... 53
Table 3: Cumulative Number of Countries/States/Provinces Enacting RPS
Policies .................................................................................................. 55
Table 4: Participating investors in the study .......................................................... 94
Table 5: Topics covered in the questionnaire by order of coverage ...................... 97
Table 6: Summary of basic characteristics of the funds reviewed ...................... 100
Table 7: Response rates for key questions ........................................................... 105
Table 8: Summary of basic characteristics of the funds reviewed ...................... 127
Table 9: Hindering factors by type of fund .......................................................... 129
Table 10: Hindering factors by type of firm ........................................................ 130
Table 11: Order of importance of investment criteria by type of fund ................ 130
Table 12: Basic fund characteristics that correspond to views on feed-in tariffs 161
Table 13: Top 5 investment criteria for each fund that does not like FiTs .......... 168
Table 14: Basic statistics on fund characteristics by type of regulatory risk
management (RRM) approach ............................................................ 213
Table A3 - 1 : First investment criterion for funds located in the United States . 304
Table A3 - 2 : First investment criterion for funds located in the UK ................. 305
Table A3 - 3 : First investment criterion for funds located in other European
countries .............................................................................................. 306
Table A4 - 1: Active regulatory risk management strategies among sample ...... 310
Table A4 - 2: Passive regulatory risk management strategies among sample ..... 318
10

1 Introduction
The energy industry is a typical example of a heavily regulated industry, and
particularly large incumbent energy firms have developed significant expertise
in non-market strategies (or corporate political activity). New entrants to the
energy industry, such as clean energy technology ventures, are also exposed to
regulatory risk (and opportunity), but they do not have the means to engage in
non-market strategies to a similar extent as large incumbent firms. On the other
hand, the success of investments in these firms significantly depends on
managing regulatory risk. However, little is known empirically about how
venture investors perceive energy policy risk (and opportunity) and what they
do to manage it. Based on a survey among 60 venture capital and private equity
firms in primarily Europe and North America, this work attempts to close this
gap in the current literature. In addition, t!"#$ %!&#"#$ "'%&'(#$ %)$ (&*)'#%+,%&$
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Figure 1: Estimated Global Clean Energy Private Equity Investment 2001-2006
Source: SEFI/ NEF 2007.
In previous research (Wüstenhagen and Teppo 2006), a number of sector-
specific risks have been identified as a potential barrier to increasing levels of
clean energy venture capital investments, one of which is regulatory risk (or the
risk that a given policy changes). Given the important role of regulatory drivers
for sustainability in the energy sector, it is particularly important for
government to understand investors’ perception of the risks (and opportunities)
associated with energy and climate policies. Otherwise, government initiatives
that are meant to be supportive of the cleantech VC market might actually end
up crowding out private capital rather than improving conditions for VC
financing in this important sector. This work intends to inform Policy-makers
about investors’ policy preferences, but also inform investors about the variety
of management strategies actively or passively chosen by other firms in the
investment community to deal with regulatory risks (such as the risk that a
given supportive policy is withdrawn).
12

1.1 Motivation for and contribution of this work
The last 3-4 years have shown that sustainability-related ventures are attracting
increasing amounts of private equity capital, with a particular focus on clean
energy technology ventures. Total private equity investment has grown from
3.3 Billion US$ in 2003 to 11.3 Billion US$ in 2006, where the majority of this
growth is private equity investment for companies (NEF, 2006). This activity
has helped defy a number of myths about clean energy technology including:
Myth #1: “There’s no room for innovative technology and entrepreneurship in
the energy and power industries;” Myth #2: “You can’t make an acceptable
return investing in new energy technologies;” and Myth #3: “Where’s the Cisco
of energy tech? There aren’t any energy tech companies with that kind of
success” (LoGerfo, J.P., 2005).
Why is investment in clean energy important to society and why should Policy-
makers be concerned with further stimulating investment in this sector? A
wider use of renewable energy technology, or clean energy technology, is seen
as one way to meet challenges such as climate change, energy security,
resource depletion, pollution, or competitive advantage and satisfy changes in
demand patterns (for example, see Jacobsson and Lauber, 2006). Governments
around the world have realized the upcoming sustainability challenges and
started to design policy mechanisms intended to support market introduction of
sustainable energy technologies. A recent report by the European Commission
explains “even though traditional fossil fuels and nuclear energy will continue
to play an important role, Europe has a special part to play in promoting
renewable energy. They are an attractive option to diversify the EU’s energy
supply: renewable sources are available locally, they bring environment
benefits and they contribute to employment and the competitiveness of the
European industry. Support for renewable energy is needed as long as
technologies are still developing and market prices for non-renewable energy
do not reflect their full costs to society due to subsidies and external costs”
(European Commission, 2005). In terms of climate change, while about 70
percent of the possible (CO2) abatements at a cost below or equal to 40 euros a
ton would not depend on any major technological developments, the remaining
30 percent of abatements depend on new technologies or significantly lower
13

costs for existing ones, such as biofuels, wind power, and solar panels (Enkvist,
et al., 2007). While low-tech carbon emissions abatement is relatively more
important in a 2030 perspective, higher-tech carbon emissions abatement is
relatively more important for the period post-2030.
Relatively little work has looked at how clean energy, climate and innovation
policies affect private equity investment in the clean energy sector, and
therefore clean energy innovation and final deployment of such technologies.
However, some work does exist on stimulation of VC/PE investment via
policy, more generally, in innovative technology sectors. In order to stimulate
VC/PE investment in innovative technology, the European Commission
recommends applying public policy where it will have the most impact, at the
earliest stages of investment 1 , as this is the point at which the private market is
most constrained. In the 1990s there was a spurring of public programs around
the globe to encourage the formation of venture capital funds. These programs
shared a common rationale: that venture capital spurred innovation in the
United States, and could do so elsewhere (e.g. see the European Commission’s
Green Paper on Innovation 1995). Gompers and Lerner (2004a) conducted
extensive analysis of data to examine the impact of venture capital on
technological innovation 2 .
Meanwhile, economic analysis tends to assume perfect capital markets, so that
if an injection of capital is required to undertake an investment, then it is
available. However, in practice this is often not the case 3 . These market failures
can also affect the supply of energy efficient goods and services. Therefore,
1 See the European Commission’s “Raising EU R&D Intensity – Improving the Effectiveness of Public
Support Mechanisms for Private Sector Research and Development” (2003). The EC report mentions
that public support should meanwhile be non-distorting, time-limited, non-bureaucratic and subject to
robust, external and independent evaluation.
2 Gompers and Lerner formally argued (1998) that the surge in patenting in the United States over the
past two decades could be explained by changes in the management of innovation activities. In their
2004 book they argue that the growth of venture capital is one such management change. For a review
of various subjects relevant to the venture capital space, including the role of government, see Gompers
and Lerner (2004).
3 For example, in terms of improvements in energy efficiency it is the less well off that are most capital
constrained and therefore may be unable to make the most efficient cost-effective investments and are
driven towards goods and services with the lowest up front costs. Furthermore, many investments and
particularly the development and marketing of improved goods and services may be subject to
relatively long time lags between the upfront costs and long-term benefits. If there is uncertainty about
the realisation of benefits, then decision makers will hesitate to make any irreversible commitments
(Defra, HM Treasury, 2003).
14

using economic instruments to correct market failures could lead to a
behavioural change towards cleaner production on both the demand and supply
side. This is the case for market-pull instruments like economic instruments to
stimulate investment in clean energy technologies by private equity investors.
Demand-pull arguments have been advanced indicating that more market-
oriented regulation should also be introduced in early innovation stages
(Christensen 1992). Both feed in tariffs for renewable electricity and certificate
markets can be seen as demand pull instruments interfacing between R&D and
the regular energy market (in this thesis these policies are categorized under
Market-Pull Policies). While traditional energy subsidies can encourage
inefficient and excessive use of subsidized inputs, clean energy subsidies like
feed-in tariffs are used to make up for market, institutional and policy failures
which favor unfavorable production and consumption.
At the same time, technology-push policies, or innovation policies, extend well
beyond basic government funding for Research and Development (R&D). A
number of other technology-push policies which progressively support
technologies as they progress along the innovation chain are also studied in this
thesis, as we attempt to understand how a wide variety of public policies
impact private equity investment decisions with regard to clean energy
technologies.
1.2 Scope of the work
Without choosing one side (market-pull or technology-push) to focus on, this
study aims to look at and compare via empirical data in the industry all the
policies which might stimulate venture capital and private equity 4 investment in
this sector and that means policies relevant to very early stage technologies, as
well as those relevant to fully developed and commercially available
technologies.
At the same time, a particular focus among this set of choices is on policies
most relevant to stimulating investment in “less mature” clean energy
4 Private equity is defined in this thesis as later-stage private company finance, such as management
buy-outs. This type of finance is naturally more relevant than VC finance to companies offering very
mature technologies.
15

technologies. Less mature clean energy technologies are defined in this thesis
as technologies which are often more costly, and often more beneficial for their
sustainable development attributes, but still commercially available, such as
photovoltaic solar energy.
This study utilizes an empirical data methodology which is focused on
investors’ perceptions of the market. The conclusions provide insight for
Policy-makers about the policies these findings imply would increase private
equity investment in the clean energy technology sector. These findings are
intended to provide a general indication of the investment impact of the various
policies studied and to be interpreted and used given particular country
circumstances, as participating investors were active in a number of countries
in Europe and the United States.
This study also investigates how investors deal with regulatory risks in the
clean energy sector – in particular the risk that supportive mechanisms are
withdrawn, affecting their ventures’ market opportunities and the financial risk
of the deals they invest in. It also aims to contribute to private equity investors’
decision-making in the field of clean energy technologies. Knowing what other
investors think about regulatory drivers in this sector and how other investors
along the investment chain manage regulatory uncertainties, may help them to
optimize their investment approaches with regard to this sector.
Recent press has pointed out the potential for a bubble in the growing cleantech
market. Company valuations in particular segments are at all time highs.
Investors should stay prudent as the venture capital industry is indeed cyclical.
Many investors which entered the market early are likely to do very well,
especially at this point in time (New Energy Finance, 2007). However, there
will also be losers. Knowing how to manage the regulatory risks relevant to this
sector will be one important new way that savvy private equity investors
already present in this space, or now entering the space, can reduce their risks
and perhaps increase their returns from this emerging private equity investment
category.
16

1.3 Developing the research questions
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"'')-,%"-&$ /0&,'$ &'&+54$ %&/!')0)5"&#$ -"&1$ *,+>&%@.300$ .)0"/"&#$ *)+&$
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$
There are more than two policy options to choose from in the real world. In
order to select the policies that would be studied, the complete innovation chain
for a new clean energy technology was considered. The basic logic for
examining technology push and market pull policies in the same study and the
wide options among these two categories, from soft to more regulatory options
therein, is that policies should not only be pertinent to one side of the
innovation chain, but policies should ideally fill all potential gaps in the
innovation chain from invention to market deployment. Indeed some countries
have more difficulty than others with certain stages of the innovation chain.
Investors also sometimes prefer to concentrate on early-stage or later-stage
technologies and investments. This is why the findings of this study must be
interpreted differently by Policy-makers and investors depending on the
conditions of the country or firm in question.
$
Also, to answer our basic research questions about the investment impact of
policies, it is important to recognize that investors in clean energy technology
ventures are not homogeneous among general groups of investors (e.g. venture
capitalists and private equity investors). Among these groups there are
experienced and less experienced investors. There are independent firms,
17

corporate-backed firms (corporate venture capital), subsidiaries of private
equity firms, banks, etc. They are invested in by a number of different types of
core investors. They function differently (e.g. they either tend to lead clean
energy investments or follow), they manage ventures differently (e.g. they are
hands-on, or not), they fund at different levels the clean energy sector, they
have different expectations (e.g. time to exit) and perspectives about drivers
and hindering factors relevant to clean energy, they have different investment
criteria and different existing portfolios. Their views on policies, and the way
they manage regulatory risks, relevant to this sector is probably dependent on a
number of factors. One can assume that they will not have a uniform view
about policies. However, we might be able to find similar views among funds
with similar fund characteristics. Therefore, this thesis not only examines what
the overall sample of private equity investors think about policies (on average),
but it also looks at how their views differ by a number of various relevant
characteristics. The same is true for how they manage regulatory risks relevant
to the sector.
The full set of public policies considered to impact clean energy private equity
and venture capital investments, and which were considered in the empirical
data collection of this thesis, include:
1) ‘Technology-Push policies’ (e.g. R&D spending or government grants for
demonstration projects) to support clean energy technology development and
the early commercialization stages of such technologies and
2) ‘Market-Pull policies’ (e.g. feed-in tariffs) to support clean energy
deployment.
Regulations to facilitate green electricity deployment and international climate
policy can also be considered as market-pull policies, but energy sector
regulations are more of a pre-requisite to ensure the market functions properly,
as opposed to a policy option – this is the case of the electricity sector.
In addition, within the class “market-pull policies” there are two major types:
a) ‘strategic deployment policies’ (e.g. feed-in tariffs) and
b) ‘barrier removal policies’ (e.g. CO2 emission trading).
18

This thesis then focuses on a comparison of investor perceptions with regard to
these two examples of strategic deployment and barrier removal policies - feed-
in tariffs and CO2 emissions trading - because these are market-pull policies
which have been covered more recently in the literature and which are often
favored by quite different camps of experts due to their very different nature.
This thesis is limited to understanding policies which impact the most
innovative clean energy technologies’ paths along the innovation chain before
they become fully commercial and competitive in the existing energy market,
which is in fact largely a subsidized energy market favoring fossil fuel and
nuclear energy technologies. In the survey used for data collection in this thesis,
the majority of questions ask about the fund managers’ perspectives with
regard to the level in which each policy option stimulates his or her
firms’/funds’ interest to invest in innovative clean energy technologies. The
results in this thesis do not address policies or regulatory uncertainty relevant to
investors in public equities (listed stocks) which would be more relevant for
fully commercial clean energy technologies. Nor does it explore regulatory
uncertainties relevant to project financiers or private equity for project finance.
Therefore, to understand fully how a wider variety of policies impact very
competitive clean energy technologies like wind energy, a wider variety of
investors from private equity to public equity to project financiers, would need
to be conducted next.
In this thesis, investors refers to private equity fund managers (both venture
capitalists and later-stage private equity fund managers), or General Partners
according to the venture capital industry vocabulary. Such fund managers, not
individual investors in private equity, were the focus of the study and make up
almost 100% of the sample used to study this category of investors. It should
also be noted that in this thesis, the term core investors is used to refer to the
institutional and other investors which invest in private equity funds, or Limited
Partners according to the venture capital industry vocabulary.
19

Thesis Research Questions:
1. Do private equity investors view certain policies as clearly contributing
to their interest to invest in the sector?
2. How do private equity investors rate the attractiveness of market-pull
policies and technology-push policies?
3. Which policies do certain types of investors appear to prefer most, and
what may be some rational explanations for their differences in opinion?
4. What are the basic characteristics of clean energy VC/PE fund managers,
and how do they relate to their policy preferences and regulatory risk
management approaches?
5. How does perceived regulatory risk influence the decision-making of
private equity investors with regard to clean energy ventures and how do
private equity fund managers currently manage regulatory risks relevant
to their clean energy technology deals?
This work also serves as a sort of test for the hypothesis that feed-in tariffs are
the best policy option (in general) - at least from the perspective of this part of
the investment community. At the same time it provides input to the debate
about the relative importance of market-pull and technology-push instruments
to support the innovation process, with a particular focus on innovative clean
energy technologies.
The research is based on surveys and interviews with ‘fund managers 5 ’ among
sixty private equity funds (of which over 80% already invested VC or private
equity in clean energy technology ventures). Given the reality of data
availability and the short history of this emerging investment space, this type of
empirical research is a practical way to study the effectiveness of various
policy options intended to stimulate private sector investment in clean energy
innovations. Chapter 5 provides further details on the research approach for this
thesis. Before moving into the details, the next chapter continues to explain
how the literature on investment, innovation and policy led to the conceptual
development of this thesis.
5 A Partner, Director, or similar, of otherwise an Investment Manager or Analyst (one person per fund).
20

2 Conceptual development of this Thesis
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1,#$ *)+&$ +&0,%&($ %)$ %!&$ .,#%$ "*.0&*&'%,%")'$ )=$ 8,(04$ (&#"5'&($ .)0"/"&#;$
I&00$ (&#"5'&($ 5)-&+'*&'%$ "'%&+-&'%")'$ ,-)"(#$ %!"#$ .)%&'%",0$ /)'=0"/%;$
J%3("&#$9)=$%!"#$%4.&:$%)$3'(&+#%,'($1!,%$%!&$.+"-,%&$#&/%)+$&7.&/%#$=+)*$
.)0"/4$9,'($1!,%$"%$()&#$')%$+&#.)'($1&00$%):$,+&$"*.)+%,'%$%)$&'#3+&$%!,%$
.)0"/4@*,>"'5$/)'%"'3&#$%)$8&$1&00@(&#"5'&(;$K3%$%!&+&$"#$#%"00$#)*&$(&8,%&6$
&-&'$,*)'5$-&'%3+&$/,."%,0"#%#$,'($.+"-,%&$&23"%4$"'-&#%)+#$,8)3%$.)0"/4@
*,>"'5;$ Venture capitalists also face skepticism from within their own ranks.
Some are reluctant to sign on to the idea of any government assistance, saying
this undermines the long-term health of the technology. “In the past, venture
capitalists would say, ‘Let the market decide.’ But the reality is that sometimes
the market needs a boost,” said Mark Heesen, president of the National Venture
Capital Association, an industry trade group (Richtel, 2007). In order to
understand the links between investment, innovation and policy, and design
this study, a literature review was undertaken which delved into the intersection
between the literature on private equity finance, climate policy, innovation
policy and energy policy (figure 2).
While many policy analysts in this field have studied the effectiveness of
policies contributing to the mitigation of climate change and to the overall goal
of sustainable energy use, few studies have looked at policy effectiveness from
the perspective of investors (e.g. Mitchell, 2006; Dinica, 2006; Wiser and
Langniss, 2001), and fewer still focus on the perspective of venture capitalists
and (later-stage) private equity investors (Wuestenhagen and Bilharz, 2004;
Burtis, et al., 2006; DiMaggio, 2007).
21

Figure 2: Intersection of various disciplines relevant to this thesis work
Regulatory risk is not completely new to such investors, assuming they have
faced regulatory risks in other sectors like the biotechnology sector. However,
investments in the clean energy sector are particularly affected by market
uncertainties such as changing energy prices, market failure, energy sector
regulations and new incentives for clean energy sources.
There are many government incentives and other types of market adoption or
barrier removal policies relevant to the clean energy sector which are
attempting to create a more level playing field in the energy sector for cleaner
technologies; and there is now a greater diversity of innovation policies which
stimulate the movement along the innovation chain of promising new
technological innovations from the R&D stage to market deployment.
A review of other research in the field follows. From previous research, it
appears that investors in the clean energy sector make decisions about
geographical preferences for investments based on favorable policy
environments. Burtis, et al. (2006) shows in Figure 3 the main attributes
22

venture capitalists look for when choosing where to focus their cleantech
investments (geographical location). The responses are ranked by the number
of mentions in the survey (each respondent could name up to three reasons).
Public policy was the second most mentioned attribute pointed at by the
venture capitalists participating in this study. Therefore, the Burtis, et al. study
showed that, in general, ‘good’ policy environments are important to cleantech
cluster development.
Figure 3: Attributes for Cleantech Cluster Development (Number of Mentions)
Note: N= 25; Source: NRDC and Burtis, et al., 2006.
Next, one would inquire about which policy environments are most favored by
investors. Venture capitalists are the most relevant investment industry players
with regard to innovative technology commercialization. A recent study
showed that the decision to invest in clean energy in a given location could
correlate with the enactment of particular policies in a given state. DiMaggio
(2007) shows the predicated probability results of venture capital investment in
a preliminary study that indicate the relative effectiveness of two specific
policies (e.g. general Renewable Portfolio Standard (RPS) enactments in
various states and the public benefit fund (PBF) in various states within the
United States) in stimulating venture capital investment. RPS enactment was
shown to be more important than public benefit fund enactment on investment.
23

Burtis, et al. (2006) also points out in another study that the radical swings in
production caused by the intermittent production tax credit (PTC) have caused
problems for people up and down the wind energy supply chain, from
manufacturers to financiers to customers, and have limited the growth of the
U.S. wind industry. He shows that in 1999, 575 MW/year were added to
America’s wind power capacity, and when the PTC expired in June 99 and was
extended only in December 99, only 43 MW of new capacity was added in
2000 (Figure 4). The same thing happened in 2001 and 2003 where new
capacity in 2001 was 1696MW and down to 410MW in 2002; up 1687MW in
2003 and down to 389MW in 2004. New capacity continually peaked right
before the PTC was expired and dropped right after it was expired. In 2005,
new capacity was 2431MW and when in August 2005 the PTC was extended
until December 2007 (the first time it was extended before it expired). Burtis, et
al. (2006) explains that players in the wind energy industry are now finally
planning for a period of sustained growth. Indeed, investors need an indication
that the market conditions of a given country are stable in order for them to
invest in the expansion of industries, in this case wind turbine manufacturing
companies in the United States. Even gradual growth, seems to be more
favorable than highly fluctuating market conditions created by policies which
must go through constant extension by Policy-makers over time. So far,
deployment of wind energy is indeed supported by the production tax credits,
but there are not many large American wind turbine manufacturers compared to
other countries, which happen to receive the support of more consistent policy
environments, which investors appear to prefer 6 .
6 Today, major wind turbine manufacturers producing >100kW machines include: Acciona
(Spain), Clipper Corp. (US), Dewind, Ecotecnia, Enercon, EU EnergyWind Ltd (UK),
Fuhrländer GmbH, Gamesa Eólica (SP), GE Energy (US), Goldwind (China), Mitsubishi
Heavy Industries (JP) Nordex, REpower Systems AG, Siemens Wind (DK) former Bonus,
Suzlon, Vestas Wind Systems, Windtec, and WinWind OY (Finland). Most are based in
European countries.
24

3000
2500
2000
1500
1000
500
0
575
43
1696
410
1687
389
2431
1999 2000 2001 2002 2003 2004 2005
6/99!PTC
Expires!"
Extended!
12/99
12/01!PTC
Expires!"
Extended!
2/02
12/03!PTC
Expires!"
Extended!
10/04
8/05!PTC!
Extended!
to!
12/07
Figure 4: Wind power capacity additions (MWs per year) in the United States
Source: Union of Concerned Scientists; American Wind Energy Association;
and replicated from Burtis, et. al. (2006)
The above two studies are important contributions to this area of study.
However, other types of clean energy and climate policies must still be
investigated and research which uses other types of empirical analyses (e.g.
qualitative analyses in addition to quantitative analyses) are still needed to
complete the knowledge gap in this stream of literature. Do investors think that
such policies are more of a risk than an opportunity? Do investors have a
preference with regard to given types of policies? What do investors do to
manage such regulatory risks and how does policy affect their investment
decision-making process?
For sure, investors, entrepreneurs, and consumers look to Policy-makers to
reduce market risks, not increase them. A few basic attributes of policy are
more or less well understood, but further work is needed to expand beyond
such generalized conclusions. For example, public policy was mentioned as the
second most important attribute for cleantech cluster development in the United
States after entrepreneurial culture/talent, and Burtis, et al. (2006) pointed out
the need for consistency in policy-making was crucial, as a result of his
25

empirical investigation with investors (via interviews). This current research
also points out the key issue of consistency in policy making 7 .
Obviously, as investors have different investment preferences and different
ways of investing in clean energy technologies, not all investors are bound to
feel and act the same way with regard to different types of policies, and their
perceptions about the basic attributes of these policies (consistency/stability,
efficiency, effectiveness, comprehensiveness, etc.). Generally it makes sense
that all investors will prefer policies that are most adapted to lowering their
risks particular to a given technology or stage of technology, but also via a
consistent implementation with the least amount of change over time. Yet some
types of investors may have something to gain from a quickly changing policy
or a policy which creates a market with a certain level of uncertainty which
they may have an advantage in managing.
On the other hand, investors might have different perceptions about different
policies because of their experience or knowledge of the past implementation
cycle of a given policy and this varies by country. Burtis, et al. (2006) points
out in his study that How Policy-makers implement policy, may indeed be as
important, or even more important than what Policy-makers do. Two policy
cases most relevant to this particular point are: the production tax credit (PTC)
in the United States and the CO2 emissions trading scheme in Europe. The case
of the PTC is shown above.
Meanwhile, as for the CO2 emissions trading scheme in Europe, in theory
emissions trading is a cost-effective climate policy and it has been supported by
many for its ability to meet emission targets at the lowest global cost to society.
However, Bertoldi, et al. (2005) point out the conceptual basis on why CO2
emissions trading cannot deliver clean energy innovation on its own. Also,
Egenhofer, et al. (2006) reviewed the EU ETS in depth and concluded that on
its own it will most likely not provide sufficient incentives for the development
of new breakthrough technologies. At the start of the scheme, European
countries over-allocated emissions to their industries to obtain political
acceptance of the new policy. The implementation of the scheme in its first
7 Even one investor interviewed which rated the PTC high had mentioned that the major failing of the
PTC was its on again, off again aspect. See results section for quotes from the interviews on this issue.
26

phase of implementation led to a crash in the CO2 emissions price 8 . This also
points out that how Policy-makers implement policy is more important than
what the policy is in theory.
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1!)$ ,+&$ .+&#&'%$ "'$ %!&$ .).30,+$ .+&##$ %)(,4$ ,..&,+$ %)$ +&/)5'"L&$ %!&$
"*.)+%,'/&$ )=$ #!)+%@%&+*$ #3..)+%$ *&/!,'"#*#$ 9&;5;6$ =&&(@"'$ %,+"==#$ =)+$
+&'&1,80&#:$%)$!&0.$8+"'5$()1'$%!&$/)#%#$)=$.+)*"#"'5$'&1$%&/!')0)5"&#$
,'($#%"*30,%&$"'-&#%*&'%$,'($834@"'$"'$%!&$+&'&1,80&$&'&+54$*,+>&%;$$
So far, the energy policy literature has pointed to the effectiveness of feed-in
tariffs as applied in Germany today. For example, Lauber (2004) and
Menanteau, et al. (2003) concludes that feed-in systems have been more
effective than other policies in terms of achieving targeted capacity 9 . This
policy approach is also deemed to be able to provide greater long-term benefits
to a given environmental target.
2.1 Regulatory influences on VC/PE investments
Regulatory influences can be identified on various stages of the venture capital
investment value chain 10 (see Figure 5).
8 Wikipedia: Many businesses have welcomed emissions trading as the best way to mitigate (prevent)
climate change. Enforcement of the caps is a problem, but unlike traditional regulation, emissions
trading markets can be easier to enforce because the government overseeing the market does not need
to regulate specific practices of each pollution source. However, monitoring (or estimating) and
verifying of actual emissions is still required, which can be costly. Critics doubt whether these trading
schemes can work as there may be too many credits given by the government, such as in the first phase
of the European Union's scheme. Once a large surplus was discovered the price for credits bottomed
out and effectively collapsed, with no noticeable reduction of emissions (Newsweek: The Carbon Folly
- Emissions trading isn't working)
9 Lauber (2004) calculates that Denmark, Germany and Spain account for 84% of installed wind
capacity in the EU. Each of these countries has implemented a Feed in Tariff.
10 In this literature review, the term Venture Capital is mostly used because literature in this field has
mostly focused on just the venture capital part of the private equity industry. It should be noted,
however, that thesis will also consider later-stage Private Equity. The difference between these two
forms of private equity will be explained further in a section three of this literature review.
27

Examples
VC
Investors
Tax
incentives for
pension
funds
Typical focus of
previous VC research
VC
Funds
Government
VC coinvestments
Entrepreneurial
Firms
Regulatory Influences
Investment
subsidies
Corporate
Customers
(B2B)
Renewable
Portfolio
Standards
Final
Customers
(B2C)
feed-in tariffs
Figure 5: Regulatory risk at different stages of the VC investment value chain
In Figure 5, the first three example policies are considered technology-push
policies in this thesis, and the last two are considered market-pull policies, as
will be explained further. Traditionally, research on the linkage between
government policy and the VC market has had a relatively narrow perspective
on one particular stage of the value chain, namely how government can support
VC funds (Baygan and Freudenberg, 2000, OECD 2004, Rigau 2002, Jeng and
Wells 2000, Dubocage and Rivaud-Danset 2002), a technology-push approach.
The focus typically is on tax incentives and other forms of direct investment
support. A 2004 OECD report surveyed five policy areas which are conducive
to increasing the supply of venture capital: investment regulations, taxation,
public equity programs, business angel networks, and second-tier stock markets.
To get a more comprehensive understanding of the links between regulation
and the level of VC investing in a certain sector or country, it is important to
also look up and down the value chain. As several authors have noted, the
emergence of a healthy venture capital market requires a whole "ecosystem" of
innovation, which includes sufficient levels of entrepreneurial activity, as well
as sufficient capital allocation from investors. Black and Gilson (1998), in their
attempt to explain differences in the development of VC markets between the
U.S. and other countries, concur that experienced VCs as well as investment
28

ankers experienced in taking early-stage companies public are critical
institutions that will not develop quickly. They conclude that a “strong venture
capital market thus reflects an equilibrium of a number of interdependent
factors.” Kuemmerle (2001), in his comparison of the evolution of VC
industries in the U.S., Germany and Japan, points out “an active venture capital
industry is arguably (…) difficult to create (…) because it typically requires not
just a functioning financial system, but a fertile technology system and a
climate conducive to entrepreneurship.” Regulatory policies to support the VC
market should therefore also be targeted to investors (e.g. pension funds) and
entrepreneurial firms. An often-quoted best practice example is “The Small
Business Innovation Research” (SBIR) program that was designed to assist
small technology-based firms to commercialize their products beyond early-
stage research and development (R&D) (U.S. EPA 1994, Lerner 1999).
Yet even looking at investors, VCs and entrepreneurs will not yet lead to a
complete picture of regulatory influences on the venture capital market. The
success of VC investments ultimately depends on customers' decisions to prefer
the entrepreneurial firm's products to existing products. With sustainability
innovation being characterized by a strong societal (rather than private) value
as described above, regulation is a strong factor influencing demand. Several
policies have been developed that influence demand for sustainable energy,
such as the UK renewables obligation, where electric utilities are mandated to
buy a certain share of their power from renewable energy, or the German
Electricity Feed-in Law (StrEG), which was introduced in 1991 (Wüstenhagen
and Bilharz 2006). This legislation guaranteed all renewable energy producers
a preferred rate for selling the electricity that they generated over 20 years
(CEC, 2004). These demand-driven policies have arguably indirectly
contributed more to successful VC investments in the German renewable
energy sector than many of the measures discussed above that aimed at directly
supporting venture capital funds, and yet they constitute a surprising gap in the
literature on regulatory influences on VC.
The view that these policies are indeed important for understanding VC
investments in the sustainability sector is underlined by LoGerfo et al. (2005),
who finds that a number of macro trends will support cleantech as a viable
venture investment category for some years to come; one of these being: Local
and national policy initiatives such as renewable energy portfolio standards for
29

utilities, subsidies for wind and solar power systems, and “green building” and
environmental procurement requirements for government agencies that create
demand for cleantech solutions and kick start the virtuous cycle of “volume
increase cost reduction.” However, as mentioned before, not much literature
exists, about the impact of energy and climate policy on the VC industry. A
few examples were already discussed in the introduction. Another one of the
few exceptions is an exploratory study by Kasemir et al (2000) using a policy
exercise methodology to survey European VCs' views on climate policies.
Among other things, they concluded that European VCs would welcome
stricter climate policies on the EU level, even if they were to be introduced
unilaterally, as a means to foster innovation in the energy sector and hence
support entrepreneurial activity in this sector. Therefore, recalling the studies
reviewed in the introduction, previous research has pointed out that 1) policy is
indeed important in determining where investors invest (at least in the United
States), 2) certain policies are superior to others in terms of stimulating clean
energy innovation (e.g. in the U.S., RPS appears to be favoured over the public
benefit charge), 3) investors need consistency and long-term policies (e.g. the
Production Tax Credit’s on again, off again aspect does not create the market
stability that investors seek), and 4) European VCs welcome stricter climate
policies on the EU level.
Concluding the review of previous research about regulatory influences on VC
investments, while many forms of possible government support for venture
capital are being discussed, most of them focus on a relatively narrow stage of
the VC value chain. Particularly the one form of government support that is
most prevalent in the sustainable energy sector, namely incentives for the
ventures' final markets, is surprisingly absent in current research. While there
are some first attempts at studying this latter-half of the investment value chain
where market-pull instruments are most relevant, further work is needed to
study what policies among a large array of options investors would prefer or
which would encourage them to invest in the clean energy sector, why they
have these preferences, how their views on market-pull instruments differ from
their views on technology-push instruments, as well as how policy affects their
investment decisions and their regulatory risk management approaches relevant
to the sector. This last subject is also an area that has been left mostly
unexplored so far in academic research.
30

3 The context of the Thesis
3.1 Defining Private Equity and Venture Capital
!
Venture!Capital$ 9ME:$ +&#&,+/!$ .+)-"(&#$ "'#"5!%#$ "'%)$ %!&$ -&'%3+&$ /,."%,0$
/4/0&$ 9N)*.&+#$ ,'($ O&+'&+$ CPPP:;$ ME$ "#$ .+)-"(&($ %)$ ("==&+&'%$ #%,5&#$ )=$
/)*.,'4$ (&-&0).*&'%;$ I!"0&$ 83#"'&##$ ,'5&0#$ %4."/,004$ .+)-"(&$ #&&($
=3'("'56$-&'%3+&$/,."%,0"#%#$.+)-"(&$&,+04@$,'($&7.,'#")'$#%,5&$="','/"'5;$
M&'%3+&$/,."%,0"#%#$1"00$%4."/,004$0))>$,%$&7"%"'5$%!&"+$"'-&#%*&'%$D@Q$4&,+#$
,=%&+$ "'-&#%"'56$ %4."/,004$ %!+)35!$ "'"%",0$ .380"/$ )==&+"'5#$ 9HGF:$ )+$ %+,(&$
#,0&#;$K&%1&&'$&7.,'#")'$#%,5&$,'($HGF6$%!&+&$*,4$8&$,(("%")',0$="','/"'5$
+)3'(#$84$Private!Equity$=3'(#;$A)+$,$!&,0%!4$-&'%3+&$/,."%,0$*,+>&%6$"%$"#$
&##&'%",0$%!,%$%!&+&$"#$#3=="/"&'%$/,."%,0$,'($>')1@!)1$)'$,00$#%,5&#$)=$%!&$
ME$ /4/0&6$ ,#$ 1&00$ ,#$ &7"%$ )..)+%3'"%"&#;$ The term Venture Capital is used to
describe the funding of development and commercialization of new
technologies, products and services. It is also more relevant to less mature
markets with windows of opportunity 11 . This obviously relates more directly to
innovative clean energy technologies, but there are other relevant financial
options for the finance of clean energy companies.

! Private equity for projects is used to describe investment in individual
renewable energy or biofuels projects, or portfolios of such projects.
! Private investment in public equities (PIPE) is used to describe transactions
in which a private equity-type investor takes a significant stake in a
company quoted on the public markets. 12
The term private equity is used generally, or to mean a specific type of private
equity. The European Venture Capital Association (EVCA) defines Private
Equity as “Private equity provides equity capital to enterprises not quoted on a
stock market. Private equity refers mainly to management buyouts,
management buyins, replacement capital and venture purchase of quoted
shares” (EVCA, 2006). They also define Venture Capital, as strictly speaking,
a subset of private equity and refer to equity investments made for the launch,
early development, or expansion of a business. According to AltAssets 13 , the
venture capital term is given to early-stage investments, but there is often
confusion surrounding this term. Many people use the term venture capital very
loosely and what they actually mean is private equity 14 . Categories of private
equity used as a generic term for the investment category include all stages of
private financing from early-stage venture capital to late-stage pre-IPO
investments: leveraged buyout, venture capital, growth capital, angel investing,
mezzanine capital and others.
In this thesis work, the term venture capital refers to investment in young
companies (seed capital, start-up and expansion stages) and the term Private
Equity is used to describe investors in what is called “later stages” or generally
replacement capital and buy-outs, but also the latter-parts of the expansion
stage. In terms of how venture capital mainly differs from other types of
company finance, Brewer and Genay (1994) and Brewer et al. (1997) provide
empirical evidence that external private equity in the form of venture capital is
more likely to be used to finance intangible assets and activities that generate
little collateral, while external private debt is more likely to be used to finance
12 Again, this thesis will focus only on venture capital and private equity for companies, and will not
focus on private equity for projects, nor private investment in public equities (PIPE).
13 http://www.altassets.com/hm_glossary.php
14 It is important to note that sometimes there is also a blur between what start-up and expansion
finance is. For example, fund managers may call themselves a private equity fund, but actually they are
a venture capital fund which focuses on start-up stages.
32

tangible assets. Firms in the earliest stages are the most prone to capital
rationing and liquidity constraints because the uncertainty and asymmetric
information are the greatest for these stages. Understanding which policies and
incentives promote the raising of more focused early-stage funds may allow
one to make better recommendations about promoting new entrepreneurial
firms (Gompers and Lerner, 2004a).
Stage
+
Cash Flow
–
Source
Seed
financing
development,
product
concept
market
analysis
own funds
business
angel
Early stage financing
Start-up
financing
foundation,
ramp-up of
production
marketing
concept
First stage
financing
start of
production
market
launch
public support,
venture capital
Second stage
financing
building /
expanding
distribution
channels
private equity
Expansion stage financing
Third stage
financing
bank loans
Fourth stage
financing
expanding production
and distribution / sales
re-definition of
corporate
governance
Source: B. Rudolph, 2001, p. 507
t
bank loans,
IPO
Figure 6: The investment chain and stages of investment along the chain
(Depending on the stage of firm development, different financing sources dominate. Case of a high-
growth venture; Source: B. Rudolph, 2001)
3.2 Clean energy private equity investment
SEFI/NEF (2007) report that globally from 2005 to 2006 there was overall a
43% growth in clean energy investment. $70.9 billion of investment was made
in 2006 (SEFI/NEF, 2007). They report that the sectors with the highest levels
of investment are wind, solar and biofuels, which reflects technology maturity,
policy incentives and investor appetite. Levels of investment are similar
between the United States and the European Union (27 Member States), with
U.S. companies receiving more technology and private investment, and EU-27
capturing the majority of publicly quoted companies. They also note that
33

investment in developing countries is increasing quickly, mostly in China,
India and Brazil (SEFI/NEF, 2007).
Taking one clean energy area as an example, the solar energy technology sub-
sector, in particular, is booming of late. For example, some predict a fourfold
increase in the annual revenues of the global solar equipment industry from $20
billion last year to $90 billion in 2010 (Marsh, 2007), with one specialist saying
“We are seeing incremental changes in innovation which are pushing down
costs and helping the sector’s expansion”, implying that falling costs overall
have made solar power increasingly competitive and propelled its growth”.
However, NEF writes that 82 constituents of the NEX at the end of last year,
representing the largest and most liquid players in the industry in the world, 32
(39%) were not yet profitable in 2006.
Billions of US$
80
70
60
50
40
30
20
10
0
27.5
49.6
70.6
2004 2005 2006
Figure 7: Total clean energy investment growth in recent years
Estimated Global (Total) Investment in Clean energy, 2004-2006 (US$ Billions) Note: Figures are
based on New Energy Finance Desktop database and industry estimates from various sources. Source:
New Energy Finance (2006).
One of the fastest growing sub-components of this total investment in clean
energy is private equity and venture capital investment. However, overall
VC/PE investment is small compared to asset finance or other types of clean
energy finance, as shown in Figure 8.
34

Figure 8: Global investment in sustainable energy by type, 2004-2006
Source: SEFI/ NEF (2007)
According to SEFI/NEF venture capital (VC) and private equity (PE) have
increased significantly from $2.7 billion in 2005 to $7.1 billion in 2006, and
look set to continue this growth in 2007. The majority of this growth is private
equity investment for companies, not venture capital, as indicated previously.
This can possibly be explained by the fact that private equity can generate
returns for investors via the use of sophisticated financial leverage techniques
and often do not need to generate the level of growth in individual invested
companies needed by venture investors (European Commission, 2003). This
situation (the need for high expected growth for VC investments) might be
exasperated in the clean energy sector, given that the sector lacks a historical
track-record for clean energy VC investments, compared to other sectors.
35

Figure 9: Estimated Global Venture & Private Equity Investment by type,
2001-2006
Note: VC = Venture Capital; PE - Asset/capacity investment is for private
equity for projects, PE - Buy-out/corp spin-off is late-stage private equity for
companies. Source: SEFI/NEF (2007).
Nevertheless, Figure 10 shows that despite the growth in private equity and
venture capital for companies, this growth is still a small part of the overall
current worldwide annual investment in the clean energy sector (7.1 Billion
US$ compared to 70.9 Billion US$ of total clean energy investment). While
there has already been significant growth in VC/PE for clean energy since 2005
(from 1.7 Billion US$ in 2005), early stage VC investment may be lacking a
little bit. Early-stage VC investments are important as they support the entire
value chain.
However, another way of looking at these figures is that “VC activity has
moved up the maturity spectrum”, with later funding rounds attracting most
investment. For example, there was noticeably higher investment in China
during 2006, most of which was private equity for solar manufacturing
expansion. Biofuels, biomass & waste, solar and wind in roughly equal shares
dominate private equity investment for expansion, according to SEFI/NEF
36

(2007). They report that in early 2007, all stages of venture capital and private
equity investment saw increased activity, with later-stage leveraged private
equity investments especially strong.
Figure 10: Global Investment in CE Estimated Annualised Total, 2006
Source: SEFI/NEF, 2007
Figure 11: Clean Energy Venture / Private Equity, by country, 2001 – 2005
Note: Number of deals in brackets. Source: SEFI/NEF (2007).
37

This growth also differs by region. Of the 1.7 Billion US$ of clean energy
venture capital and private equity finance for companies in 2006, most of the
growth and investment was in North America, and in particular in the United
States (see Figure 11). Meanwhile, this can be expected to some extent because
the U.S. has historically had more of a venture capital investment culture
compared to Europe and the United States is a good market for clean energy
company expansion to occur (European companies tend to expand there as
well).
38

4 Literature Review on Policy and Innovation
4.1 The innovation chain, the investment cycle, and
policy
According to Grubb (2005), “to foster technologies right across the innovation
chain requires policies that bridge the “technology valley of death 15 ” (Figure
12) and, where successful, can carry technologies on into the phase of large-
scale diffusion.” Figure 26 indicates three such classes of policies. Grubb
(2005) notes these should be combined with the generic need for
‘internalisation’.
Figure 12: The Cash Flow Valley of Death as a function of development stage
(Time), with typical investors shown for the various stages; Source: Murphy and
Edwards (2003)
Market Engagement programmes relevant to the start of the innovation chain
move a ‘trial technology’ from public R&D funding to engagement with the
15 The technology “valley of death” is discussed in Murphy and Edwards (2003). Significant financial
resources are required for early enterprises over an extended period of time during which the cash flow
is quite negative (the so called Cash Flow Valley of Death) as described in the cash flow curve in
Figure 12. But to get these resources, entrepreneurial ventures must be able to assuage the risk
perceptions of private sector investors by demonstrating significant progress towards these
achievements – a sort of “Catch – 22”. The concept of the valley of death, from a technology
development perspective, has been around for a number of years. The cash flow valley of death
provides a financial resource perspective and overly that extends this concept (Murphy and Edwards,
2003).
39

private sector. Moving along the chain, Strategic Deployment policies build
market scale and thereby buy-down the cost of technologies. Finally, “Barrier
Removal” or “internalization policies” aim to establish a ‘level playing field’
through removal of regulatory and institutional barriers that generally favour
incumbent technologies.
Internalization policies may operate in different ways at many stages of the
innovation chain. Grubb (2005) notes that emissions cap-and-trade or emission
taxes, which seek to internalize the environmental damages which are
associated with incumbent technologies and thereby improve the economics of
alternatives, are most active towards the end of the innovation chain (shown at
the bottom of Figure 13). The investment cycle as it correlates with the
innovation chain (illustrative) is shown at the top of Figure 13. Internalization
policies are therefore most relevant to private equity investors that generally
invest in technologies at the end of the innovation chain (or fully commercial
technologies).
Figure 13: Investment and innovation chain, with corresponding policies
Note: adapted from Grubb (2006).
It is important to understand the innovation chain and how it relates to the
investment cycle (Figure 13) in order to relate policies relevant to this industry
40

to various stages along the chains. Certain policies are clearly more relevant to
investors depending on which technology they are investing in and at what
stage the technology is at the time of investment. However, Grubb (2005) also
points out that ‘learning by doing’ earlier in the innovation process is from an
economic perspective also an expression of external benefits, to the extent that
the knowledge becomes available to all future developers. Later in time, this
also benefits investors that are active in the latter part of the investment cycle.
Ideally, it would be best to analyze policies according to their effectiveness at
supporting the process more or less directly at different stages. At least, in any
assessment of policy effectiveness one should try to consider how a given
policy impacts the entire investment community – from early-stage technology
investors to project financiers.
In addition, policies that promote wind power production via the cheapest
available wind power technologies are affecting investments at the later stages
or even more so, they affect project financiers. However, they may also impact
investments at early stages like first round VC spending at least indirectly by
perhaps creating the impression that the clean energy sector can effectively
compete with the conventional energy sectors (this potential affect was
supported by an interview with a couple of project financiers which
acknowledged this potential affect on VC and private equity finance).
The concept of ‘dynamic efficiency’ or the efficiency of a policy applied to the
innovative phase of the product cycle to stimulate significant changes in clean
energy technologies and infrastructures over time amplifies the role of venture
capitalists and private equity investors in the commercialization and rapid
market diffusion of these technologies, which would be accompanied naturally
with the rapid growth of the companies they invest in.
In the introduction to this thesis market-failure has been discussed with regard
to innovation. This section describes two types of policies that are used by
various governments in a number of sectors where market-failure occurs. They
are referred to in this thesis as: ‘Technology-Push’ policies and ‘Market-Pull
policies’. The ‘Technology-Push policies’ have also been termed ‘Product-Push
policies’, as well as ‘Market-Push’ in the literature stream on these policies.
They are also referred to sometimes as ‘Innovation Policies’, although this does
41

not mean that ‘Market-Pull Policies’ do not also simulate innovation. The
difference is that technology-push programs and instruments are more directly
impacting the early stages of the technological innovation process. They
provide incentives to invest in activities including niche market deployment
that lead to technological innovation, as opposed to the deployment of
innovative technologies. Market-pull policies stimulate innovation indirectly
via changing market conditions for innovative products and services.
G+&-")3#$ 1)+>$ !,#$ ("#/3##&($ %!&$ -,+")3#$ +&,#)'"'5$ 8&!"'($ %!&$ '&&($ =)+$
*,+>&%@.300$ .)0"/"&#$ 9N+3886 2005, Midttun and Gautesen, 2006; R&','%&,36$
&%;$,06$DSSTU$&%$ '"/!&#$ ,'($
.+)5+&##$)'$%!&"+$0&,+'"'5$/3+-&#;$&#$%!&*$,%%+,/%"-&$=)+$5)-&+'*&'%#;$M&'%3+&$E,."%,0"#%#$0))>$=)+$
"'-&#%*&'%#$%!,%$/+&,%&$.+"-,%&$+,%!&+$%!,'$#)/"&%,0$-,03&;$O))>"'5$#%+"/%04$
,%$.+"-,%&$-,03&6$%!&$&23,%")'$*"5!%$)=%&'$0))>$3'=,-)+,80&6$,#$("#/3##&($"'$
I3&#%&'!,5&'$ ,'($ ?&..)$ 9DSSV:$ =)+$ #3#%,"',80&$ &'&+54$ %&/!')0)5"&#6$
#"'/&$%!&4$,+&$&,+04$)'$%!&$0&,+'"'5$/3+-&$,'($!&'/&$%!&4$)=%&'$!,-&$!"5!&+$
/)#%;$J"(&@8&'&="%#$/,'$.,+%04$)==#&%$%!"#$("#,(-,'%,5&;$J)$1!"0&$"'-&#%*&'%$
'&&(#$,+&$!35&$"'$%!"#$#&/%)+6$"%$"#$')%$%+"-",0$1!&%!&+$%!&+&$1"00$8&$%!&$+"5!%$
"'/&'%"-&#$ %)$ *)8"0"L&$ &')35!$ .+"-,%&$ /,."%,0$ 9HY&%;
Different clean energy sub-sectors also require different levels of support,
mainly because the costs of energy from various technologies and sources are
at varying competitiveness levels with conventional energy technologies and
sources today. There is a philosophical debate in the energy-related literature
today about which clean energy technologies should continue to be supported
and at what level of support society should continue to offer to these emerging
technologies, and for what benefits to society. More consensus exists about the
42

need for consistent policy that is crucial for the technology and companies in
this area to become competitive during the learning phase.
In particular to this debate is the long-term dynamic efficiency of policy that
stimulates investment in innovation. Dynamic efficiency is achieved when
society pays less over time for a given emission reduction target or sustainable
energy goal set in the future. This occurs when we invest as a society today in
innovative energy technologies that can assure that we reach a sustainable
energy and cost optimal energy mix in the next decades. Meanwhile, the short-
term static economic view would argue that decisions we take today should be
based on cost-effectiveness assessments for society given today’s energy needs
and today’s most cost-effective technologies (least cost options to achieving a
given annual environmental or sustainable energy-related target). As for
specific policies to promote both visions, there is also a healthy debate in the
energy policy literature about the use of price-based and quantity-based
instruments, among other attributes of specific public policy measures to
address our energy and environmental challenges of today and the future.
Meanwhile, there are differences in experience by country or region. For
example, a set of feed-in tariffs, being a price-based mechanism, is the most
often used support mechanism for renewable electricity in Europe, and is now
the world’s most prevalent national policy largely because of the example set in
Denmark, Germany and Spain. Feed-in tariffs require utilities to provide
renewable generators with a long-term fixed price for electricity. In the United
States, quota-based systems (quantity-based instruments) are used. Twenty-
three U.S. states have enacted binding renewable portfolio standard laws or
renewable portfolio goals. RPS policies seek (originally) to create price
competition between renewable generators. Tax credits (production tax credits)
are also used in the United States to encourage investment in renewable
electricity from wind, primarily. Meanwhile, a few U.S. states have now put in
place fixed-price policies and several others are considering feed-in tariffs
based on the European model. New analyses project that existing state RPS
laws will meet only 16 percent of U.S. load growth and are insufficient alone to
“carve away at current use of conventional generation” (Eggers and Dennison,
2006). However, the debates about policy are quite different in Europe
compared to the United States. In Europe people debate about which policies
43

are most effective, and in the U.S. people debate about whether policy is
needed at all (Rickerson, et al., 2007).
4.2 International policy, CO2 emissions trading and
CDM/JI
The Kyoto Protocol calls for the implementation of policies and measures in
order to curb global warming and introduces the so-called flexible mechanisms,
which can be used by parties to meet part of their GHG reduction obligations.
The Kyoto Protocol offers an over-arching framework for countries to meet
greenhouse gas emissions reduction goals via a number of their own set of
customized policies and measures (including the possibility of trading
emissions via the three Kyoto mechanisms described above). More generally,
the effect of the Kyoto Protocol has been felt in markets located in signatory
countries (according to New Energy Finance, 2005). NEF also noted that as at
30 December 2005, clean energy stocks listed on markets in signatory countries
were an average of 68% higher than stocks listed in non-signatory countries
since Kyoto came into effect in February 2005.
One of the KP mechanisms is International Emission Trading 16 (IET). IET
provides for Annex I Parties to acquire units from other Annex I Parties. These
units may be in the form of assigned amount units (AAUs), removal units
(RMUs), ERUs and CERs. International emission reductions are an important
part of any emissions trading scheme, but it is crucial to get the domestic
scheme right first (Rosewell, 1999). CO2 emissions trading schemes was
conceived to bring market forces to bear on the climate change problem.
Generally, this type of scheme has been believed to be more efficient and
effective than administrative measures (Rosewell, 1999). However, it does
imply costs and risks, as well as uncertainty in both emission allowance prices
(as it is a price mechanism), but also in fuel or electricity prices.
Market price uncertainty is driven by weak national allocation plans for the
binding CO2 caps on industrial sectors covered by the scheme, trading
behavior and mixed/late participation. For example, the European Emissions
16 Article 17 of the Kyoto Protocol.
44

Trading Systems’ allocations are quite close to the ‘business as usual’
projections, and far from the Kyoto targets (Grubb, 2006). However, the
introduction of emission allowances is expected to still alter operating costs in
the power generation sector, and is expected to have an influence on the
operation of existing generating capacity as well as the composition of future
investment. Indeed, the carbon “emission allowance” will increase the variable
costs for fossil-fuelled power plants and thus its short-run marginal costs since
an emission allowance will be needed for each unit of CO2 produced (Reinaud,
2003). CO2 emissions trading could also affect industrial sectors in terms of
direct and indirect CO2 emissions, and possibly the transportation sector
depending on how and where it is applied along the well-to-wheel CO2
emission cycle.
Emissions trading can be applied alone with a cap and trade scheme, or it can
be applied in combination with a tax. According to Rosewell (1999), “The best
way to choose what is most suitable is to let firms themselves choose whether
to pay a tax (a CO2 tax) or to engage in trading; “Who can trades, who can’t
pays.” Emissions trading can also be applied under voluntary schemes, such as
via the Chicago Climate Exchange in the United States. Voluntary
commitments (e.g. outside of the Kyoto Protocol) can also work with
voluntarily acquired verified emission reductions (VERs) from projects in less
industrialized countries. Very early attempts to adapt GHG emissions trading to
corporate emission reduction schemes, such as BP’s successful design of an
internal emissions trading scheme, were encouraging.
However, while voluntary schemes have helped increase the momentum
toward mandatory schemes, mandatory economy-wide schemes are considered
the only way to meet Kyoto commitments. Under the Kyoto Agreements, the
European Union is committed to reducing emissions of greenhouse gases to 8
percent below 1990 levels by the period 2008 to 2012. Indeed, the EU
emissions trading scheme (EU ETS) has been seen to be a key component of
the Kyoto Protocol's success. Meanwhile, several states in the United States are
considering the implementation of CO2 emissions trading schemes (the North-
East states and California, in particular).
45

But initial experience with the first phase of the EU ETS was not very
impressive. This testing period set much less aggressive caps. Last year, the
European Commission set tougher new caps on carbon dioxide emissions for
10 nations. The second phase of Europe's emission trading scheme will occur
between 2008 and 2012. The second phase is crucial as 2008 to 2012 is the
period over which countries that have ratified the Protocol must meet their
emissions targets. The trading scheme covers only industrial emissions, while
the Protocol covers all emissions, such those from transportation and
households. Nevertheless, there are many other means towards meeting
emission reduction targets in such sectors and these sectors are probably better
addressed with the use of building and appliance energy efficiency standards
and vehicle standards for CO2 emissions. Under emissions trading, each
country's government divides its allocation between the nation's industries. Any
industrial plant that wants to emit more than it has been given can buy
emissions rights from any other European plant in the scheme (Brahic, 2006).
Reinaud (2003) show that uncertainty in energy markets (e.g. the gas market) is
compounded by the uncertainty regarding stringency of emission allowances
and the consequent demand for new gas-fired plants. “Those uncertainties are
perceived as an additional risk by investors” (Reinaud, 2003). Uncertainty
regarding the stringency of the allocation plans may delay investment decisions.
For example, stringency on the power sector is expected to result partly from
the other sectors’ emissions 17 . Uncertainty also comes from the possibility that
Russia and Ukraine would be given permission and would decide to trade their
assigned amount units (AAUs) on the European ETS. There is also the
uncertainty about what will happen after 2012 and whether the Kyoto Protocol
will ever be ratified by the United States. Companies may decide not to invest
immediately in new power plant technologies or abatement costs. Power
companies may choose to delay their investments or delay the closure of their
most inefficient plants until they know more about how rigorously the Kyoto
Protocol will be implemented.
Reinaud explains that regulatory uncertainties regarding an emissions trading
scheme cannot be removed over the time frame of a typical power plant
17 The forecasted growth of emissions from the transportation sector and household sectors, both of
which are not covered by the cap via the EU ETS, may increase the share of total emissions and other
sectors may bear this increase (Reinaud, 2003).
46

investment (20-30 years). Investors have a short foresight into the ETS (three to
four years for the first and second commitment periods) when they must
commit to a 20-30 years investment. However, she adds that some regulatory
risk (not all) can be transferred to a market price of carbon that should be easier
to manage through options, futures, etc. However, it should be noted that
market price fluctuations might be well managed by certain types of investors,
but not all types.
While emissions trading is supposed to provide additional flexibility to power
companies compared to other regulatory measures such as emission standards,
it should be recognized or at least questioned whether certain types of investors
may even prefer to deal with the stability of an emission standard, or another
types of market-pull instrument, as opposed to the fluctuations of the emissions
trading market. As mentioned before price uncertainty has much to do with
non-market issues such as national allocation plans. Grubb (2006) also points
out that weak allocations for the EU ETS in Phase 1 mean it will not drive
significant investment or innovation. He points to a competitive ‘race to the
bottom’ between Member States, information asymmetries, gaming, and
unfamiliarity, has resulted in weak allocations: prices were initially volatile
with small trading volumes owing to the lack of market confidence, prices are
likely to fall as ‘sellers’ start to release allowances, and there are little market
incentives for emission-reduction investment. He outlines that even the ‘Kyoto
Period’ prices of Euro 10-20/tCO2 were inadequate to drive significant
innovation. He notes they are a small fraction of the current value of
renewables incentives and almost irrelevant compared to final oil product
(transport) prices. Finally, he notes that the long lead-times to prepare and
invest means that weak and sequential allocations militate against investment
and innovation. In particular, the phase 1 period of the EU ETS encouraged
industry to ‘bury head in the sand’ for 3 years, and undermines the legitimacy
of the “most industry-friendly instrument”. Also, the long-term uncertainties
may start to deter carbon-intensive investments but make it inadequate to
justify low carbon innovation-related investments (Grubb, 2006).
One can assume how price fluctuation in the first phase of the EU ETS might
have affected investors’ perception of the real effectiveness of this policy
option in terms of supporting clean energy innovation. Phase I was indeed
47

ough for the entire reputation of this public policy option. A report
commissioned by the Carbon Trust explains that in Europe, 2006 started with
prices for Phase I (2005-7) allowances trading at levels higher than anyone
predicted, and governments confidently issuing draft National Allocation Plans
(NAPs) for how they intended to allocate allowances for Phase II, the Kyoto
period of 2008-12 (Carbon Trust, 2007). The year ended with Phase I prices
sinking close to zero (see darkest line in figure 14), and several countries
threatening to take legal action to overturn the European Commission’s
rejection of almost all the submitted NAPs as inadequate 18 .
Figure 14: European Emissions Trading Scheme (for CO2) and price
development
Source: Carbon Trust, 2007.
Other Kyoto Mechanisms are:
! Joint Implementation 19 (JI) - provides for Annex I Parties 20 to implement
projects that reduce emissions, or remove carbon from the air, in other
Annex I Parties, in return for emission reduction units (ERUs);
18 Concerns from some commentators about overall shortage in Phase I proved groundless, when in
May 2006 the release of data on verified emissions for 2005 showed a substantial surplus. The price
halved overnight, and as the situation clarified over subsequent months, it sank further. The final tally
showed that emissions in 2005 were about 100Mt (5%) below the allocated amount, and shortly after
the Phase I allowances in the new year became essentially worthless. Preliminary data for 2006 show
that emissions increased, but nothing like enough to absorb the excess supply of allowances (Carbon
Trust, 2007).
19 Article 6 of the Kyoto Protocol
48

! Clean Development Mechanism 21 (CDM) - provides for Annex I Parties
to implement projects that reduce emissions in non-Annex I Parties, in
return for certified emission reductions (CERs), and assist the host
Parties in achieving sustainable development and contributing to the
ultimate objective of the Convention.
The commercial attractiveness of investing in such foreign emission reduction
projects is related to a sufficiently high global market price for emission
reductions, and this is based on well-functioning emissions trading schemes in
developed countries, like the EU ETS. The Carbon Trust explains that the high
carbon price of 2005-6 under the European ETS stimulated explosive growth
for CDM and JI projects, with almost two billion tonnes of such emission
reductions (cumulative up to 2012) now submitted for registration with the
relevant international authorities (the CDM Executive Board that operates
under the Kyoto Protocol). With growing supply also from Joint
Implementation projects in Eastern Europe, the total grows monthly and is
expected to top three billion of CO2-equivalent (Carbon Trust, 2007).
While projects in certain fields like waste-to-energy in the developing world
received something of a boost from the CDM mechanism, the CDM is not
intended to support technological innovation in the energy sector. It is intended
to promote sustainable development via technology transfer of already fully
commercial technologies. In other words, it is intended to stimulate investment
in “low hanging fruits” among carbon mitigation technological options.
Meanwhile, the environmental integrity and commercial attractiveness of CDM
projects also depends on making the process of obtaining the CERs simple,
equitable and cost-effective (Solis, 2007). Therefore, there is a great need for
organizations to monitor the environmental integrity of the use of the
mechanism. Finally, smaller firms may avoid the CDM and invest outside of
the official certification process. This calls for a voluntary market of verifiable
credits under a separate system, but which also ensures the environmental
integrity of such projects.
20 Annex I Parties to the Kyoto Protocol are mostly industrialized countries.
21 Article 12 of the Kyoto Protocol
49

Other options for international climate and energy policy frameworks which
have been discussed include: 1) sector-by-sector agreements to meet specific
targets related to specific industries, and 2) international cooperation on R&D.
However, only R&D cooperation has so far taken some form. Meanwhile,
many people seem to now recognize the need for sector-by-sector agreements
in especially the most energy-intensive or most carbon-intensive sectors. Sector
approaches could be a way to advance with significant greenhouse gas
emission reductions in countries that have not ratified the Kyoto Protocol like
the United States, or countries without binding limits under the Kyoto Protocol,
like China and India. Sector-by-sector approaches that could involve
international commitments with regard to clean energy, or more specifically
renewable energy targets, could be an additional component of a more general
framework such as the UNFCCC negotiations and the Kyoto Protocol. There
are significant challenges in both the political process for coming to an
international agreement and in the implementation of such agreements
thereafter. Unfortunately, one cannot rely too heavily on international
agreements either; as there are often few significant repercussions associated
with breeching internationally agreed environmental targets. A high-level
agreement to address subsidies in the energy sector for conventional fuels, in
combination with the Kyoto Protocol under the UNFCCC, would be another
option, yet quite an idealistic one.
4.3 National or state policy
Government support is a key feature of alternative energy development.
National policies directed at specific parts of the energy sector, or specific
sectors (e.g. the automotive sector) appear to be most efficient in terms of
stimulating significant change in a given problem sector. Renewable energy
technology is promoted by a variety of national energy policy options focused
on mainly the electricity and transportation sectors of the economy.
4.3.1 Renewable energy targets
At least 48 countries have renewable energy policy targets in place (REN21,
2005). The EU has Europe-wide targets as well: 21 percent of electricity and 12
percent of total energy by 2010. Most national targets are for shares of
electricity production, typically 5–30 percent. Other targets are for shares of
50

total primary energy supply, specific installed capacity figures, or total amounts
of energy production from renewables, including heat. Most targets aim for the
2010–2012 timeframe (REN21, 2005). Furthermore, several developing
countries have renewable energy targets now. In addition, 18 U.S. states (and
the District of Columbia) and 3 Canadian provinces have targets based on
renewables portfolio standards (although neither the United States nor Canada
has a national target). An additional 7 Canadian provinces have planning
targets (REN21, 2005).
Table 1: Non-EU countries with renewable energy targets (REN21, 2005)
China’s target of 10 percent of total power capacity by 2010 (excluding large
hydropower) implies 60 GW of renewables capacity given projected electric-
power growth. China also has targets for 2020, including 10 percent of primary
energy and 12.5 percent of power capacity, 270 million square meters of solar
hot water, and 20 GW each of wind and biomass power (REN21, 2005).
4.3.2 Policies for renewable electricity promotion
At least 48 countries—34 developed and transition countries and 14 developing
countries—have some type of policy to promote renewable power generation
51

(REN21, 2005). Feed-in laws are the most common existing policy. It has been
enacted in many new countries and regions in recent years. The U.S. was the
first country to enact a national feed-in law (PURPA), in 1978. However, most
implementation was discontinued in the 1990s. They were then adopted in the
early 1990s by Denmark, Germany, Greece, India, Italy, Spain and
Switzerland. 32 countries and 5 states/provinces had adopted such policies by
2005. More than half of these have been enacted since 2002. As for developing
countries, the first to establish feed-in tariffs was India, followed by Sri Lanka,
Thailand, Brazil, Indonesia and Nicaragua. In the first half of 2005, China
Ireland, Turkey, and the U.S. state of Washington enacted feed-in laws
(REN21, 2005). China’s comprehensive renewable energy promotion law
enacted in February 2005 included a feed-in policy.
Sawin (2004) notes that energy markets are not now and never have been fully
competitive and open, and today’s markets include substantial institutional
barriers, as well as long-term subsidies for conventional energy, that act as
obstacles to renewable energy. She recalls that even market-oriented countries
such as the United States and United Kingdom now agree that subsidizing
renewable energy makes sense. Support for renewables is important not only to
incorporate the external costs (environmental, social and security) of energy
production and use, and make up for decades of past support for conventional
energy. It is also essential to account for the environmental, social and security
benefits associated with renewables—including the reduced risk of fuel price
volatility, a more diversified portfolio of energy options, a cleaner environment
and better health, and job creation and economic development. She notes that
well-designed, modest production-based subsidies provided up front can work
rapidly to close the cost gap between renewables and conventional energy
systems.
52

Table 2: Renewable Energy Promotion Policies (REN21, 2005)
53

Table 2: Continued (REN21, 2005)
A sample of country approaches to policy-making in the main growth regions
for renewable energy worldwide is provided below (source: Renewable Energy
Global Status Report 2006). Such legislative support schemes provide the
security and financial support for this developing sector.
Germany: Feed-in tariff support schemes for wind and solar electricity. Solar –
20-year contracts, subsidized at Euro 54 cents/kW. Wind electricity – 20 year
contracts, Euro 8/kW. Biofuels – tax exemption for bioethanol, lower taxes for
biodiesel.
Spain: Targets in line with the EU white paper. Feed-in tariffs offered for wind
and solar. No digression rates for solar or wind.
France: The government has a goal to reach renewables’ share of electricity
generation from 14% today to 21% as of 2010. There is a biofuels target of 7%
of transport fuels by 2010. There are plans to reduce nuclear dependence from
78% to 73% of generation while increasing renewables. Meanwhile, France is
not on target towards its renewable energy share, but there are existing
incentives for wind energy and now recently a feed-in tariff has been approved
for solar PV. Integrated PV systems in buildings will be particularly
encouraged.
EU-25: Key “white paper target” – 12% of energy consumption provided by
renewables by 2010. Also, targeting 5.75% of all transport fuels from biofuels
by 2010.
54

U.S.: “Advanced Energy Initiative” announced by President Bush in January
2006 – Replace more than 75% of oil imports from the Middle East by 2025.
R&D budgets for solar, wind, biofuels, and biomass. California state solar
initiative approved January 2006. RPS policies exist in various states. The
federal production tax credit (PTC) for wind power has had a significant impact
on wind investment. Unfortunately, its application has been inconsistent.
Table 3: Cumulative Number of Countries/States/Provinces Enacting RPS
Policies
Korea: Started a fixed price power purchase scheme in May 2002
(W716.40/kW). Targets installation of 1,300MW capacity by 2012 (2004
Government target).
Brazil: “Profina project” aims to add 3,300MW of renewable energy within 3
years. A world leader in the ethanol industry with mandatory blending since the
late 1970s. Biodiesel capacity expansion in progress.
India: Targeting 10% of electricity generation by 2012. 10% of oil
consumption from biofuels by 2032. Offers 10 year tax exemption on
renewable electricity – wind and solar.
China: Targeting 16% of primary energy from renewables by 2012. Targeting
30,000MW of wind capacity by 2020. China will invest US$100 billion in
renewable energy projects by 2020. China plans to raise its electricity installed
capacity for renewable energy to 10% of its total power capacity by 2010 and
16% by 2020.
55

4.4 Market-pull policies studied
As we have seen, a wide array of policies can be applied in any given country,
among market-pull and technology-push policy options. The options among
market-pull policies, which are studied in this thesis work, are shown below.
Market-pull policy options considered in this thesis
! Feed-in tariffs (e.g. subsidies for renewable energy market take-up)
! Reduction of fossil fuel subsidies
! GHG or CO2 emissions trading
! Renewable Portfolio Standards (RPS)
! Renewable fuel standards or targets
! Green (renewable energy) quotas and certificate trading
! General CO2 tax or energy tax
! Residential and commercial tax credits for RE
! Kyoto Mechanisms (e.g. CDM, JI)
! Government procurement of clean energy
! Production tax credits (e.g. for wind)
! Technology performance standards (eg. vehicle pollution standards)
This section explains further a few of the most important policy options listed
above.
According to the European Commission, two aspects are important for the
deployment of renewable electricity:
! Firstly, the financial support, and
! Secondly, the reduction of administrative and grid barriers (considered
under “regulatory issues” in this thesis).
Concerning financial support a range of different systems is currently
operational in Europe, of which the two most important are feed-in tariffs and
green certificate systems.
! Feed-in Tariffs exist in most of the Member States. These systems are
characterised by a specific price, normally set for a period of around several
56

years (generally 20 years), that must be paid by electricity companies,
usually distributors, to domestic producers of green electricity. The
additional costs of these schemes are paid by suppliers in proportion to their
sales volume and are passed through to the power consumers. A federal (or
provincial) government regulates the tariff level that is usually based on the
marginal electricity generation costs. It normally takes the form of either a
total price for RES-E production, or an additional premium on top of the
electricity market price paid to RES-E producers 22 . Apart from the level of
the tariff, its guaranteed duration is an important parameter when assessing
the actual financial incentive (FEA, 2006). A variant of the feed-in tariff
scheme is the fixed-premium mechanism currently implemented in
Denmark and partially in Spain. Under this system, the government sets a
fixed premium or an environmental bonus, paid above the normal or spot
electricity price to renewable electricity generators.
! Under the Green Certificate System, renewable electricity is sold at
conventional power-market prices. Recently, some European countries have
replaced their existing policy schemes by a quota obligation. The basic
principle of this system is the determination of an obligation for consumers,
suppliers or producers to provide a certain percentage of electricity using
RES. Generally, quota obligations or RPS requirements (see below) are
implemented in combination with tradable green certificates. The revenue
from selling green electricity comprises the market electricity price as well
as the value of the green certificates. In order to finance the additional cost
of producing green electricity, and to ensure that the desired green
electricity is generated, all consumers (or in some countries producers) are
obliged to purchase a certain number of green certificates from renewable
electricity producers according to a fixed percentage, or quota, of their total
electricity/production. Since producers/consumers wish to buy these
certificates as cheaply as possible, a secondary market of certificates
develops where renewable electricity producers compete with one another
22 According to Butler and Neuhoff, 2004, the Feed-in Tariff, was first adopted in California under the
Public Utility Regulatory Policies Act (1978). This required utilities to purchase power from
'Qualifying Facilities', especially small renewable generators, at ‘avoided cost’ rates. These rates,
which reflected the marginal cost of acquiring the same amount of energy from an alternative source,
were determined by the state utility commissions. Many commissions pegged the rates to high oil
prices, resulting in highly favorable guaranteed payment and stimulating renewable development (IEA
2004a).
57

to sell green certificates. Compared to feed-in tariffs, quota systems are
sometimes classified as a strongly market-oriented policy system 23 .
Tradable renewable energy certificates are also typically used in
conjunction with voluntary green power purchases or obligations under
renewables portfolio standards. At least 18 countries had schemes and/or
markets for tradable certificates.
Other important market-pull policies considered in this thesis:
! Renewable Portfolio Standards (RPS) - Renewable Portfolio Standards
(RPS) are state policies mandating a state (or country) to generate a percent
of its electricity from renewable sources. Each state has a choice of how to
fulfill this mandate using a combination of renewable energy sources,
including wind, solar, biomass, geothermal, or other renewable sources.
Some renewable portfolio standards will specify the technology mix, while
others leave it up to the market (CREST, 2007). Several European and other
countries have RPS mandates as well.
! Production Tax Credit (PTC) (or direct production payments, e.g. per Kwh)
– Energy production payments or tax credits exist in several countries.
Production tax incentives are generation-based, price-driven mechanisms
that work by permitting exemptions from the electricity taxes applied to all
producers. Thus this type of instrument differs from premium feed-in tariffs
solely in terms of the cash flow for RES-E producers: it represents an
avoided cost 24 rather than additional income (FEA, 2006). One should note
that only certain large tax-generating types of producers could really benefit
from this policy. In the U.S., the federal Production Tax Credit (PTC) is
considered by some to be the most significant policy driving wind power
production. Those producing electricity from wind, closed-loop biomass
and poultry waste receive 1.5 cents (adjusted for inflation) for each kWh
produced during the first ten years of a plant’s operation. The federal PTC
has been instrumental in spurring the development of wind power since its
23 Federal Environment Agency, EU Renewable Energy Policies Review, 2006.
24 This credit in the U.S. has applied to more than 5,400 MW of wind power installed from 1995 to
2004. Indexed to inflation, the credit started at 1.5 cents/kWh in 1994 and increased over time, through
several expirations and renewals, to 1.9 cents/kWh by 2005, with expiration extended to 2007 (REN21,
2005).$
58

adoption in 1992, but its on-off again aspect has created uncertainty in the
market for investors and added costs as a result (Reeves and Beck, 2003). 25
Other countries with production incentives include Finland, the
Netherlands, and Sweden (REN21, 2005).
! Renewable Fuel Standards (RFS) - A renewable fuels standard requires that
an increasing percentage of transportation fuel sold must be biofuel (e.g.
ethanol or biodiesel). This policy can feature a credit trading system to
allow refiners, blenders, and retailers to buy and sell credits from each other
to meet their goals (CREST, 2007). Several countries have RFS mandates,
including the United States. In April 2007, the U.S. Environmental
Protection Agency established the nation’s first comprehensive Renewable
Fuel Standard (RFS) program, primarily to reduce dependence on foreign
sources of energy 26 . Another type of policy for renewable fuels is renewable
fuel price subsidization, but this option was not considered in the surveys
and interviews conducted for this thesis 27 .
! Technology Performance Standards (or generation performance standards)–
For example, in the United States, performance standards have been used in
legislation to reduce CO2 emissions from vehicles via a fleet-wide CO2
performance standard on manufacturers of passenger vehicles. A CO2
performance standard for power plants is a potential policy option as well.
This approach has been effective for energy efficiency in the United States
25 This uncertainty is causing wind developers to incur added costs as they rush to get new plants
online before the PTC expires again. Some experts say the future economic viability of wind power is
also causing under-investment in wind energy. Meanwhile, some U.S. states also provide tax incentives
to wind developers. These incentives include investment tax credits, production tax credits, and
property and sales tax incentives. The state investment tax credits have been found to lessen the value
of the federal PTC, due to “double-dipping” provisions in the latter (Reeves and Beck, 2003).
26 This is related to the Alternative Fuel Standard (AFS) proposal which builds on the RFS and requires
use of 35 billion gallons of renewable and alternative fuels in 2017 - nearly five times the RFS target of
2012. The AFS proposal will supposedly displace 15 percent of projected annual gasoline use in 2017
through the use of fuels, including corn ethanol, cellulosic ethanol, biodiesel, methanol, butanol,
hydrogen, and other alternative fuels (US EPA, 2007).
27 There is some debate about whether first generation ethanol, for example, should continue to be
heavily subsidized in countries like the United States. According to Runge and Senauer (2007). “High
oil prices over the past few years have made ethanol naturally competitive, but the U.S. government
continues to heavily subsidize corn farmers and ethanol producers. Direct corn subsidies equaled $8.9
billion in 2005. Although these payments will fall in 2006 and 2007 because of high corn prices, they
may soon be dwarfed by the panoply of tax credits, grants, and government loans included in energy
legislation passed in 2005 and in a pending farm bill designed to support ethanol producers. The federal
government already grants ethanol blenders a tax allowance of 51 cents per gallon of ethanol they
make, and many states pay out additional subsidies.”
59

and air pollution. It is may soon be applied in California (and other states)
in that a standard for CO2 emissions is to be set for manufacturers’ vehicle
fleets sold (if the courts favor California in a lawsuit with automakers). This
approach allows for flexibility in that vehicle manufacturers can produce
more CO2-intensive vehicles, as long as they compensate them for lower-
emission vehicles. However, it ensures by setting the standard at an
appropriate level (e.g. the most ‘cost-effective’ level) that the best available
technologies will be applied in the given sector. In the automobile sector,
the best available technology (now commercially available) is hybrid
vehicle technology. Other manufacturers are working on fuel cell vehicles
that they have announced will soon be commercially available (e.g. 2015
for General Motors 28 ).
Barrier reduction policies considered:
! CO2 tax (or carbon tax or energy tax) – One major form of supporting
renewable energy is through stimulation of renewable energy consumption
by price reduction or a price increase among non-renewable energy sources.
A tax can be applied to internalize external costs and can be applied in the
form of a CO2 tax, a carbon tax or an energy tax. A CO2 or carbon tax$
1)30($!,-&$.)#"%"-&$&==&/%#$)'$+&'&1,80&$&'&+54$#)3+/&#6$/)*.,+&($%)$
=)##"0$ =3&0$ #)3+/&#$ )=$ &'&+546$ 83%$ "%$ 1)30($ ,0#)$ !,-&$ .)#"%"-&$
/)*.&%"%"-&'&##$ &==&/%#$ )'$ '3/0&,+$ &'&+54 DP;$

! CO2 emissions trading (or GHG cap and trade) – This has already been
presented under international policy as it is related to the Kyoto Protocol.
! CDM/JI (already presented under international policy)
! Reduction of fossil fuel subsidies (or conventional energy sources) -
Distortions in the electricity market, for example, are in the form of direct
and indirect subsidies, and the social cost of externalities currently excluded
from costs of electricity production. EWEA/Greenpeace (2005) points out
in their report, “Subsidies to fully competitive and polluting technologies
are highly unproductive, seriously distort markets and increase the need to
support renewable. Removing subsidies to conventional electricity would
not only save taxpayers’ money and reduce current market distortions in the
electricity market. It would also dramatically reduce the need for renewable
support. Wind power would not need special provisions if markets were not
distorted by the fact it is still virtually free for electricity producers to
pollute”.
4.4.1 Feed-in Tariffs
At present, the system of fixed feed-in tariffs (FiT) is the dominant policy
scheme for promoting electricity generation with renewable energy sources
(RES) in Europe. A Feed-in Tariff scheme involves an obligation on the part of
electric utilities to purchase the electricity produced by renewable energy
producers in their service area at a tariff determined by the public authorities
and guaranteed for a specified period of time.
61

Figure 15: Renewable Electricity Policies in EU Member States as of February
2007
Source: Rickerson, et al., 2007.
They have a track record of some two decades and are well established
throughout the European Union. It is important to note that Feed-in tariffs
allow technology-specific and band-specific promotion as well as an
acknowledgement of future cost-reductions by implementing decreasing tariffs
leading to a high dynamic efficiency (FEA, 2006). Indeed, in Germany, under
the EEG 30 , feed-in tariffs are differentiated by: technologies, according to size,
development status, and according to site (BWE 31 , 2007). With feed-in tariffs,
different tariffs can be defined for different technologies (wind, solar, biomass,
etc.) or different countries depending on resource conditions (e.g. solar
irradiation). The rate of a FiT is furthermore reduced each year for new
installations in order to stimulate a decrease in production costs.
30 In Germany, the original policy (StreG, Stromeinspeisungsgesetz, 1991) required public energy
supply companies to buy power as supplied by renewable generators at 90% of the average price of
electricity as charged to final consumers in the previous year. A decline in electricity prices, and thus in
payments to renewable generation, prompted the introduction of a fixed tariff, effective from 2000
onwards (EEG, Erneuerbare-Energien-Gesetz, 1998).
31 German Wind Energy Association (BWE) See: www.wind-energie.de
62

The Feed-in Tariff system operates as a subsidy allocated to producers of
renewable electricity. The cost of subsidizing producers of RES-E is covered
either through cross-subsidies among all electricity consumers (Spain, Italy) or
simply by those customers of the utility obliged to buy green electricity
(Germany until 2000), or by the taxpayer, or a combination of both systems
(Denmark). Calling simply on customers of local companies to finance green
power generation is considered unfair and mechanisms are therefore often
adopted to share the burden more equitably (Menanteau, et al., 2003);
Different countries apply different financial support for renewable electricity.
Country-specific cost resource conditions as well as inherent differences in the
support instruments applied, contribute to the different support levels for
renewable electricity. Support may also include secondary instruments with a
considerable direct impact (in particular investment incentives and soft loans)
or an indirect impact. It is often claimed that the high level of feed-in tariffs is
the main driver for investments in wind energy especially in Spain and
Germany. However, the tariff level is not particularly high in these two
countries compared with other countries in Europe. In fact, a long-term and
stable policy environment has been shown to be actually the key criterion for
the success of developing renewable electricity markets (Held et al., 2006).
Furthermore, administrative barriers have been shown to be important. In
France, even under a stable policy environment combined with reasonably high
feed-in tariffs for wind power, high administrative barriers appear to have
significantly hampered the development of wind energy. Furthermore, progress
was much slower in new Member States than in EU-15 countries.
Renewable energy producers ask for higher feed-in tariff levels. The European
PV Association explains that whilst many countries in Europe have introduced
a FiT on different levels, only some of them (e.g. Germany) have adopted
appropriate rates specifically for PV. They say that others used inadequate FiT
parameters (for instance Austria – too low a ceiling on total installed PV
capacity) and thus failed to stimulate significant investor interest.
Meanwhile, Policy-makers should be aware that while feed-in tariffs with an
appropriate level of support is key, there are other important ways to create a
63

stable environment for investors including the reduction of administrative
barriers which will be discussed next.
4.5 Regulatory issues studied
According to the European Commission, “It is impossible to isolate the
discussions on the support schemes from the issue of barriers, as barriers can
increase the cost of renewable electricity or can inhibit the deployment
completely. Barriers that project developers and investors encounter when
installing new capacities can be of administrative, grid, social and financial
nature.”
The Commission points out Administrative barriers can unnecessarily hamper
the planning process, e.g. when:
! A high number of authorities are involved in the planning process and
there is a lack of coordination between them.
! Long lead times to obtain necessary permits exist.
! Potential sites for renewable electricity production are insufficiently
taken into account in spatial planning.
The Commission also highlights that priority access to the grid at a reasonable
and transparent price is essential to the development of renewable electricity
generation, but is not provided for in many Member States. 32 Furthermore,
“renewable electricity generation is normally not situated in the same places as
conventional electricity production and has, in general, a different scale of
generation. Thus renewable electricity production can be confronted with a lack
of sufficient grid capacity. This barrier is worsened by the lack of transparent
rules for bearing and sharing of various grid investment costs, as well as the
existence of vertical integration and dominant utilities.” Finally, the European
Commission points out that transparent rules for bearing and sharing of costs of
various grid investments have been put in place in Denmark, Finland, Germany
and the Netherlands.
32 Furthermore they note that grid infrastructure was mainly built when the electricity sector was
publicly owned and has been designed to allow large power plants being situated near mines and rivers,
or near the main centres of consumption.
64

Figure 16: Estimation of administrative barriers in the renewable energy
deployment in the EU$$
Source: European Commission, 2005.
This thesis focuses on the following three regulatory issues that could be
perceived as potential barriers to renewable energy deployment if not adjusted
to suit the needs of renewable electricity production, in particular:
! Grid access (access to the grid; as explained above)
! Siting policies for renewable energy projects - Public opposition to new
energy projects is perhaps the most well known constraint on siting
processes. However, regulatory hurdles remain a costly, time-
consuming, and unpredictable part of the problem. In many U.S. states,
regulation is fragmented across multiple agencies, permitting and
licensing processes are not standardized, and there is little in the way of
established or timely review at the national, state, or local levels
(Vajjhala, 2006) 33 .
! Net metering regulations - a state level electricity policy for consumers
who own "qualifying facilities," which are generally smaller, renewable
energy sources such as a wind or solar power. "Net", in this context, is
used in the sense of meaning "what remains after deductions" -- in this
case, the deduction of any energy outflows from metered energy inflows.
Under “net metering”, a system owner receives retail credit for at least a
portion of the electricity they generate (Wikipedia, 2007). Net metering
laws exist in at least 7 countries, 35 U.S. states, and several Canadian
provinces 34 . Net metering has been particularly instrumental in
33 Kahn (2006) describes, “Fossil-fuel power plant sponsors enjoy an important siting advantage over
renewables: they can, within certain parameters, select the government agency that will approve or
deny their projects. Renewable energy cannot.” Conventional power plant developers can avoid
specific agencies or review requirements by selecting project sizes and locations strategically. In
contrast, renewable energy developers have fewer alternatives. See:
http://www.rff.org/documents/RFF-DP-06-34.pdf
34 A)3+$,(("%")',0$Z;J;$#%,%&#$!,($)'&$)+$*)+&$&0&/%+"/$3%"0"%"&#$)==&+"'5$'&%$*&%&+"'5;$

facilitating grid-connected solar PV markets in the United States and
Japan (REN21, 2005).$
Current energy legislation on planning, certification and grid access has been
built around the existence of large centralized power plants, including extensive
licensing requirements and specifications for access to the grid. This favours
existing large-scale electricity production and represents a significant market
barrier to renewable energy technologies. Furthermore, it does not recognize
the value of not having to transport decentralized power generation over long
distances (EWEA/Greenpeace, 2005). The EWEA/Greenpeace report explains
that distortions in the conventional power market include, for example:
institutional and legal barriers; existence of regional and national dominant
players; potential for abuse of dominant positions; barriers to third party access;
limited interconnection between regional and national markets; discriminatory
tariffs, no effective unbundling of production and transmission
(EWEA/Greenpeace, 2005). Therefore, they call for changes to be made to
redesign the grid infrastructure, system management, grid regulation and grid
codes that reflect the characteristics of renewable energy technologies 35 .
Finally, other regulatory measures such as building codes 36 and other types of
administrative rules and procedures also serve important roles in promoting
renewable power generation. Different renewable energy technology
stakeholders will have different views about what exact reforms in the
electricity sector which are required to support renewables 37 . While this thesis
+&530,+046$1"%!$#"7$'&1$Z;J;$#%,%&#$.,##"'5$#3/!$0,1#$"'$DSS];$R)#%$+&/&'%046$,$DSS^$Z;J;$=&(&+,0$
0,1$+&23"+&#$,00$Z;J;$&0&/%+"/$3%"0"%"&#$%)$.+)-"(&$'&%$*&%&+"'5$1"%!"'$%!+&&$4&,+#$9_Y\DC6$DSS^:;
35 Cross-border electricity inter-connectors are also important for markets which are not
geographically isolated, according to EWEA/Greenpeace (2005).
36 While building codes are important to solar PV in particular, this type of measure is not considered
in detail in this thesis. Meanwhile, more general clean energy regulatory issues like transmission access
and pricing are highlighted in this research.
37 For example, the specific reforms mentioned in the EWEA/Greenpeace report which are needed to
address market barriers to renewable (specifically wind power deployment) include: Streamlined and
uniform planning procedures and permitting systems and integrated least cost network planning;
Access to the grid at fair, transparent prices and removal of discriminatory access and transmission
tariffs; Fair and transparent pricing for power throughout a network, with recognition and remuneration
for the benefits of embedded generation; Unbundling of utilities into separate generation and
distribution companies; The costs of grid infrastructure development and reinforcement must be carried
by the grid management authority rather than individual renewable energy projects; Disclosure of fuel
mix and environmental impact to end users to enable consumers to make an informed choice of power
source.
66

does not explore all the relevant reforms which renewable energy project
developers call for, it explores clean energy private equity investors’
satisfaction level with the following key regulatory issues: siting, grid access,
and net metering regulations. $
4.6 Technology-push policies studied
Sometimes policy analysts forget about the earlier end of the innovation chain
when they focus on policies that stimulate market deployment of existing
technologies or lead to the reduction of cost over time of existing technologies
with higher current costs of production. Nevertheless, as the innovation chain
is dynamic and non-linear, as discussed earlier, it is important to still consider
how innovation policies or such Product/ Technology-Push policies affect the
eventual deployment of innovative clean energy technologies over time. Just
like investment is required for the deployment of technology, continual
innovation is important to the stimulation of investment in this sector. The
investment chain requires a good supply of deals across the entire chain in
order to be sustainable. These policies include R&D spending, grants for
demonstration plants, investment subsidies, tax credits for entrepreneurs and
investors, etc.
Technology-Push policy options considered in this thesis
! Tax breaks for clean energy investors
! Government VC funds
! Government investment in private VC funds
! Investment subsidies for entrepreneurial firms (e.g. to set up
manufacturing facilities)
! Soft support measures (e.g. coaching for entrepreneurs, business plan
competitions)
! Incubators/technoparks
! Tax breaks for entrepreneurial firms
! Government grants or other financial support for pilot and
demonstration plants
! Doubling public R&D spending for private institutions
! Doubling public R&D spending for public institutions (e.g. universities)
! Grants for SMEs or communities to install equipment
67

4.7 General policy attributes
One of the major attributes of any policy (international, market-pull, regulatory,
or technology-push) is the need for increasing legislative stability and the need
for policy to reduce investment risk. The most important aspect is clear policy
signals to the investment community. Some major international investors and
corporations have already expressed to governments that they need climate
(and energy) policies to be “loud, long and legal” 38 (Defra, 2005). Hamilton
and Kenber (2007) reviewed what business/investors are looking for on climate
change, the role of energy policy, etc. From work with renewable energy
financiers in 2004, they found the same right conditions were needed at the
national level: “policy is critical; needs to be ‘Loud, Long and Legal’” for
further scale-up. Loud means big enough to attract capital, make a difference to
the bottom line; long means it reflects the duration of the project; and legal
means legally based targets or incentives – confidence that it isn’t going to
change (Hamilton and Kenber, 2007). The European Commission (2005) points
out that one of the main concerns with national support schemes is any stop-
and-go nature of a system. Any instability in the system creates high
investment risks, normally taking the form of higher costs for consumers. Thus,
the system needs to be regarded as stable and reliable by the market
participants in the long run in order to reduce the perceived risks. Reducing
investment risk and increasing liquidity is an important issue, notably in the
green certificate market. The design of a support mechanism must minimise
unnecessary market risk. Increased liquidity could improve the option of long-
term contracts and will give a clearer market price.
38 The UK government built on the momentum of the G8 Gleneagles Summit by hosting a high-level
conference in London bringing together government with UK and international business
representatives to discuss the risks and opportunities presented by climate change and the response to
it. One of the findings from the sessions at the conference was that climate policies need to be “long,
loud and legal”. Other messages in this context were that government should establish a clearly mapped
out long-term policy framework to create security and confidence for business, both domestically and
internationally with other major emitters; ensure that climate and energy policy is consistent across
government; remove tax and incentive distortions that favor high carbon over low carbon options;
provide early stage support for new carbon technologies to improve their chances of attracting private
sector investment; and use its procurement power to explicitly support low carbon solutions (Defra,
2005).
68

4.8 Assessing policies’ performance
While this section considers only renewable electricity, the same concepts
apply to renewable fuels. The European Commission (2005) points out two
criteria in order to assess the performance of support systems for renewable
electricity: effectiveness and efficiency. Effectiveness is understood as the
capability of a support system to actually deliver renewable electricity. Thereby
the amount of green electricity delivered needs to be assessed against the
realistic potential of the country. When assessing the effectiveness, the effects
of more recent systems are difficult to judge. Notably the experience with green
certificates is more limited than with feed in tariffs. Efficiency of a support
system for the electricity sector is understood as the capability to produce at the
lowest possible cost. As the generation cost for renewable energies show a
wide variation between the different technologies on the one hand and
geographic conditions on the other, the assessment of support systems has been
done per sector. Another interesting criterion that is only assessed for a limited
number of Member States is to compare the investors’ profits and the
effectiveness within a support system. This gives an indication whether the
high effectiveness of a specific support system is primarily based on the high
financial incentives, or whether other aspects have a crucial impact on the
market diffusion in the considered countries (European Commission, 2005).
4.8.1 Performance of support schemes
4.8.1.1 Performance in terms of effectiveness
The European Commission (2005) performed an assessment of the support
systems separately for the different renewable technologies 39 . They concluded
that the most effective systems in wind energy are currently in Germany, Spain
and Denmark with feed-in tariff systems 40 , although the green certificate
39 Other studies exist about the effectiveness of policies, however not all studies could be reviewed in
this introduction to the literature on the topic. Other studies with regard to policy effectiveness will be
discussed in later sections.
40 Countries with feed-in tariffs for wind power (e.g. Germany, Spain, Denmark) have seen the largest
growth of RES electricity. After the Electricity Feed-in Law (EEG) was passed in Germany, installed
capacity of wind energy more than doubled year-on-year during the 1990-95 period. At the same time,
a viable RES–E manufacturing industry was being established in these countries. The adequate FIT
also significantly contributed to surpassing capacity targets. This was the case in both Denmark and
Germany, where targets set for the future were reached years in advance with regard to wind (EPIA,
2005). $
69

systems, where they apply, present currently a significantly higher support
level than the feed-in tariffs. This could be explained by the higher risk
premium requested by investors in case of green certificate systems, the
administrative costs as well as a still immature green certificate market. The
question is how the price level for green certificates will develop at the medium
and long term. The analyses showed that for wind energy, in one fourth of the
Member States, the support is too low for any take off. Another fourth of
countries show enough support but still mediocre results due to the existence of
grid and administrative barriers (European Commission, 2005).
Meanwhile, in the United States, some research tends to indicate that the
Renewable Portfolio Standards have been effective, at least for wind power.
Texas has rapidly emerged as one of the leading wind power markets in the
United States. Wiser, 2001, shows that this development can be largely traced
to a well-designed and carefully implemented renewable portfolio standard
(RPS). The production tax credit has helped as well, but it appears that the
inconsistency in the production tax credit has affected the wind turbine
manufacturing industry, as noted before, resulting in uncertainty for investors.
Currently, a majority of wind turbines used in the United States are imported
from overseas (Cleantech Venture Network, 2006).
The European Commission’s analyses for both the biomass and the biogas
sector are not as clear as in the case of wind. The generation cost of biomass
presents big variations, caused by different biomass sources, different processes
of transformation and different sizes. Denmark with feed-in tariffs and the
Finish hybrid support (de-taxation and investment subsidies) clearly show the
best performance in the biomass sector, both in terms of effectiveness as well
as economic efficiency of support. A long tradition in biomass use for energy
purposes, stable planning conditions and a combination with heat generation
can be considered as key reasons for this development (European Commission,
2005). In the biogas sector six countries present effectiveness that is higher
than the EU average, four of them with feed-in (Denmark, Germany, Greece,
Luxemburg), two of them with green certificates (UK, Italy). But in nearly 70%
70

of the EU countries the support level is too low to develop this high potential
technology (European Commission, 2005).
The European Photovoltaic Industry Association (2005) has outlined why feed-
in tariffs are the most effective system for the promotion of solar PV
technology. They note that the German case is a good example of the FiT effect
on installed PV capacity. Although the “100,000 Rooftop Programme” did
contribute to the enhancement of installed PV capacity, they note, it was the
FiT introduction and later optimisation of its rate that really enabled market
take-off. They write that until 2004 yearly installed PV power increased almost
thirty-fold to 363 MW and system price decreased by more than 20% since
1999. During this period German PV industry created about 10,000 jobs in
production, installation, trade and maintenance of PV systems 41 . They conclude
that competitive bidding systems (e.g. applied in the UK) in contrast are not as
effective in building RES-E capacity. In the past (2001) for instance Germany
boasted over 8000 MW of installed wind power capacity whereas the UK
showed a mere 500MW despite a much more favourable wind regime. They
note that renewable portfolio standards are unlikely to have comparable
impacts on PV deployment (as the FiT scheme) and may even cause unforeseen
negative implications 42 . The EPIA also views the green certificate systems as
not suitable for PV either as the Danish and Swedish cases demonstrate 43 .
As for the United States, both the California Energy Commission (CEC) and
California Public Utilities Commission (PUC) have offered “buy down”
programs that reimburse purchasers of solar systems for up to 50% of their
project cost 44 . Finally, net-metering credits reimburse solar system owners for
41 They also note that since 1999 the majority of investments in solar cell production facilities in
Europe were made in Germany and Spain, the two countries that offer the most stable and realistic
legal framework conditions for citizens investing in a PV system.
42 This arises because an RPS requirement for renewable energy may encourage the lowest direct cost
for renewable energy options, so as to minimize electricity retail price. Without specific targets for PV,
any portfolio standard will stifle growth of PV markets and impede the technology development (EPIA,
2005).
43 In Denmark, a forced transition from the FiT scheme to a green certificate system has led to a
collapse of the Danish wind energy market (acc. to the WWEA6). In 2000, 600 MW of new capacity
were installed based on FiT, whereas during the first half of 2001 new installations dropped to a mere
18 MW, bringing construction of wind power plants to an almost standstill.
44 California also offers a phased Solar Income Tax Credit (15% of the capital investment for the first
two years, 7.5% for the remaining two years) for residential and commercial customers purchasing
onsite PV systems up to 200 KW in size.
71

energy they produce but do not use. Individual municipalities and utilities also
offer substantial rebates to customers installing PV equipment. Also, in January
2006 the California Public Utilities Commission approved the California Solar
Initiative (CSI), committing $2.9 billion over the next ten years to help
homeowners, businesses, farmers, and government install 3000 MW of new
solar capacity on 1 million rooftops in California 45 . By offsetting the capital,
installation, and production costs of PV, wind, and other power systems, Burtis,
et al. (2006) points out that California has helped nurture one of the largest
state-based renewable energy industries in the country, with hundreds of
renewable equipment manufacturers, installers, and servicers now employing
thousands of Californians (Burtis, et al., 2006).
4.8.1.2 Performance in terms of creating domestic industries
Sawin, 2004, summarizes a number of points relevant to this discussion. First,
she says the experiences of countries such as Denmark, Germany, Japan, Spain
and Brazil have demonstrated that the key to steady and significant cost
reductions is the development of consistent and reliable markets. Such
conditions allow for the entry and maturation of small- and medium-scale
enterprises, which have provided the bulk of the technological innovation that
has driven down renewable energy costs. In addition to the “global learning
curve” that exists for technologies such as wind turbines and PV cells, there is a
“national learning curve” as individual countries develop domestic industries
that are able to manufacture, install and maintain renewable energy systems
using local equipment and labor. Those countries that do not yet have sizeable
industries in place can expect dramatic price reductions in the first few years
after effective new policies are introduced. Finally, Sawin concludes by saying,
to date, feed-in—or pricing—systems have been responsible for most of the
additions in renewable electricity capacity and generation, while driving down
costs through technology advancement and economies of scale, and developing
domestic industries.
45 It is estimated that the initiative will help dramatically lower the cost of solar cells and create 15,000
jobs over the coming decade (Burtis, et al., 2006).
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4.8.1.3 Effectiveness and economic efficiency
The Federal Environment Agency (2006) studied both the effectiveness and
economic efficiency of a number of policies (for the area of wind energy) in
their 2006 report for selected EU Member States. This is done using empirical
investigations as well as model-based scenario calculations. Effectiveness is
defined by the ratio of the additional annual normalised electricity generation
and the realizable remaining potential until 2020. Figure 17 shows the onshore
wind effectiveness indicator for the year 2004. Firstly, the three Member States
Spain, Germany and Ireland showed the highest effectiveness in 2004. In
contrast, the four countries using a quota obligation - Belgium, Italy, Sweden
and the UK - only achieved moderate effectiveness 46 .
Figure 17: Effectiveness indicator for the market development of onshore wind
for selected EU-member states in 2004 47
Source: FEA, 2006.
The feed-in tariffs turn out to be generally lower than the sum of certificate
price and electricity price in those countries applying quota systems.
46 In 2004, the Irish tender system reached a higher level of effectiveness than in former years because
of the exceptionally ambitious targets set in the last bidding round in 2003.
47 Effectiveness is defined by the ratio of the additional annual normalised electricity generation and
the realisable remaining potential until 2020 (diagonal shading for Belgium indicates that the Belgian
quota system is combined with a minimum tariff) (FEA, 2006).
73

Figure 18: Comparison of support for onshore wind power for selected EU
Member States in 2004
Source: FEA, 2006.
Since the tariff level disregards important characteristics of the support policies
such as the duration of payment, relevant additional support measures and
country-specific resource availability, the annual payments presented in Figure
18 are then translated into a quantity that takes these characteristics into
account. Figure 19 below shows the support level adjusted by the factors
mentioned 48 . The FEA attests that the normalised support level is an adequate
indicator of the economic efficiency of the support scheme. The message is that
the support level of countries with feed-in systems is typically lower than those
with quota systems.
48 The duration of support is accounted for by calculating the annuity of the support level based on a
uniform interest rate of 6.6% and 15 years. Resource availability is accounted for by normalising the
support level to a uniform number of 2000 full-load hours per year. The certificate price is assumed to
remain constant within this calculation.
74

Figure 19: Normalized level of support for onshore wind in selected EU
Member States in 2004 49
Source: FEA, 2006.
Figure 20: Effectiveness indicator in relation to the annual expected profit for
onshore wind in 2004
Source: FEA, 2006.
49 The data presented is scaled for the country-specific duration of support, additional support
measures and country-specific resource conditions are considered. Diagonal shading for Belgium
indicates that the Belgian quota system is combined with a minimum tariff (FEA, 2006).
75

The study concludes that it is striking that three countries - Italy, the UK and
Belgium - which have recently transformed their markets into quota systems as
the main support instrument, have a high expected annuity of support 50 but low
growth rates. Based on the assumption of constant certificate prices, which is
mainly justified by empirical observations 51 , the results show that certificate
systems can lead to high producer profits resulting from high investment
risks 52 . They note that on the other hand, it seems typical for countries with
feed-in tariffs to be more effective at generally moderate levels of support 53 . As
a general conclusion, the report states that the feed-in systems examined are
effective at relatively low producer profits. On the other hand, it can also be
observed that the present quota systems only achieve rather low effectiveness at
comparably high profit margins. However, they emphasize that these quota
systems are relatively new instruments in the countries currently applying
them. Therefore the behaviour observed might still be marked by significant
transient effects (FEA, 2006).
4.8.2 What does existing empirical work tell us?
4.8.2.1 Wind energy and policy
As described earlier, the European Commission, in its assessment of various
policies to promote renewable energy deployment, concluded that fixed feed-in
tariffs were the most effective policy options. Taking a simple example, the
example of wind energy, we see that Denmark, Germany, and Spain are the
world leaders in wind turbine production. This appears to correlate with the fact
that these countries also are the leaders with regard to feed-in tariffs in Europe.
50
The high annuity results in particular from the extrapolation of the presently observed certificate
prices.
51
They report that so far there is no clear trend of decreasing certificate prices under the different
quota systems in the EU. Such a decrease should be expected only if the risk level on existing
certificate markets falls significantly (FEA, 2006).
52
It should be stated here that if long-term contracts are negotiated by the RES producer and the
obliged party, e.g. a utility, only a certain fraction of the 'producer profit' will actually be earned by the
RES producer.
53
An exception to this rule is France, where administrative barriers are preventing the rapid
development of wind energy. Spain had the highest growth rates in terms of the effectiveness indicator
offering an adequate profit. Profits are expected to be higher in Spain than in the other feed-in countries
not because of a high support level, but because of relatively low electricity generation costs due to
good resource conditions on the one hand and low investment costs on the other hand (FEA, 2006).
76

Fixed feed-in tariffs 54 are used in Denmark, Germany, Spain and Italy. It is the
oldest and most widely used support system to stimulate the diffusion of
renewable energies, besides RD&D and investment subsidies. Butler and
Neuhoff, 2004 explain, “In terms of absolute capacity, and capacity compared
to stated target, the German feed in tariff has been more successful than the
NFFO. The introduction of the ROC has yet to generate substantial increases in
capacity, with only 60MW of wind capacity being installed in England and
Wales since introduction. Sawin (2004) concludes that ‘feed-in systems have
been responsible for most of the additions in renewable capacity and generation
whilst the record of quota systems is more uneven. Lauber, 2004, and
Menanteau, et al. 2003, also conclude that feed-in systems have been more
effective in terms of achieving targeted capacity 55 .
Most of the growth experienced in the sector appears to be a result of the first
German feed-in system. Mitchell, et al., 2006 write that Germany has seen an
impressive growth of electricity generation from renewables during the 1990s
and this success is to a large extent due to a feed- in mechanism laid down in
the first German feed-in system, introduced in 1991 (Stromeinspeisegesetz).
This was a feed-in system based on the ‘‘market price’’ topped-up by a
premium payment 56 .
54 The guaranteed feed-in tariff scheme involves an obligation on the part of electric utilities to
purchase the electricity produced by renewable energy providers in their service area at a tariff
determined by the public authorities and guaranteed for a specified period of time (generally about 15
years).
55 However, Butler and Neuhoff consider other factors which may be significant to the reason why the
development under the NFFO was well below expected levels. One hampering factor observed in an
investor survey by LEK Consulting (2003) suggested the costs involved in connection and
reinforcement can be prohibitive in the UK and such difficulties with connection seem to have
increased over time.
56 In such a system, the feed-in tariff would vary according to the general electricity tariff, exposing the
generator to the development of these tariffs. The authors explain that as long as there was a
monopolistic market, this was not a problem because prices were both high and relatively stable. As
electricity prices went down after the market had been liberalized in 1998, prices paid to renewable
generators fell and many came under pressure.
77

Figure 21: Installed Capacity in Germany and the UK (1990 - 2003)
Source: Butler and Neuhoff, 2004.
Meanwhile, Butler and Neuhoff (2004) explain that the feed in tariff has been
criticized for being unduly expensive, with the price of wind energy falling
only 18% between 1990 and 1999 compared to a decline of 67% in contracted
prices in the UK. However, they explain that this change in relative prices has
been achieved despite a more favorable wind resource in the UK. 57
4.8.2.2 Solar energy and policy
Grid-connected solar PV has been one of the fastest growing clean energy
sectors (along with biofuels more recently) at a 60% average annual growth
rate during the five-year period between 2000 and the end of 2004 (see Figure
22), according to REN21. Sarasin bank analyst Mattias Fawer predicts that
electricity from photovoltaics will be one of the fastest growing energies in the
next decades. The current global volume of the PV-market is approximately
9bn Euros – and in 2020 it could be around 50bn Euros (Fawer, 2006).
57 Dale et al (2004) quote a typical wind speed of 8.3 m/s in the UK, which compares to a wind speed
of 5.5 m/s at the reference location in Germany. Moreover, evidence from developers suggests that
over the latter half of the 1990s sites with a lower wind resource have been developed.
78

Figure 22: Existing World Capacity for Solar PV, total and grid-connected only
Source: REN21, 2005.
Since 2006, grid connected solar PV installations are concentrated in three
countries: Germany (55%), Japan (17%), and the United States (8%), and are
driven by supportive policies. The rest of the Europe has 11% of PV
installations and the rest of the world has 9% of PV installations (Marketbuzz,
2007).
The concentrating solar thermal power market has remained stagnant since the
early 1990s, when 350 MW was constructed in California due to favourable tax
credits. However, commercial plans in Israel, Spain and the United States have
led to the resurgence of interest in recent years. Solar hot water/heating
technologies are becoming more widespread in countries like China, Israel,
Turkey and Japan, as well as European countries. China accounts for 60
percent of the total installed capacity worldwide (REN21, 2005).
As for solar PV markets, there has been remarkable growth in 2005 despite a
solar silicon bottleneck. In 2005 worldwide solar cell production grew from
1’230 to 1’740 MW by 41%. Since beginning of 2005 solar stocks have soared.
PPVX-Index 58 increased by 150% between 1.Jan 2005 and 31. Dec 2005
(Fawer, 2006). Many (smaller) companies took advantage of the positive
market environment for capital increase or an IPO. Investors seemed to make
no differentiation and were willing to pay any price for solar shares around this
time.
58 PPVX-Index stands for the Photon Photovoltaic Stock Index (see: http://www.photon-
magazine.com/ppvx/index.htm)
79

Figure 23: Solar PV stocks soared from beginning of 2005
Source: Fawer, 2006.
Fawer (2006), reports that prices of solar modules have significantly decreased.
According to him, competitive prices will be reached within the next 10-15
years. This will be at a generation cost of approximately 0.20 euro/kWh (at the
moment cost for PV-power are around 0.30-0.50 euro/kWh (Fawer, 2006).
Figure 24: Prices of solar modules and newly installed capacity (Germany)
Source: Fawer, 2006.
80

However, volatility in the market was apparent in 2006. Until May 2006, the
PPVX-Index grew another 50%, however over the whole year it lost 7%.
Figure 25: Share prices then slumped in 2006
Source: Öko-Invest; from Fawer, 2006.
Fawer (2006) proposes that the reason for the increase in early 2006 was the
California PV programme, a high oil price, and still much of a positive
sentiment for solar energy. He also proposes that it came down in the later half
of 2006 because of declining demand for PV-systems in Germany, growing
price pressure, and uncertainty about the feed-in tariff (the EEG law in
Germany) from 2007 onwards. As for the price pressure and the stagnation in
the German Market, he notes the clear slowdown in the quarterly results of
smaller German players (e.g. Aleo, SAG Solarstrom, Sunways, Phoenix
Sonnenstrom, Reinecke & Pohl…) but also the brilliant figures from
internationally active upstream companies (e.g. SolarWorld, Q-Cells, REC).
Now solar energy is no more a self-runner, but investors must investigate the
business model of solar companies in more detail. A number of factors that
may determine the future success of PV-companies were noted by Fawer
(2006). They are: 1) growth despite a solar silicon bottleneck, 2) critical size of
the company, 3) establish a clear business model and build-up unique know-
how, and, 4) international customer basis. Fawer notes that growth markets of
the future are Southern Europe, Asia and North America; a home market
(especially for German companies) is not enough. This case points to the fact
81

that an inflexible business model in a policy-driven market can be the main
source of regulatory risk. If investors are aware of the need to expand outside
of initially favourable markets (due to policy), then they will be able to find
appropriate ways to mitigate risks related to a company potentially becoming
too dependent on a given policy environment.
4.9 Concluding remarks on policies
While this research appears to lend itself to a comparison of policies as if the
best policy should win over others, in fact it does not advocate the application
of one best policy. It must be emphasized that a mix of instruments is essential.
Furthermore, an apparent ‘winning’ policy or set of policies might not fit every
country’s situation.
Governments can use a number of options to promote clean energy
technologies. Voluntary measures are also an option, but they have had limited
effects and the results can vary. For example, Bird, et al. (2002) studied green
power marketing activities worldwide and concluded that the impact of green
power marketing on new renewables development has been limited so far. 59
They also found that while price is not the only important driver of demand,
companies offering lower-priced products generally obtained more customers.
Meanwhile, even regulatory instruments like carbon trading (if applied alone)
can not be expected to stimulate much investment in renewable energy (RES)
or end-use energy efficiency (EUEE), at least not as they have been applied so
far. “E,+8)'$%+,("'5$"'$"%#&0=$,#$/3++&'%04$,..0"&($"'$YZ$Y?J$"#$3'0">&04$%)$#%"*30,%&$
"'-&#%*&'%#$ "'$ _YJ$ )+$ YZYY$ .+)`&/%#6$ 3'0&##$ %,+5&%#$ ,+&$ #&%$ *)+&$ ,*8"%")3#04$
/,3#"'5$%!&$.+"/&$)=$/,+8)'$%)$+"#&6$,'($%!&$=0,1#$)3%0"'&($,8)-&$,+&$,((+&##&(;$F'$
%!&$ )'&$ !,'($ prices!are!not$ expected!to!increase!sufficiently!to!foster!takeoff!of!RES!
projectsU$ )'$ %!&$ )%!&+$ !,'($ solely!price$ increases!cannot!be!relied!on!to!foster!EUEE!
project!deployment”$9Bertoldi, et al., 2005).$ Other instruments such as standards,
taxes, tax credits, fixed tariffs, etc. are important to make renewable energy
59 Bird, et al. (2002), found that much of the green power sold in competitive electricity markets (in
2002) had been supplied from existing renewable resources. However, Wuestenhagen and Bilharz
(2006) found the contribution to be higher in Germany more recently. Bird, et al. (2002) also found that
requirements for new generation instituted by certification organizations and labeling programs played
an important role in shaping products and stimulating capacity additions.
82

prices more competitive, increase demand and supply, and stimulate learning
effects.
It is also important to note that there are different interaction effects between
public policies which have been found to be an effective driver for renewable
electricity generation, and voluntary measures like green power marketing 60 .
For example, Bird, et al. (2002) found that tax exemptions and credits for green
power purchases and government procurement were successful at stimulating
supply and demand for green power.
Wuestenhagen and Bilharz (2006) conclude from their study that Germany has
been very successful in increasing the share of renewable electricity over the
past decade, and this has largely been achieved by effective public policy. The
also found that within the public policy mix, the feed-in system was most
significant. Sawin (2004), also points out that a mix of instruments is essential
and a key to success and that the combination of policies needed depends on
the costs of the technology used, location and conditions. In this line of thought,
Wuestenhagen and Bilharz (2006), conclude in their paper that the German
model has been brought about by a strong central government and a political
culture that is open to government intervention, meanwhile a quota system or
RPS scheme may have a better cultural fit in a cultural environment that puts
higher emphasis on (shorter term) economic efficiency and trading.
The mix of policies relevant to a country is also dependent on the specific goals
of the country with relation to renewable energy. To demonstrate an example in
which a mix of policies was the best approach to meet an economic goal (not
just increased capacity), one can point out the work of Lewis and Wiser (2005),
which showed that policies that support a sizable, stable market for wind power,
in conjunction with policies that specifically provide incentives for wind power
60 For example, Wuestenhagen and Bilharz (2006), explain that a key driver for the emergence of the
green power market is the desire of marketers to establish product differentiation and despite the
greater success of public policy to stimulate the market, if there continues to be a liberalized retail
electricity market in Europe, this desire is not going to go away. The authors conclude, “Hence not
influencing power marketing strategies might be a missed opportunity for renewable energy
stakeholders to leverage private marketing Euros for the public good, i.e. to educate consumers about
the benefits of renewables.
83

technology to be manufactured locally, are most likely to result in the
establishment of an internationally competitive wind industry.
Looking more globally at the various possible approaches, there are five major
categories of relevant options that can be combined to increase renewable
electricity generation, as defined by Sawin (2004):
! Regulations that govern capacity access to the market/electric grid and
production or purchase obligations
! Financial incentives
! Industry standards, permitting and building codes
! Education and information dissemination
! Stakeholder involvement
Still, there is a healthy debate in the literature about which types of policies are
most effective. Wuestenhagen and Bilharz (2006) point out that it now became
clear that the feed-in system was effective at getting the renewable energy
market started in the 1990s, and other work has pointed to the effectiveness of
the feed-in tariff system. Comparisons between different schemes have led to
the most often debated topic about whether price-based mechanisms are better
than quantity-based mechanisms. An example is Mitchell, et al. (2006) that
argues that the German EEG (feed-in system) is more effective at increasing
the share of renewables than the England and Wales Renewables Obligation
because it reduces risk for RES generators more effectively.
However, Midttun and Gautesen (2006) also maintain that rather than
continuing a debate for or against given policy instruments, a more useful focus
would be on how technologies may be phased through either of these support
instruments on their way to the mainstream energy market. Furthermore, in
order to ensure good market conditions for a portfolio of technologies, a
diversity of policies is needed, as each policy is better adapted to the risk
profile of each technology investment. Then again, if a country has a specific
vision of the future that it would like to move toward, a tailored set of policies
that may exclude certain policies, would be best. For example, Jacobsson and
Johnson (2000) explain that if a future energy system is to be built on
renewable energy sources, it will probably contain a varied set of technologies,
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presumably including various types of applications of bio energy, solar
collectors, photovoltaic cells and wind power. It is also probable that these
smaller-scale, more decentralized technologies will be exploited by a larger
number of actors than in the case of nuclear power, coal and hydropower
technologies. Therefore, if policies are intended to stimulate investments and
activities by a larger number of actors for the creation of a more decentralized
energy system, than they should also be designed so that this larger number of
actors can directly access the benefits created by these policies. Feed-in tariffs
are again a good solution in this case, as compared to the more complex and
indirect CO2 emissions trading scheme.
To conclude, the choice of a set of policies used to stimulate change in a given
country is dependent on the vision of the future that the country aims to move
towards. The feed-in tariff appears to be the best tool to reduce risks faced by
investors and stimulate investments in new and innovative technologies. If
greater investment in smaller sized firms is also a goal, than this is obviously
the best policy choice. Butler and Neuhoff, 2004, studied the initial experience
with the ROC scheme, and also confirm Sawin’s observation that a quota-based
system such as the ROC is not inherently cheaper than a feed in tariff. Of
course, the evaluation of any given policy depends on what the country views
as important evaluation criteria. This work is now contributing to the area by
uncovering the investment impacts of various policies, particularly for the ever
growing venture capital and private equity investment sector.
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5 Research approach and methodology
5.1 Research questions
The basic research questions of this thesis are as follows:
1. Do private equity investors view certain policies as clearly contributing
to their interest to invest in the sector?
2. How do private equity investors rate the attractiveness of market-pull
policies and technology-push policies?
3. Which policies do certain types of investors appear to prefer most, and
what may be some rational explanations for their differences in opinion?
4. What are the basic characteristics of clean energy VC/PE fund managers,
and how do they relate to their policy preferences and regulatory risk
management approaches?
5. How does perceived regulatory risk influence the decision-making of
private equity investors with regard to clean energy ventures and how do
private equity fund managers currently manage regulatory risks relevant
to their clean energy technology deals?
In this work policy was examined in terms of how it is relevant to increasing
private equity investment levels in clean energy technology ventures. For this
purpose, perceptions of fund managers with regard to policies were used as an
indicator. Understanding that policies affect different parts of the investment
cycle and the innovation chain, one can assume that investors will have
different views about policies depending on which stages of the cycle and chain
are relevant to them. Therefore, fund characteristics like stage of investment,
fund type, firm type, and others should be important to influencing their views.
Furthermore, various types of stakeholders and information sources, such as the
type of core investors that invest in their funds, are likely to influence their
decisions. Therefore, core investors, information sources, and the entrepreneurs
they invest in are likely to influence and contribute to the building of their
views, as well. Finally, investment team backgrounds and experience in the
sector are likely to be influential in terms of personal knowledge and
perspectives as well as group knowledge and mindset. Also of relevance are a
number of other fund characteristics such as: 1) how much funding they now
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dedicate to clean energy compared to total VC or PE funding, 2) and where
they are located and where they tend to invest, 3) management characteristics
(extent of hands-on approach with portfolio companies vs. political activity,
etc.), as well as 4) their perspectives on key drivers and hindering factors.
These factors may also affect to a different extent their choice of regulatory risk
management approach.
The focus of this thesis research is on specifically clean energy technologies
defined as technologies that utilize renewable energy sources, or are advanced
energy technologies contributing to distributed energy systems or increased
energy efficiency (on the demand or supply side). In particular the technology
categories within this definition are: PV (solar photovoltaic), solar thermal,
wind power, geothermal, marine, biomass for power, biofuels for transport,
stationary fuel cells, fuel cells (for transport), energy storage, and hydrogen
from renewable 61 .
There may be feedbacks between influential forces (firm characteristics, fund
characteristics, core investor expectations, and information sources) as well as
between the process of developing appropriate risk management approaches
and the process of developing an opinion about the opportunities and risks that
different public policies offer to investors. Therefore, it is proposed that this is
not a linear process but a dynamic process (changing over time) and a complex
process. Furthermore, while this thesis has not investigated individual mind-
sets among a given firm, it should be noted that firm specific biases (biases or
opinions among important team members, or the status-quo bias of the firm
perceived by fund managers) about policy and doing business in a policy-
driven market may also influence fund managers’ investment decisions in the
clean energy sector, as well as their choice of regulatory risk management
strategy 62 .
61 Fund managers were also asked to provide information on how many deals they finance of each type.
The deal-type which was most often financed among the sample was solar PV, which fits the growth
trends in solar PV seen earlier in the literature review.
62 Recalling that VC investment decisions are governed by intuition more than reasoning (Kahneman
2003) and are characterized by a number of cognitive biases (McFadden 2001) such as anchoring-andadjustment,
availability and status quo-biases (Samuelson and Zeckhauser 1988), leading to
conservatism in adjusting to new information (Tversky and Kahneman 1974, Kahneman 2003).
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For example, firms that do not believe a deal should ever rely on policy might
proceed with a pre-screening process or an in-depth due diligence process to
weed out any deals which would be considered too dependent on a policy-
driven market. Other investors might accept that the entire clean energy market
is policy-driven and that a diversity of supportive policies and regulatory
frameworks reduces the risk that a given venture in the sector will fail. Risk
management approaches are likely to result from various “views of the world”.
Overall firm investment strategy may also influence both regulatory risk
management practices and policy perceptions.
5.2 Research approach
As shown in Figure 26, the analysis started by exploring the fund’s various
basic characteristics. It then moved on to explore its management practices,
information sources and skills, and to examine more general perceptions about
the sector (e.g. drivers and hindering factors). Then the funds’ policy
preferences were examined, on average. A more detailed analysis of policy
preferences was performed using the data collected in the first three parts of the
research process shown in Figure 26. Finally, regulatory risk management
approaches among different types of funds were analyzed in a similar way.
However, regulatory risk management approaches were studied with more of a
qualitative analysis. Study participants who answered the on-line survey and
participated in interviews were asked how they manage regulatory risks
relevant to their clean energy VC/PE investments. The answers were grouped
according to similarities in responses. The apparent groups were then analyzed
using the results from earlier steps in the research process (e.g. basic fund
characteristics and policy perceptions).
Indeed, fund characteristics, management practices and skills, as well as
general perceptions of funds regarding the clean energy market (and their
technology investment preferences) were found to be related to the funds’
policy perceptions and choice of risk management practices in the final analysis.
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Fund’s
Fund’s
Risk
Risk
Management
Management
Fund’s Fund’s
Policy Policy Preferences
Preferences
Fund’s
Fund’s
Views
Views
& &
Preferences
Preferences
Re:
Re:
Clean
Clean
Energy
Energy
Fund’s Fund’s Management Management & & Skills Skills
Fund’s
Fund’s
Basic
Basic
Characteristics
Characteristics
Figure 26: Research process for this thesis
In the first three steps shown above called “Fund’s Basic Characteristics,
Fund’s Management & Skills, and Fund’s Views & Preferences Re: Clean
Energy” the various fund characteristics, perceptions and expectations of
investors were also examined to see if the sample studied was well-balanced,
and to better understand and characterize the players in this market using the
data collected. While these are independent results of the study by themselves,
this data was used primarily to study why differences may exist in funds’
policy preferences and regulatory risk management approaches.
Finally, the knowledge collected has been compared to the knowledge available
in the literature review to develop propositions about the effectiveness of
policies in stimulating private equity investment interest in clean energy
technologies, in particular less mature technologies. The findings are also used
to analyze why there are major differences of opinion as well as differences in
risk management practices.
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While the approach taken in this research highlights what factors may lead to
differences in view and practices among fund managers, this work also aimed
to determine from the average data collected among the entire sample if there
were general preferences among the clean energy fund managers with regard to
policies. These findings can be most easily referred to in order to develop
guidance for Policy-makers, assuming that Policy-makers should be interested
in stimulating the interest of all the players in the venture capital and private
equity fund management space.
The following aspects were therefore investigated:
! Major perceived hindering factors for further clean energy VC/PE
investment (in particular, how perceived lack of consistent government
policy compares to other perceived hindering factors)
! Preference for non-market-based mechanisms vs. market-based
mechanisms
! Preference for price-based mechanisms vs. non-price-based mechanisms
! Preference for market-pull policies vs. technology-push policies
! Preferences among technology-push policies, R&D policies vs. grants or
fiscal measures to stimulate innovation and investment
! Preferences among market-pull policies, strategic deployment policies
vs. market barrier reduction policies
! Preferences among international policies, an R&D approach vs. a sector-
specific approach vs. an economy-wide market-based instrument
approach
! How important regulatory issues are (or how satisfied or not investors
are with the handling of regulatory issues relevant to clean energy today)
! More general findings such as which characteristics of policies fund
managers’ tended to mention in their interviews as important to them
(e.g. long-term, uniformity across countries, stringency, etc.)
! Differences between North American and European markets and policy
environments
Figure 27 and Figure 28 show the general model used in the empirical data
analysis of this thesis research. It includes: 1) fund characteristics, 2)
management practices/skills, and 3) clean energy market views and preferences
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which were viewed as potentially being independent variables that could
impact (more or less) the dependant variables – a) continued clean energy deal
investment (in particularly companies offering less mature or the most
innovative clean energy technologies), and b) regulatory risk management
approaches regarding funds’ clean energy investments.
Basic Characteristics Clean Energy Policy Views
Management & Skills
Clean Energy Views
How policy impacts
Funds’ investment decisions
- Primarily the decision to invest or not in
a company offering innovative clean
energy technology
feedback
Figure 27: Relationship between fund characteristics and investment decisions:
Step 1 of the basic research approach
Basic Characteristics
Management & Skills
Clean Energy Views
Regulatory Risk Management
Approach or Strategy
feedback
Figure 28: Relationship between the variables and the fund’s regulatory risk
management approach - Step 2 of the basic research approach
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Basic Characteristics
Management & Skills
Clean Energy Views
Regulatory Risk Management
Approach or Strategy
Interaction?
Views on investment stimulation
Effectiveness of clean energy policies
Figure 29: Potential interaction between policy and regulatory risk
management – Step 3 of the basic research approach
The last step in the process is to reflect on what the findings in the first two
steps imply with regard to how they relate to one another (Figure 29). It is
proposed that: 1) regulatory risk management approaches will influence how
much a fund knows about policies relevant to the sector, thereby influencing
their views on policies, 2) funds’ preconceptions about policies, as well as
experience related to policy, will influence their regulatory risk management
decisions, as well as the general investment decisions of funds, and 3) the
importance of policy and the level of activity that the fund is likely to pursue to
manage regulatory risks will depend on basic fund characteristics such as their
commitment and level of interest with regard to clean energy finance.
5.3 Research process and methodology
5.3.1 Data collection and participants
After an initial period of informal data collection via 1) participation at major
clean energy investment industry conferences (informal interviews, contact
making, and collection of presentations) and 2) a few years of fieldwork
experience with regard to policy-making, the following empirically based
research process and methodology was designed. On-line and written surveys
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as well as in-person and telephone interviews with venture capital and private
equity fund managers (one representative per fund) were conducted as the basis
of the empirical research which focused on clean energy fund manager
perceptions and management practices. Questions for the structured interview
and on-line survey (see Annex 1) were designed after re-iterative tests with a
select group of fund managers over the spring and summer of 2006. A few
supplementary interviews were also held with other stakeholders such as major
active institutional investors and highly knowledgeable consultants in the field,
in order to better design the structured interview/survey.
The first objective in the search for study participants was to obtain a fully
representative sample of the sector (e.g. different stages of VC and PE finance
for clean energy), the second objective was to obtain as many fund managers as
possible to increase the size of the sample, and the third objective was to
maintain a balance between different types of players in the sector (e.g.
between European and U.S. investors), so that the results would not be biased
in any way, but rather represent the large variety of globally-located fund
managers in (or planning to enter) the clean energy VC/PE finance space.
However, there were limited opportunities to reach out to fund managers
located in Asia, Australia, New Zealand, Latin America and Africa. As a result,
the sample was finally composed of funds primarily active in the United States
and/or Europe. They are mostly already active in the clean energy sector, with a
few exceptions (20% of the total had not already invested in the clean energy
field). In any case, North America and Europe are still the dominant clean
energy markets at this time, while it is recognized, of course, that the market in
China 63 is quickly growing as well.
Sixty fund managers took part in the survey, of which 80% had already
invested in a clean energy deal. Out of the 60 fund managers, about 1/3
completed the web-based questionnaire, another 1/3 returned the shorter paper-
and-pencil version and another 1/3 responded either face-to-face or via
telephone. Again, in all cases the respondents were assured of 100%
confidentiality.
63 Future work in this area would therefore do well by looking more specifically at funds active in the
Chinese market.
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Participating investors in the study are shown below in table 4.
Table 4: Participating investors in the study
@Ventures Danfoss Ventures
3i plc DFJ Energy Ventures
AB Chalmersinvest DTE Energy Ventures
Advanced Technology
Ventures
Amadeus Capital
EDF (France)
Emerald Technology
Ventures
RockPort Capital
Partners
SEED Capital
Denmark
Siemens Venture
Capital
Sierra Venture
Capital
Sierra Ventures
Apax Emertec Gestion Signal Hill
Ardour Capital
Environmental
Technologies Fund
SJF Ventures
Aretê Corporation EPS Value Plus AG Starfish Ventures
Argentum
Fondsinvesteringer
Axiom Venture Capital
BankInvest New Energy
Solutions
Foursome Investments
GE Energy Financial
Services
GLE London Seed
Capital
The Black Emerald
Group
The Carbon Trust
TRF’s Sustainable
Development Fund
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Braemar Energy Ventures Good Energies, Inc. UBS Pactual Bank
Calvert Group Heiko Ott US Global, LLC
Chesapeake Strategic
Partners, LLC
Climate Change Capital
Private Equity Fund
CMEA Ventures, Fund VI
Conduit Ventures
Credit Suisse, Masdar
Cleantech Fund
CVC Sustainable
Investments, Ltd.
Jane Capital VentureInvest AG
Kfw BankenGruppe Wheb Ventures Ltd.
Matignon Investissement
& Gestion
Meridian Venture
Partners
Woodside Fund
Zernike Group
NGEN Partners Zouk Ventures
Nomura, New Energy &
Clean Technology
Ventures
Cycad Group VC Nth Power E+Co
Omar A. Sawaf
Interviews and surveys were undertaken between October 2006 and April 2007.
On-line surveys were mostly undertaken between January 2007 and February
2007. As much as possible, the funds, which participated in the surveys, were
interviewed in order to obtain either missing information or supplementary
comments on their policy views or their regulatory risk management practices.
In some cases, the interview also covered the fund manager’s view on why the
clean energy sector has boomed of late (an open question which sometimes led
to their perspective on the role of policy in contributing to this recent growth).
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The compensation for participating in the interviews and surveys which was
offered for participation was to receive a summary of the results, and/or the full
thesis, in return. It should be noted that this might imply that the fund managers
that were interested to receive the results were already quite interested in clean
energy policies and regulatory risk management, thereby possibly adding a pro-
policy bias to the results. However, this potential bias was considered
unavoidable 64 , and potentially harmless, since the main goal of the study was to
understand what active clean energy investors in the field perceive various
clean energy policies and how they manage regulatory risks (and not to test
whether clean energy policy leads in practice to more innovative clean energy
investment by the private equity community as a whole).
The main research approach was to directly interrogate investors with regard to
their fund’s investment activities more generally, but in particular with regard
to their investments in clean energy entrepreneurial firms, and finally with
regard to their views about different market-pull and technology-push policies.
Direct surveys and interviews with fund managers themselves seemed like the
best research approach to gather information on investor perceptions, fund
characteristics and investment activities in the clean energy space. This
approach allowed for the gathering of information that would otherwise be
unavailable, and it allowed for the gathering of information from a
representative set of fund managers at the same point in time. Where
information was lacking because of investor’s lack of time, additional
information was pursued via a web search, soon after the collection of
investor’s perceptions, or via a brief follow-up phone interview with the
investor. In all cases, the same individual was contacted, after establishing
initial contact and obtaining initial input. The main topics covered in the survey
are shown in table 5. The first part of the questionnaire on policy preferences
is the most important, followed by questions to obtain information on fund
characteristics to complement the policy analysis. The total number of question
used in the on-line survey was 30 plus a few questions to obtain contact
information (see Annex 1 for the full survey questions).
64 It was necessary to tell the investors what the study was about in order to interest them to participate
without financial or other compensation available (besides the report) for the research.
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Table 5: Topics covered in the questionnaire by order of coverage
Policy Views
! Market-Pull policy preferences
! Technology-Push policy preferences
! Other – current handling of relevant regulatory issues in the electricity
market, international climate policy preferences, and nuclear power
Investment Criteria, Drivers & Hindering Factors
Region Focus & Policy Environment Preferences
Investment Stage, Exit & Space Preferences
Information Sources & Risk Management
Capital Under Management
Clean Energy Investment Experience
Firm & Fund Type
Team & Contact Information
Basic Characteristics Management &
Skills
CE Views and
Preferences
CE Stage(s) Focus Team Backgrounds CE Drivers
Country of Management Fund Experience CE Hindering Factors
Fund Type Leadership CE Investment Criteria
Firm Type Interaction CE Geographical Focus
Core Investor Types Information Sources CE Technologies Funded
Fund Size CE Typical Time to Exit
Firm Size
Figure 30: Fund characteristics, fund particularities and clean energy views and
preferences
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Looking at only fund characteristics only, Figure 30 lists the fund
characteristics studied and splits them into three main categories: 1) basic
characteristics such as fund type and fund size, 2) particularities’ such as staff’s
backgrounds or experience in the clean energy sector, and 3) views and
preferences related to the clean energy sector, such as views on drivers they
believe are important to stimulating VC/PE investors’ interest in the clean
energy sector.
Basic characteristics
! CE Stages Focus - The fund’s preference or focus on particular
investment stages (seed-capital, start-up, expansion, replacement capital,
buy-out, or several, or all)
! Country of Management or geographical location of the fund - Which
country the majority of their team is based at
! Fund Type - e.g. A dedicated clean energy fund, a cleantech fund, a
general VC fund or a general private equity fund, or other type of fund
! Firm type – This is the type of firm such as a bank subsidiary, an
independent firm, a corporate venture capital (CVC) company, etc.
! Core Investor Types - These are the limited partners or core investors in
the fund such as the following: corporations, banks, pension funds,
private individuals, governments, etc.
! Fund Size - This is defined as the current funds available (funds raised
for the fund) to invest in clean energy VC or private equity deals, in
Euros. Note: it was also asked how much growth the fund manager
expected to see in the size of their funds by 2015.
! Firm Size - This is defined as the total VC and PE funding of the firm,
overall, in Euros.
Management & skills
! Team Backgrounds - This would be a measure of what extent different
backgrounds exist among the entire investment team membership of the
fund which deals with clean energy VC and PE investments 65 .
65 This is a fund-level measure of experience by examining investment team backgrounds. The personal
background of the survey or interview respondent will obviously affect the results of this study
significantly. However, rather than focusing on the individual’s background, because of length
restriction in the survey it was rather chosen to focus on the entire team’s background as this was
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! Fund Experience - This was measured by the year of the first VC or PE
investment the fund made in the clean energy sector 66 .
! Leadership - The number of rounds in which the fund was the lead
investor among the deals they invested in.
! Interaction - The fund’s level of activity with regard to Policy-makers
and their portfolio companies.
! Information Sources - Key information sources used by the fund
managers in their decision-making process regarding deals in the clean
energy sector. This may include internal staff intelligence, institutional
investors, other investors, news media, investment banking reports, etc.
Clean energy views and preferences (besides policy preferences)
! CE Drivers - The fund managers’ perceptions about what drives the
clean energy market. These include: climate change, security of energy
supply, competitive advantage (of firms), and air pollution.
! CE Hindering Factors - The fund managers’ perceptions about key
hindering factors for continued growth of the clean energy VC/PE
finance space.
! CE Investment Criteria - The fund’s five key investment criteria for
deals in the clean energy sector
! CE Geographical Focus – This is the fund’s regional focus (e.g. North
American, Europe, etc.)
! CE Technologies Funded – The fund’s investments in clean energy sub-
sectors or segments (e.g. wind, solar PV, solar thermal, biomass for
power, biofuels for transport, stationary fuel cells, energy storage, fuel
cells for transport applications, etc.)
! CE Typical Time to Exit - The fund’s expected and typical time to exit
for clean energy deals
Annex 2 explains in further detail each characteristic that the study looked at.
deemed to be a more accurate measure of the overall funds’ expertise level across industries. Obtaining
data on only the respondent would have likely biased the findings inappropriately when the objective is
to use the information to analyze funds’ overall capabilities and knowledge of the energy sector, for
example.
66 This is another fund-level measure of experience. It is not intended to measure expertise as expertise
can be acquired. Therefore, it does not measure the quality of the individual expertise of team members
either.
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Briefly, some statistical results on the basic characteristics of the sample are
shown in table 6. This shows that the sample was quite representative of the
sector. Given the diversity of fund characteristics, the sample is a good
representation of the diverse world involved in private equity investments, and
shows that the sample does not represent a minority of types in the field.
Table 6: Summary of basic characteristics of the funds reviewed
CE stages focus 44% expansion, 28% seed & start-up, 12% laer stage,
Fund geographical
preference
16% all stages
44% North America, 28% Europe, 18% all regions, and
10% both EU and North America. Note: Most of the U.S.-
based funds invest in North America only.
Fund location 47% U.S., 21% UK, 32% rest of Europe
Fund type 31% Clean Tech Funds, 23% Dedicated Cean Energy
funds, 22% General VC funds, 14% General PE funds,
10% others
Firm type 61% Independent firms, 19% Banks & Subsidiaries of PE
Core investors
type
firms, 11% Corporate VC, 9% Government
36% Mixed, 22% Private, 22% Corporate, 11% Banks,
5% Government, 4% Pension funds
Fund size 37% 0-20M, 30% 100-250M, 21% 10-100M, 12% 250-
500M
Firm size 25% 0-50M, 12% 50-100M, 21% 100-250M, 16% 250M-
1B, 16% 1B-5B, 10% N/A.
In addition, the following was gathered from the sample:
- 80% of the funds already invested in clean energy.
- Almost all funds had made their last clean energy investment in
the year of the study (2007).
- Technologies invested in were mainly solar PV among the
sample (37 deals), followed by fuel cells for transport (19),
energy storage (16), wind (15), stationary fuel cells (15),
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iopower (11), biofuels (11), hydrogen from renewables (4), solar
thermal (3), geothermal (3), and marine/wave power (1).
- About 1/3 rd had already invested in clean energy before the year
2000.
Furthermore, section 6.1, on the basic characteristics of the participating funds,
and Annex 3, looks into detail at the various characteristics of the sample of
funds used for the empirical data analysis and provides a few specific examples
on how the sample is representative of the clean energy VC/PE finance space
as well as the entire VC/PE industry.
Therefore, information was collected on policy preferences with regard to
market-pull and technology-push policy options, but also on a number of basic
characteristics of the funds, management practices and skills, as well as clean
energy views and preferences. Investors were asked about major drivers for
clean energy investment, hindering factors for more clean energy investment,
their investment criteria for clean energy deals, their typical time to exit for
clean energy deals, various fund characteristics (size of clean energy funding,
size of all VC or PE funding, fund type, firm type, etc.), and various factors
which are relevant to how they manage their funds. Funds were asked about
their most influential sources of information, what type of core investors invest
in their funds, how much exposure and interaction they tend to have with
Policy-makers and portfolio companies, what backgrounds do their investment
teams tend to have, etc.
5.3.2 More details on the data collection process and approach
In order to obtain findings on a full range of policies and options, policy
perception questions were not only about the selected options among basic
market-pull and technology-push options, but also about international climate
policy, nuclear energy and regulatory issues in the electricity industry which
are relevant to clean energy and considered by some to be prerequisites for a
functional clean energy market, as opposed to policy options. Perceptions on
the market-pull and technology-push policy options were generally based on a
5-scale-rating. The respondents replied to the questionnaire either online, in
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written form, or in an interview. About 10% of the time (6 cases) the
interviewees did not have enough time to complete the full interview and only a
sub-set of questions were asked of them in such cases. On-line surveys
provided for the most extensive information gathering. Finally, the short paper-
and-pencil surveys were the least complete sources of empirical data, however
they were conducted after the interviews and on-line surveys were collected in
order to further complete the data set. This survey was conducted at a major
international conference for VCs in the cleantech industry 67 . This last set of
responses included answers to only the key questions on the market-pull,
technology-push policies and international policies, as well as their ranking of
market drivers and their 5 key investment criteria for clean energy deals. In this
survey, a number of respondents were anonymous but only the responses with
firm name indicated were used in the final analysis as this data was then
complemented with an Internet search for each firm 68 .
The research started with in-person and telephone interviews in order to better
define the set of questions that would be relevant to answering and
complementing the analysis and exploration of the four major research
questions. The tool, which was used for the long surveys (all 30 questions), was
on-line survey software called “feedback server” from the Swiss Federal
Institute of Technology in Lausanne (EPFL). This software allows respondents
to take part in the survey on-line and also provides the researcher with a tool
for collection of data, basic reporting and analysis of the results. Funds were
allowed to respond to the survey anonymously, but it was recommended that
they provide at least their firm’s name for research purposes. In any case they
were assured of 100% confidentiality in all cases.
The sample is considered to be representative of the general investment actors
in the venture capital and private equity investment space in the clean energy
sector. The survey was first sent to 200 investment companies in the private
equity field that were located around the world, but mostly located in Europe.
67 Indeed, this set of empirical data may be slightly biased towards US-based cleantech funds because
the conference was held in San Francisco, and the conference was not a clean energy only conference
but focused on all clean technology VC investment areas. The conference was the Cleantech Venture
Networks’ 2006 forum in San Francisco, held in mid-February, 2006.
68 The researcher filled in missing demographic data which could be obtained indirectly via the funds’
internet sites. Also, in some cases, respondents to the short survey had indicated that they could be
contacted to complete the full survey by telephone.
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Emails were directed to the Managing Director or a similarly senior position in
each company. It was later estimated that about 100 of the funds reached were
effectively involved or interested in the clean energy sector. Therefore, a more
focused list of these 100 funds was used in a second email mailing to invite
participants to utilize the on-line software to complete the survey. A thorough
research of relevant people at each fund was conducted in order to increase the
response rate among this set. Initially, the response rate was not high enough
after this mailing, so follow-up emails were sent to select groups of investors
that were considered to be the most important players in the field. In some
cases, the fund managers that were contacted were invited to participate in a
quick interview of 10-15 minutes only, in order to increase the response rate
among this busy and important set of funds. Although the data has been
compiled via three different methods and with varying completeness, in this
manner it was possible to reach a response rate of approximately 60% among
the funds that were deemed to be the most important players in the field.
Considering the time availability of venture capitalists for academic research of
this type, this can be considered to be quite a good outcome. Furthermore, the
additional reach was considered to be more important than the thoroughness in
answering all the survey questions, as the most important questions were
anyway answered by almost all the participating fund managers. As for the
professional level of the fund manager which participated in the study, the
majority of the respondents to the surveys and interviews were at senior level in
the funds, i.e. Director, Partner, Principal or similar 69 .
69 Note that not every respondent declared their title or position. Out of the 60 funds, 55 declared their
position.
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Number!of!funds/firms
40
35
30
25
20
15
10
5
0
38
Director,!Partner,!or!similar Investment!Manager,!Investment!
Analyst,!or!similar
Figure 31: Number of respondents by type of respondent
5.3.3 Response rates
The response rates to the questions in the full on-line survey varied because of
the use of a shorter-survey, which primarily included the key policy questions.
There were very good response rates for all the key policy questions (the lowest
response rate for the two sets of policies was 88% and the highest was 100%).
However, some questions such as on important information sources received
response rates of between 50-70%. This must be taken into consideration when
reviewing the results of this thesis, as it means the conclusions on average
policy preferences are the most robust of all findings. For all results shown by a
figure in this thesis, the sample size for the given question (the number of funds
that answered the question) is shown in the notes to each figure. The results on
regulatory risk management were also based on slightly fewer respondents as
not every fund manager answered the open question about their regulatory risk
management practices. About 30 responses to the question on regulatory risk
management were used in the analysis (see results in Chapter 8).
17
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Table 7: Response rates for key questions
Did your fund ever investigate policies? 91%
Has your fund invested in clean energy technologies? 92%
Market-pull policy preferences
Government procurement 95%
Feed-in tariffs (FiTs) 98%
Residential and commercial tax credits 95%
Production Tax Credit (PTC) 97%
Technology performance standards 95%
Renewable Portfolio Standards (RPS) 98%
Renewable Fuel Standards (RFS) 97%
Green certificate trading 94%
Clean Development Mechanism (CDM) and Joint
Implementation (JI) of the Kyoto Protocol 94%
CO2 emissions trading 100%
CO2 emissions tax 97%
Reduction of Fossil Fuel Subsidies 94%
Would you change answers for more mature technologies? 88%
Is Nuclear competing with CE technologies? 72%
Technology-push policy preferences
Doubling publicly financed R&D 95%
Doubling privately financed R&D 95%
Soft support mechanisms 92%
Incubators for start-ups 94%
Tax breaks for entrepreneurs 92%
Grants for small and medium-sized enterprises (SMEs) 94%
Government demonstration grants 95%
Government-sponsored VC funds 92%
Government investment in private VC funds 92%
Tax breaks for investors 88%
Investment subsidies 94%
International policy
International agreement type preferred 97%
Fund Characteristics
Fund type 98%
Stages of investment 95%
Firm type 100%
105

Core investor types 84%
Regional Focus 97%
Funding levels (CE Fund and Firm size) 72-74%
How much will your fund's CE funding level increase? 78%
Time with Policy-makers and companies 64-69%
Information sources 53-61%
Lead investor on funding round 65%
Experience 88%
Backgrounds of the team members 59-75%
Hindering factors for clean energy investment 56-65%
Time to exit for investments 75%
Finally, in order to understand what drives investors to invest in clean energy
today, it was also considered of interest to interview a number of investors in
the clean energy field that were not in the category of venture capital and
private equity fund managers. Therefore, a few additional interviews were
conducted to supplement the qualitative research in this thesis with the
following types of investors: 1) institutional investors which invest in clean
energy funds (one pension fund, three banks, and one fund of fund), 2) project
financiers (three private equity investors for projects in the clean energy sector),
and finally 3) a few advisory firms in the private equity and venture capital
space for clean energy technology ventures. The results from these interviews
were used in the analysis of the decision-making process of VC and PE fund
managers with regard to what makes them invest in the clean energy sector in
the first place (e.g. what leads their firms to raise funds for a dedicated clean
energy fund in the first place).
Fund-level data (fund characteristics) were mixed with individual-level data
(perceptions) as individuals were selected to serve as a proxy to study decision-
making on the fund level or how such perceptions might influence decision-
making. In other words, the research approach was based on cross-sectional
self-reported data. While there are analytical issues with regard to this approach,
it was deemed as the most practical approach possible and the most desirable
option available given the objectives of the study. It should be pointed out that
venture capitalists and private equity fund managers tend to refuse
systematically academic research interviews or surveys due to the nature of
their rapidly moving business. Therefore, first of all it was not practical to
106

conduct multiple surveys or interviews with staff in each of the funds that
volunteered to participate in the study. Furthermore, the goal was to speak
mostly to Principles or Directors of funds, which were even more time-
constrained. The positive aspect of the choice was that the findings are based
more on the feed-back of Directors of the funds, which were assumed to have a
better understanding about policies and the funds’ risk management practices,
than if more than one staff member in the lower ranks of the fund had been
interviewed per fund.
As discussed before, the private equity investment space includes venture
capital investment, but while venture capital investment was originally viewed
as investment in young entrepreneurial start-ups, the practice of venture capital
investment is now something quite different from the traditional early-stage
high-risk finance of new entrepreneurial firms. Today certain large venture
capital firms act more like what are called in this thesis private equity funds.
They involve larger sized expansion-stage deals or private investment in
growing companies, and while these deals are still risky, private equity
investors carry out very detailed investigations into both the potential deal and
the project before making any investment (in a process called “due diligence”).
Therefore, they reduce the information gaps that exist between companies
needing capital investment for growth and potential investors, or “information
asymmetry”.
Meanwhile, information asymmetry is most acute for venture investments in
long-term funding of high-risk, new ventures. It is indeed difficult to
differentiate between these two types of funds, also because in reality funds use
different strategies regardless of what type of fund one can try to define them
as. This is why in this study which stages each fund invests in are important to
analyze, as well as fund and firm type, as this indicates the level of early vs.
later stage focus of the funds. Again, some funds may invest across all stages,
but in these cases the level of funding and the type of investments they make
can be an indicator of how these funds are operated. They may act more like a
traditional venture capital fund which invests in very early stage companies and
are generally more hands-on with regard to their portfolio companies, or they
may be more like the newly evolved funds which focus on later-stage deals
more than they focus on early-stage deals.
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5.3.4 A few limitations of the research method
A few limitations have already been discussed; this section adds further
explanation regarding key limiting factors of the approach undertaken. The first
limitation of this work is the lack of multiple responses per fund that would be
a preferable approach, in order to reduce individual-level bias given that the
level of analysis chosen was the fund-level. Unfortunately, given the small
amount of firms active in the clean energy venture finance space, there were
few fund management teams to choose among. The small sample size therefore
significantly reduced the chance of conducting multiple surveys per firm and
indeed, few firms were willing to volunteer the time of two key individuals
from their fund management team (which tend to be quite small teams, as well).
Second, the survey length was quite long, given the exploratory nature of the
work. Third, the time constraints of venture capital and private equity fund
managers, especially those at the higher levels of the company, are a major
constraint for this type of empirical study. As shown above, if only the
responses of top-level managers were considered for this study, the sample size
would have decreased significantly. It was more difficult, generally, to speak to
a top-level manager for a fund in the case of the larger-sized firms. In these
cases, often an investment manager, or the equivalent, which was actively
involved in managing the fund’s clean energy deals, participated in the study.
Therefore, the self-reported data nature of this study is a recognized limitation
of the research design. However, this is a newly emerging industry, and the
study was not intended to test hypotheses, but rather to develop them. Also, a
final limitation that should be noted is that because of the time constraints of
the fund managers, some of the telephone interviews could only be partially
completed (e.g. fund managers sometimes agreed to only spend 15 minutes for
the interview, instead of 30 minutes). In such cases, it was sometimes possible
to follow-up with the investor to complete the interview, and in other cases it
was not. On the other hand, other fund managers were happy to speak for a
longer amount of time, which enabled the gathering of other relevant
information such as their perspective and further anecdotes on how policy plays
a role in driving investment in clean energy VC today. In the worse case
scenario, however, it was always possible to fill in the gaps regarding the
funds’ basic characteristics, through an internet search, as the first questions
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asked were always with regard to the policy options in order to ensure a high
response rate with regard to this main output of the thesis.
Finally, it should be noted that there are advantages to the mixed methods used
in this research (e.g. long survey, short survey, telephone interviews, and
longer in-person interviews). First, both quantitative and qualitative
information could be collected, compared, and analyzed given the use of a
semi-structured interview that closely resembled the longer on-line survey.
Furthermore, the flexibility in the approach allowed deeper questions to be
answered via the interviews, for a better understanding of the more structured
questions. Also, interviews alone may have led to less structured results. Yet,
the interviews were indeed the richest source of data. Therefore, interviews
were not only limited to the fund managers not also held with a number of
experts, institutional investors, and relevant organizations with knowledge
about clean energy investment trends, implications of policy on VC/PE finance,
and key drivers for the growth in investment levels for this space in recent
years 70 . Finally, it was easy to conduct the research in such a way as a result of
significant knowledge building (10 years of work experience in the area of
energy and climate policy, with exposure to Policy-makers as well).
70 However, the results from such interviews were not reported in this thesis as the level of analysis was
VC/PE fund managers. These additional interviews were used to both design the questions for the
structured interview/survey and in order to better interpret the findings.
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6 Characteristics of funds
6.1 Basic characteristics of funds
This section reviews the type of data collected with regard to fund
characteristics and in doing so provides some overall results on the various
characteristics of funds interviewed and surveyed. It also provides information
to show how representative the sample is of the market players in question.
This information was collected because as described earlier different types of
funds that invest in clean energy (sometimes referred to as “clean energy
funds” in this thesis) are likely to have different views about clean energy
policies, depending on their fund characteristics.
First of all, 80% of the funds had already invested in clean energy and 80% had
already investigated relevant public policies.
Next, as can be seen from Figure 32, a significant share (44%) of the 60 funds
invests in the expansion stages 71 . The next largest category is funds focused
primarily on seed and start-up finance (28% of the total). Among this 28% in
the seed and start-up stage category there are three funds focusing only on seed
capital, 6 funds focusing on both seed and start-up capital, and 7 funds focusing
only on start-up funds (the total sample size was 60). A smaller fraction (16%)
of funds reviewed invested at all stages. Later-stage funding represents 12% of
the fund sample (this group is mostly composed of funds focusing on
expansion, replacement capital and buyouts (6 funds). Out of the 7 later-stage
funds, only one was actually focused only on buyouts.
71 However, those placed in the expansion category are mostly funds which invest in both expansion
stages as well as start-up stages (18 funds) while a minority among this group focused only on
expansion stages (7 funds). It was deemed that if the fund invested at all in the expansion stage, it
should be placed in the expansion category, even if it also invested in start-up finance. The start-up
finance they are likely to invest in will most likely be closer to the expansion stage of a company, than
the very early start-up phase of a company.
110

Late stage
12%
All
16%
Expansion
44%
Seed and
start up
28%
Figure 32: Stages that funds invest in
Note: response rate = 95%.
EU & North
America
10%
All
18%
North
America
44%
Europe
28%
Figure 33: Overall regional focus for all funds
Note: response rate = 97%.
Funds were asked to select their geographical focus for investments in clean
energy among a number of regional categories including North America,
Europe, Australia/New Zealand, Asia, Africa, and Latin America. As for
geographical preferences of the funds in the sample, most of the funds focused
their clean energy investment in North America (44%), followed by Europe
(28%), all regions (18%) and both EU and North America (10%) (see figure
33).
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Most of the U.S.-based funds invest in North America only (of course they may
invest across a variety of U.S. states and state policy environments). About
one-third of UK-based funds have a focus only on North America. Most funds
located elsewhere focused on both Europe and North America with regard to
CE VC/PE investments. Figure 34 below shows that most funds based in the
United States focus their investments on North America only. This partly
explains the focus on North American markets in the sample, because
European-based funds were not in the same way only focused on European
markets.
30
25
20
15
10
5
0
US UK Other EU
EU+NA+Other
All
EU+NA+Asia
Europe only
North America + Latin
America
North America + Asia
EU+North America
North America only
Figure 34: Regional focus of investment by location of funds
Note: locations are grouped by U.S., UK and other EU. N = 53.
U.S.-based funds interviewed said they tend to focus on North American
companies because many of them like to be hands-on, and also because the
market and diversity of regulatory environments is large enough in the United
States only. In the interviews and surveys, when all respondents were asked
why recent investment figures showed that clean energy funding was higher in
the U.S. than in Europe (e.g. New Energy Finance data for 2005 and 2006)
investors responded that the U.S. has the following desirable attributes for an
investor (note that these are mostly general investment environment
characteristics and almost all of them are not particular to the clean energy
sector):
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o More years of experience in an alternative asset class (venture capital
and private equity for companies)
o More comfort on behalf of institutional investors for the alternative
investment class (private equity)
o More freedom among larger fund managers to use money from
institutional investors - More “dry powder” available
o Better market for venture capital (specialists, know-how, etc.)
o Some VCs (especially American VCs) are very hands-on and like being
in close proximity to their portfolio companies
o Better entrepreneurship, in general, in the U.S. – e.g. more experienced
entrepreneurs
o More liquidity in the market
o More coherent end-use markets
o Greater land areas for wind, solar, ethanol
These general factors may explain the tendency to focus on North-American
deals, despite more supportive policies for in particular less mature clean
energy technologies in Europe, e.g. Germany and Spain. Also, in the interviews,
many investors said nothing stops them from investing in an American
company that will install equipment in a country with a supportive policy
environment, like Germany. Literature also supports this finding. Leleux
(2006), has noted that the U.S. industry revived nicely in 2004 and 2005, to
levels often seen as « sustainable », on the back of demonstrated performance
by the industry as a whole. The European VC industry is showing signs of
revivals in 2006, but it seems to be by « default », not by « true commitment »
and belief, according to Leleux. However, in the clean energy sector one must
note that there are many American firms that are coming to London to list on
the AIM public market as it has more favorable conditions for small clean
energy companies going public. Meanwhile, as for the overall market, Leleux
notes that performance is exit-driven: with IPO markets cooling off and trade
sales taking longer, he says patience is going to be needed, even more than
before. Finally, he notes that European VCs have lived through their first down
cycle: the education was expensive, but they are now better equipped to
function.
Moving to geographical preferences by technology segment (a possibly more
policy-relevant measure of geographical preference), one of the main findings
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of this study is that the best perceived policy environment for solar PV
technology is clearly Germany (see Figure 35).
Number!of!respondents
35
30
25
20
15
10
5
0
FR
ES
GB
JP
US
DE
IL
CN
ES
US
DE
NL
DK
FR
ES
GB
US
DE
IS
NZ
FR
US
DE
BM
AU
PT
ES
GB
BR
GB
JP
US
BR
AT
GB
US
DE DE
CA
GB
US
CN
CA
IS
GB
DE DE
KR
US US
CN
CA
US
DE DE
Figure 35: Number among all respondents choosing a particular country in
terms of best policy environment by technology
Note: N = 32 72 .
This was also the view of U.S.-based funds (Figure 36), supporting the finding
that feed-in tariffs provide the best investment climate for venture
capitalists/private equity investors. Spain, which also has feed-in tariffs, was
deemed the best market for solar thermal technology. One can also take note
that U.S.-based investors clearly liked the U.S. policy environment for biofuels
for transport (and the same was true for all investors as well).
72 Actually, some of the technology areas have results which are less robust due to a lower response
rate in these categories compared to the solar PV question which received answers from the full 32
respondents to this question. That is among the 32 respondents for this set of questions, the full 32
replied for PV, but only 22 replied for the question on wind, 14 on marine/wave energy and 12 on
biomass for power.
IL
CN
KR
BR
AT
CA
BM
AU
PT
IS
NZ
NL
DK
FR
ES
GB
JP
US
DE
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Numer!of!respondents
14
12
10
8
6
4
2
0
ES
JP
US
DE
IL
CN
US
NL
DK
ES
US
AU
BR
GB
US
NZ
GB US
DE DE DE
JP
BR
US
CN
KR
CN
US US US
Figure 36: Number among U.S. only respondents choosing particular best
policy environments by technology
Note: N = 13.
Germany was obviously a favorite country for investments in PV technology,
but other countries, which were favored per technology segment in the full
sample results, were:
! U.S., Germany, Denmark and Spain for wind energy
! UK for marine/wave energy
! U.S. and Germany for biomass for power
Figure 37 gives their respective share of country locations in the sample of
funds reviewed. Data was collected on the exact country of fund location, but
as there is sometimes only one fund per country, results by the exact country-
breakdown are not provided in this thesis work due to confidentiality purposes.
A little more than half of the funds reviewed are based in Europe, with more
than a third of them being based in the UK. Another half of the funds reviewed
are based in the United States.
IL
CN
KR
BR
AT
CA
BM
AU
PT
IS
NZ
NL
DK
FR
ES
GB
JP
US
DE
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Europe!
" Others
32%
GB
21%
US
47%
Figure 37: Location of funds by region
Note: response rate = 97%.
Figure 38 shows stage of investment focus by the country of management
(location of funds). A dominant share of the expansion stage funding (recalling
that the expansion category includes some start-up finance as well) is coming
from funds that are based in the United States. Next, the United Kingdom is an
important player with regard to start-up and expansion funding. Finally, other
European countries are quite active in all stages or else also in the seed and
start-up stages, while they are relatively the least active (among the sample) in
the expansion stages. A final point is that funds based in the United States
dominate the expansion and later-stages of finance among the sample
(expansion, replacement capital and buyout stages). This preference for
expansion stage investment, however, is not only pertinent to U.S.-based funds.
One of the UK-based funds mentioned in their interview that they do not invest
in start-up stages because the expansion stage deals have shown better exits
than start-up stage deals in the clean energy sector. They thought that either
governments or corporate investors should finance the seed and start-up stages
of investment.
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14
12
10
8
6
4
2
0
Seed+S
Expansion
Late
All
US
US
Great Britain
Other Europe +
Others
Other Europe + Others
Figure 38: Country of fund management (location) by investment stage
Note: response rate = 97%.
Literature on clean energy investment trends also confirms that the distribution
of VC and PE investors in the clean energy field are most active in the
expansion stages, therefore the sample is representative of the sector in this
way. SEFI/NEF (2007), report that, “VC activity has moved up the maturity
spectrum, with later funding rounds attracting most investment. There was
noticeably higher investment in China during 2006, most of which was PE for
solar manufacturing expansion. Biofuels, biomass & waste, solar and wind in
roughly equal shares dominate private equity investment for expansion. In early
2007, all stages of venture capital and private equity investment saw increased
activity, with later-stage leveraged private equity investments putting in a
particularly strong showing.” Finally, the study’s sample appears to be a fairly
representative sample for Europe, when compared to the total VC/PE industry
in Europe 73 .
73 For example, the stage distribution by percentage of number of investments made in Europe in 2005
was 41.8% in the expansion stage, 21.7% in the buy-out stage, and 29.1% in the start-up stage. 3.8%
were seed-capital deals, and 3.6% were replacement capital deals. Furthermore, while noting that the
number of funds which focus on a given stage is not the same as the percent of funds spent on a given
stage, the following data gives an idea about the importance of later-stage deals in the general VC/PE
space in Europe, as well. As for the entire private equity industry, buyout stage finance is 68.2%, and
expansion capital is 21.8% (start-up is only 5%, and seed-capital is a mere 0.2%) of the total amount of
money invested (private equity) in Europe in the period 2001-2005, according to the European Venture
Capital Association (EVCA) (2006).
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As for industry-wide distribution, the European Venture Capital Association
(2006) shows that in Europe, the UK has 50% of total invested VC/PE in
Europe. Of all other European countries, France has 15% of the total VC/PE
market by amount invested, followed by Sweden with 6.4%, Germany with
5.7%, Spain with 5.7%, the Netherlands with 5% and Italy with 4.7%. The rest
of Europe represents 6.4% of total European VC/PE finance (by location of
fund) (EVCA, 2006).
Figure 39 gives the share of each type of fund in the total number of funds
reviewed. The sample of funds reviewed is therefore represents a good
diversity of fund types investing in the clean energy sector. However, literature
is not available to confirm if this diversity is represented in the overall clean
energy VC/PE sector, as well. Clean Tech funds (CTF) are the most
represented in the sample, with almost a third of the respondents, followed by
Dedicated Clean Energy funds (DCE) and General VC funds. This prevalence
of cleantech funds might be due to the higher presence of cleantech funds in the
United States, as this research also showed that a high number of U.S. funds
were cleantech funds as well. It is recognized, however, that this prevalence of
cleantech funds in the United States may be due to a bias in the research
approach. The shorter hand-written survey was distributed in February 2007 in
San Francisco at the Cleantech Venture Network’s (CTN) U.S. Forum.
Attendance at an earlier Forum of CTN in Europe which was held in London
(June, 2006) and another European conference on venture capital in Zurich
(October 2006), however did help to obtain more interviews with European-
based funds.
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General!
VC!fund
22%
General!
PE!fund
14%
Other
10%
DCE
23%
CTF
31%
Figure 39: Share of fund types
Note: response rate = 98%. CTF stands for Cleantech Funds; DCE stands for
Dedicated Clean Energy Funds.
As can be seen in Figure 40, the most notable type of firm backing these funds
is independent firms (61%). Banks and subsidiaries of private equity firms
were the next most important category at 19%. CVCs and government-backed
VC firms were a minority. As for the entire European VC/PE industry,
independent firms are equally prevalent, with other firm types being more of a
minority, meaning the sample features a representative proportion of firm types.
For example, out of 100 members of the EVCA that invest in the energy sector,
57 of them are independent firms (meaning they have no parent) (EVCA 74 ,
2007). In the study’s sample, independent firms represent almost two thirds of
the funds reviewed, so this proportion appears to be slightly more for the clean
energy sector. There are no other figures available for the entire clean energy
sector, in order to compare the sample distribution by firm type, with all clean
energy investing VC/PE firms.
74 See member search at www.evca.com
119

Indep.
61%
Bank &
SubPE
19%
CVC
11%
Gov.
9%
Figure 40: Share of firm type backing the funds
Note: response rate = 100%. CVC are Corporate Venture Capital (CVC) firms;
Indep. funds are independent venture capital or private equity firms; Bank &
SubPE are generally private equity firms; Gov. generally represents the
government’s investments in seed or start-up venture capital.
Figure 41 shows that independent firms are active at all stages of investment.
Meanwhile, they are most notably active in the expansion stage of finance
(with some start-up finance), and next the start-up stage (with some seed-
capital).
20
15
10
5
0
Indep LP Corp CV C
G ov.
S ubP E
B ank
FO F
Late s tage
S eed or s tart-up
S eed or s tart-up
E x pans ion
Late s tage
Figure 41: Number of firms by firm type and stage of investment focus
Note: response rate = 100%.
A ll
120

On other firm types, most of the government-backed VC funds interviewed and
surveyed tended to focus on seed or start-up stages. Most of the corporate
venture capital funds interviewed and surveyed tended to focus on the
expansion stages while most of the corporate-backed funds (Corporate LPs)
interviewed and surveyed tended to focus on start-up stages. Most of the
subsidiaries of private equity firms interviewed and surveyed tended to focus
on expansion stages or their firms were active in all stages. Most of the banks
interviewed and surveyed were focusing on later stages (e.g. the buy-out stage)
or all stages. Finally, most of the funds of funds interviewed and surveyed
tended to focus on all stages.
Also, funds reviewed have a variety of core-investors in each fund. This is
different to the parent-firm of the fund or firm type. For example, in Europe
each country has a different proportion of core investors that generally
contribute funds to private equity fund managers. In the Netherlands, the
majority of funds are invested in by banks, in Switzerland the majority are
invested in by corporations, in the UK there are more pension funds investing
than in other countries, in Germany there is a very diverse set of core investors
in funds, in general, etc. (EVCA, 2006). As for the clean energy sector, Figure
42 gives the share of each type of core investors in the overall set of VC/PE
funds participating in this study. Most of the funds are invested in by a mixed
set of investors (as is the case for overall VC/PE investment in Germany),
followed by private investors and large corporations.
121

Mixed
36%
Private
22%
Bank
11%
Corporate
22%
Gov.
5%
Pension
4%
Figure 42: Share of core investor types in full sample
Note: response rate = 84%. Private means private investors - often high netwealth
individuals.
The results for technology investment choices by type of investor also show
that they may have a key influence on investment decisions (more precisely,
the decision to invest in an established clean energy technolgy area or a less
mature clean energy technology). This is shown by the corporate investment in
fuel cells (both mobile and stationary) technology ventures, as well as
potentially by the private individual investment in solar PV and wind energy
which obviously receive the most public attention (news media, etc.). Of
particular interest is that private investors (e.g. wealthy individuals) clearly
dominate the solar PV investments among the sample that responded to this
question. However, it must be noted that the data collected on technology areas
for deals was not completed by all the funds leaving the findings relevant to
this issue less robust 75 .
75 This question received a 48% response rate. 28 funds did not answer this question while 31 funds did
answer the question. This was partly due to the fact that not all questions could be asked and a shorter
survey was employed to increase the sample size for the most important questions relevant to the thesis
research questions.
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45
40
35
30
25
20
15
10
5
0
Mixed
Private
Pension
Gov.
Corporate
Figure 43: Clean energy technology investments by type of core investors
Note: N = 29
Different levels of funding, and different levels of firm total funding for VC
and private equity investments as shown in Figure 44 are represented among
the funds which took part in the survey. The number of small funds represents
27%, medium-sized funds 31%, large funds 30% and very large funds 12%.
As for fund size relative to stage of focus, large funds focus more on the
expansion stages although some also invest at other stages. Small-sized funds
reviewed show a great diversity in investment stage focus, but tend to do more
start-up and early expansion-stage investments. Medium-sized funds mostly do
expansion finance and some seed or start-up finance.
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100-250M
30%
250-500M
12%
10-100M
31%
0-10M
27%
Figure 44: Fund sizes among the sample
Note: response rate = 72%.
There was a quite diverse mix of firm sizes (firms backing the fund) in the full
sample, as well. 25% were 0-50M, 12%50-100M, 21% 100-250M, 16% 250M-
1B, 16% 1B-5B, and 10% did not answer. Another characteristic of the sample
is that when taking the larger firm sizes into consideration, the firms’ clean
energy funding proportional to their firm size was quite large in a few cases.
1B-5B (very
large size)
16%
250M-1B
(large size)
16%
N/A
10%
100M-250M
(medium
size)
21%
0-50M (very
small size)
25%
50M-100M
(small size)
12%
Figure 45: Firm sizes among the sample
Note: response rate = 74%. Different categories from Figure 44 are used
because firm sizes are sometimes much greater than fund sizes and the
breakdown was more or less an even one starting from very small sizes to very
large sizes for each.
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For example, the majority of firms with a size of 100-250M Euros spent on VC
and PE investments spent 100% of their funds on clean energy VC/PE finance.
Similarly, the two funds with VC/PE spending or firm size of 250-500M Euros
also spent their entire VC/PE accounts on clean energy. In the case of firms
with a size of 500M-1Billion for VC/PE spending, they spent less (100-250M
or 10-100M in one case). In the case of the largest firm sizes, these firms spent
different amounts on clean energy.
Small firm sizes generally invest in seed-capital. Large and very large firms
mostly invest in expansion or later-stage deal, while medium firm sizes have a
preference for the expansion stages as well.
7
6
5
4
3
2
1
0
0-50M
Euros
50-100M
100-250M
250-1B
1B-5B
Figure 46: Number of firms by size and by stage of investment
Late stage
Seed and start up
Seed and start up
Expansion
Late stage
Note: response rate = 74%. Size here is defined as total funding for private
equity or venture capital.
43% of the funds were small sized clean energy funds (up to 20M Euros for
clean energy investments) and 38% of the funds were large funds (100M Euros
or more). Medium-sized funds made up 18% of the sample. Large fund sizes
clearly focused on mostly the expansion stage. Small funds are more diverse
regarding investment stage focus, with start-up and expansion stages being
more important than seed-capital and start-up stages. This means that overall
the investors in this space are possibly not investing enough in the early stages
of company development. This could represent an important gap (recalling the
technology valley of death) that requires attention from Policy-makers. Indeed,
All
125

one investor interviewed said that they found early-stage investments did not
work well in the clean energy sector. They thought such investments are better
left to corporations and governments.
Results also show that the majority of funds replying to the question on fund
size growth expectations 76 believed that their fund sizes would grow by more
than 100% by 2015. 77 This is an important finding because it points out that the
fund managers interviewed generally expected their fund’s clean energy
financing to continue to rise over time, either because core investors have
already indicated an interest to increase the levels of their funding in this space,
or because their firm has strategically chosen the clean energy sector as a major
new area of VC/PE finance for them to increasingly manage in the near future.
Finally, Table 8 summarizes the basic characteristics reviewed in the above
section.
76 This is how much they expected their firm’s clean energy investment levels to increase by 2015. The
options offered to the respondents in this question were: 0, 0-20%, 20-40%, 40-60%, 60-80%, 80-100%
and more than 100% or N/A.
77 Thirteen funds did not respond or responded N/A to this question, but they were evenly divided
among categories of fund size. But it should be noted that there was only a 60% response rate on this
question.
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Table 8: Summary of basic characteristics of the funds reviewed
CE stages focus 44% expansion, 28% seed & start-up, 12% laer stage,
Fund geographical
preference
16% all stages
44% North America, 28% Europe, 18% all regions, and
10% both EU and North America. Note: Most of the U.S.-
based funds invest in North America only.
Fund location 47% U.S., 21% UK, 32% rest of Europe
Fund type 31% Clean Tech Funds, 23% Dedicated Cean Energy
funds, 22% General VC funds, 14% General PE funds,
10% others
Firm type 61% Independent firms, 19% Banks & Subsidiaries of PE
Core investors
type
firms, 11% Corporate VC, 9% Government
36% Mixed, 22% Private, 22% Corporate, 11% Banks,
5% Government, 4% Pension funds
Fund size 37% 0-20M, 30% 100-250M, 21% 10-100M, 12% 250-
500M
Firm size 25% 0-50M, 12% 50-100M, 21% 100-250M, 16% 250M-
1B, 16% 1B-5B, 10% N/A.
6.2 Further analysis of fund characteristics
This section provides a look at other fund characteristics such as management-
related characteristics, drivers, hindering factors, technologies invested in,
typical time to exit, etc. It analyzes some of the findings by a few of the basic
fund characteristics, as well. A summary of these findings is presented here, but
the details on how these findings were obtained are included in Annex 3.
Technologies invested in were mainly solar PV among the sample (37 deals),
followed by fuel cells for transport (19), energy storage (16), wind (15),
stationary fuel cells (15), biopower (11), biofuels (11), hydrogen from
renewables (4), solar thermal (3), geothermal (3), and marine/wave power (1).
Time to exit was typically about 6 years for all the funds. The distribution was
40% for 5-6 years, 20% for 3-4 years, and 7% for 7-8 years. General PE funds
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mentioned the longest typical time to exit period while funds focusing on
Europe only tend to accept slightly longer time to exit than those who focus on
North America only.
Finally, most funds interviewed and surveyed (80%) had investigated climate
and clean energy policies with regards to how they impact their investment
decisions. The backgrounds of investors that were most important among the
sample were: energy, finance, science and other industrial backgrounds. The
most important were energy and finance for all types of funds, but science-
related backgrounds were high among early-stage and expansion stage focused
funds. Almost all the funds had made their last investment in 2006 or 2007.
The majority of the funds however were investing in the sector post-2000.
Those with experience in the sector pre-2000 were mostly based in the United
States. Most of the funds in the sample were lead investors on the clean energy
deals they invested in (funding rounds) many or almost all the time.
Most of the funds met with Policy-makers rarely (less than one time per
quarter) and they more often met with portfolio companies. Therefore they are
generally not lobbyists. However, when looking at stage of investments, later-
stage focused funds do meet with Policy-makers more often than other types of
funds, and they meet less often with portfolio companies than other types as
well.
As for information sources that are of importance to funds, overall, key sources
of information were: internal staff intelligence, final consumers, specialized
industry reports, advisors on technology and corporate buyers. Later-stage
focused funds tend to also consider institutional investors and investment
banking reports, and other investors as important sources of information.
As for drivers, the main driver for investment in clean energy, overall, was
competitive advantage. This was followed by security of energy supply and
climate change. Air pollution was the least important driver. Large firms tended
to give climate change a greater importance than small-sized firms. Small to
large funds gave competitive advantage the most importance and very large
funds ranked climate change and energy security high. Finally, EU-based funds
gave more importance to climate change than U.S.-based funds.
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With regard to hindering factors to further clean energy investment by the
VC/PE community, fund managers rated high capital expenditure, long lead
times, lack of track record, less experience and technology risk as important
factors to them. U.S.-based funds mostly mentioned less experience, along with
high capital expenditure, long lead-time, fossil fuel subsidies/lack of
internalization of external costs, and lack of track record as high on their list.
EU-based funds were much less concerned about less experience, fossil fuel
subsidies and high capital expenditure, but were more concerned about lack of
consistent government support. UK-based funds rated many hindering factors
lower than the U.S.-based funds and other EU-based funds. Large funds are
much less concerned about fossil fuel subsidies, lack of competent VCs, and
high capital expenditure in the market than other funds. However, large funds
are more concerned about institutional investors, lack of government support,
lack of deal flow, and market power of incumbents.
The following tables summarize hindering factors perceived by type of fund
and type of firm, and order of importance of investment criteria by type of fund.
Table 9: Hindering factors by type of fund
General VC Funds Overall less concerned about hindering factors. But
General Private Equity
Funds
essentially concerned about technology risks.
More concerned overall than general VCs. Mostly
concerned about market power of incumbents, and
lack of trade sale opportunities, high capital
expenditure, long lead time, and deal flow
Cleantech Funds Mostly concerned with lack of consistent government
Dedicated Clean
Energy Funds
support, technology risk, and lack of track record
Mostly concerned about high capital expenditure,
fossil fuel subsidies, and less experience in the
sector
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Table 10: Hindering factors by type of firm
Corporate backed
(CVC)
Overall the most concerned about hindering factors –
mostly high capital expenditure, lack of competent
venture managers, lack or track record, and long
lead-time. However, institutional investors interest
and FF subsidies are not seen as important at all to
these investors compared to others.
Government-backed Overall, they are less concerned about hindering
factors than other firm types, apart from technology
risk that they perceive as very important.
Bank-backed Mostly concerned about lack of consistent
government support and less experience.
Independent firms Mostly concerned about high capital expenditure,
lack of track record and less experience in the sector.
Table 11: Order of importance of investment criteria by type of fund
Cleantech funds Financial, technological, and management
Dedicated clean
energy funds
Technological, financial, and management
General PE funds Financial, and management
General VC funds Market, and technological
See Annex 3 for the source of these findings and further interpretations thereof.
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7 Analysis of policy preferences
7.1 Overview of policies considered
This study investigated the views of the reviewed funds on the following types
of public policies relevant to the clean energy sector:
o Market-pull policies (such as feed-in tariffs and GHG emissions
trading);
o Technology-push policies (such as R&D and government grants for
technology demonstration);
o Electricity sector regulatory issues (such as net metering regulations);
and
o International policy options (such as the Kyoto Protocol)
First of all, one should recall that the large majority of respondents (80%) said
they had already investigated various climate and clean energy policies with
regard to how they impacted their clean energy investments. Therefore, their
opinions on policy are mostly informed by their existing experience in the
sector.
Investors were asked to rate policies from 1-5 with 5 being defined as “highest
preference” (other levels of preference were implied but not specifically
defined). If an investor gave a rating between 1 and 5, this was intended to
mean that there was some positive effect on their decisions to invest in clean
energy ventures from the listed policies. This can be assumed because investors
were also offered the choice of selecting “no-effect” or “don’t know”.
Market-pull policies considered (in order of their affect along the innovation
chain) were:
o Government procurement of clean energy
o Feed-in tariffs (e.g. subsidies for renewable energy market take-up)
o Residential and commercial tax credits for renewable energy
o Production tax credits (e.g. for wind)
o Technology performance standards (e.g. vehicle pollution standards)
o Renewable Portfolio Standards (RPS)
o Renewable fuel standards or targets
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o Green (renewable energy) quotas and certificate trading
o Kyoto Mechanisms (e.g. CDM, JI)
o GHG or CO2 emissions trading
o General CO2 tax or energy tax
o Reduction of fossil fuel subsidies
Technology-Push Policies investigated (in order of the impact along the
innovation chain) included:
o Doubling R&D spending for private institutions
o Doubling R&D spending for public institutions (e.g. technical
universities)
o Soft support measures (e.g. coaching for entrepreneurs, business plan
competitions)
o Incubators/technoparks
o Tax breaks for entrepreneurial firms
o Government grants or other financial support for pilot and
demonstration plants
o Grants for SMEs or communities to install equipment
o Government VC funds
o Government investment in private VC funds
o Tax breaks for clean energy investors
o Investment subsidies for entrepreneurial firms (e.g. to set up
manufacturing facilities)
The regulatory issues included:
o Siting policies (e.g. for onshore wind)
o Grid access
o Net metering regulations (for trading surplus electricity)
The purpose here was to request respondent’s level of satisfaction with current
handling of regulatory issues.
Finally, three international policy options were considered. Choices offered
included:
o Extension of and focus on the Kyoto Protocol
o Agreements to increase R&D and technology cooperation
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o Sector-by-sector energy-related agreements (e.g. subsidy reform or clean
energy targets)
o All of the above (no preference)
o No effect on our investments
o N/A or no opinion
It is worth mentioning, that although the surveys and interviews did not inquire
about a particular policy regarding nuclear energy, respondents were asked if
they believed that nuclear energy is a competing alternative that could
substantially reduce renewable energy deployment.
Before moving on, it is important to note that when analyzing market-pull and
technology-push policies, the innovation chain can be used as a basis for the
analysis. Therefore, the policies have been placed along the following radar
charts according to their approximate placement along the innovation chain.
The grouping of policies according to technology-push and market-pull policies
fit Grubb’s classification (2005) in that technology-push policies are what he
terms “market engagement programs”, and market-pull policies include both
what he terms “strategic deployment policies” and “barrier removal”.
7.2 Findings about market-pull policies
Market-pull policies were divided into two types: “market deployment
policies” such as feed-in tariffs, and “barrier removal” policies such as CO2
emissions trading schemes. Both types are policies related to technologies that
are already available to the market. However, strategic deployment policies,
which build market scale and thereby buy-down the cost of technologies, are
specifically intended to promote less mature technologies (such as solar PV
technology).
According to the innovation chain concept, and starting at noon and reading
clockwise, market deployment policies are mentioned first and policies
addressing market failures, in general, are mentioned last on the charts shown
below. The policies are best suited to stimulate less mature technologies and
then more mature technologies as you move clockwise along the radar chart.
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It is important to recall that respondents to the question about market-pull
policies were asked to respond with regard to how effective they perceived
these policies in terms of stimulating venture capital and private equity
investment in less mature clean energy technologies (e.g. solar PV).
7.2.1 Overall findings
Overall, market-pull policies received higher scores (Figure 47), when
compared to scores for technology-push policies. The lowest score was 3.0 for
CDM, JI and the highest score was 4.2 with feed-in tariffs.
CO2 tax
CO2 trading
CDM, JI
Red. FFS
3.6
3.4
3.4
3.0
certificate
trading
3.2
procurement
5
3.4
4
3
2
1
0
3.4
RFS
3.3
Feed-in tariff
4.2
RPS
3.5
3.5
3.4
Res and
comm tax
credits
PTC
Tech perf.
standards
Figure 47: Market-Pull Policies and scores (overall scores for all funds)
Note: “PTC” stands for “Production Tax Credit”, “RPS” stands for “Renewable
Portfolio Standard”, “RFS” stands for “Renewable Fuel Standard”. N = 56-60
depending on the policy.
The top four policies favored (meaning fund managers thought they
encouraged private equity investment in clean energy technology ventures best)
were:
1. Feed-in tariffs 4.2
2. Reduction of fossil fuel subsidies 3.6
3. Technology performance standards 3.5
4. Residential and commercial tax credits 3.5
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Soon after, several market-pull policies were rated on average with a 3.4:
! CO2 tax
! CO2 trading
! Renewable fuel standards
! Production tax credits
! Procurement
Those on the lower end were (rated 3.0 or slightly higher) from lowest to
highest:
1. CDM, JI 3.0
2. Green certificate trading 3.2
3. Renewable portfolio standards 3.3
It makes sense that funds would rate the CDM quite low for two reasons. First,
many of the funds were located in the United States, and most of the funds
(whether U.S.-based or not) were focused on North American markets.
Therefore, the Kyoto Protocol is less relevant to them. Second, the CDM is
about development (i.e. technology transfer) and not about technology
innovation, per say.
Green certificate trading received quite low scores as well. It must be noted that
green certificate trading is losing popularity in Europe, to feed-in tariffs. Other
explanations for this preference are explained in the literature review on
policies. In the United States, RPS is dominant. The literature review on
policies has pointed out the reasons for this preference. Major factors are risk-
related for project developers, and obviously investors in the technologies that
project developers utilize are likely to have the same views, more or less, as
their customer base.
Figure 48 and Figure 49 illustrate the dispersion of ratings for the various
market-pull policies. The frequency of 5’s and 4’s for feed-in tariffs indicates
that the high preference for this policy among all funds is shared among 80% of
the respondents.
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5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
4.5
3.4
2.4
4.2
3.3
4.9
2.2
4.6
3.5 3.4
2.2
4.7
3.5
2.4
4.6 4.6
3.3
1.9
3.4
2.3
4.4
3.2
2.0
4.3
3.0
1.7
4.6
3.4
4.7
3.4
2.2 2.1
Figure 48: Mean values and standard deviations for market-pull policies
Note: values are for all funds. N = 56-60 depending on the policy.
30
25
20
15
10
5
0
Figure 49: Dispersion of scores for all market-pull policies (for all funds)
Note: N = 56-60 depending on the policy. 0 was used to represent the
respondent’s entry of “no effect”; chart can be read with 0 on the left column
and 5 on the right column for each policy.
4.8
3.6
2.3
0
1
2
3
4
5
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6
5
4
Rating
3
2
1
0
9
17
15
10
1
27
19
7
2
1
11
9
8
3
9
19
11
7
3
1
10
18
8
7
2
1
6
18
8
6
1
4
Figure 50: Frequency of each rating for all market-pull policies (all funds)
7
20
14
5
1
3
6
19
10
12
3
1
6
7
13
9
4
2
10
16
10
11
3
13
16
13
8
4
1
9
16
11
3
3
1
Procurement
Feed-in tariff
Res and comm tax
credits
PTC
Tech perf. Standards
RPS
RFS
Certificate trading
CDM, JI
CO2 trading
CO2 tax
Red. FFS
Note: Ratings are 1-5 and “no effect” being 0. First from the left is procurement
and last on the right is reduction of fossil fuel subsidies (order along the
innovation chain). The size of the circles is proportional to the frequency.
It is interesting to note that the policies that received the highest scores were
price mechanisms (feed-in tariffs obviously being a typical price mechanism,
and subsidy reduction or tax credits, being an indirect price mechanism to
correct or affect technology market prices). Among the non-price mechanisms,
technology performance standards were highly scored. These are technology-
forcing standards which can be set at such a level that in a way force into the
market newer technologies (e.g. hybrid vehicles) as they are the best available
technology which can most economically meet a given performance target. In
this way the regulators do not choose the winning technology but the market
chooses the winning technology to meet a given performance target. This
policy can be applied to an entire fleet of vehicles sold by a given automaker,
or a given total number of power plants owned by a given firm.
Therefore, as for price mechanisms, fund managers appeared to prefer feed-in
tariffs, and as a possible complementary non-price mechanism, fund managers
liked technology performance standards. Investors may prefer feed-in tariffs
because they view price risk as important (price mechanisms reduce price risk).
Also, it is understandable that they would like performance standards that cut
off the less advanced and more polluting technologies from potential
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competition with clean advanced technologies. For example, assuming these
funds are investing in new low or super-low emission technologies, such
technologies would have to compete with lower-tech technologies under an
overall market-approach (e.g. CO2 emissions trading) or a portfolio-approach.
Users could still use more polluting technologies as long as they can offset their
effects with reductions met elsewhere. These market-based approaches are
favored by industry because they provide more flexibility in meeting targets
with a wider variety of technologies, and across a wider variety of markets, but
one glitch for investors is that technology investors cannot calculate easily how
their technologies will be taken up under such systems. This is especially a
concern under an emissions trading scheme, where market demand and supply
set the emission reduction prices, leading to price uncertainty for technology
investors.
Finally, investors were also asked after responding to the question on market-
pull policies if their responses would change if they considered more mature
clean energy technologies, instead of less mature technologies. About half of
the respondents that answered this question would not change their answers and
the other half would change their answers (with regard to how they rated
market-pull policies, such as feed-in tariffs) if they were asked to respond with
regard to more mature clean energy technologies.
7.2.2 Policy findings by fund characteristics
The higher preference for feed-in tariffs among funds is also confirmed when
fund perceptions are examined after a breakdown of findings by stage of
investment focus. Lowest ratings for feed-in tariffs come from the funds focused
on seed and start-up stages. Overall, seed and start-up funds are less positive
about the effect from market-pull policies compared to expansion or later-stage
funds.
When funds were divided into groups according to their stage of investment
focus, a few distinctive policy views emerged, although differences of opinion
by stage of investment were not as evident as expected.
138

The one market-pull policy that was most favored on average among the entire
sample of funds (e.g. feed-in tariffs) was also the most favored policy when
policies were analyzed by a few key fund characteristics. For example, it was
also favored by all stages of investment (funds with different preferences with
regard to stage of investment). However, seed and start-up focused funds were
slightly less positive about feed-in tariffs, than funds focused on the other
stages.
However, some key differences in opinion existed for the following market-
pull policies:
1. CO2 emissions trading
2. Renewable portfolio standards
3. Production tax credits (PTC)
4. CO2 tax
Funds focusing on later-stage investments clearly liked CO2 emissions trading
and production tax credits more than other types of funds. Meanwhile, funds
investing in expansion stage deals preferred feed-in tariffs first, but soon after
rated CO2 tax quite high and gave comparatively good scores to renewable
portfolio standards. On the other hand, RPS received quite low scores from
seed or start-up focused funds. CO2 tax was also clearly preferred by the
expansion stage funds, compared to other stages. Funds in earlier stage
company finance offset the higher scores that later-stage investors gave to CO2
emissions trading and production tax credits. This explains why feed-in tariffs
received relatively much higher scores than these policies, despite the fact that
later-stage investors liked them just about as much as feed-in tariffs.
Later-stage investors also find effective the production tax credit (PTC) slightly
more than feed-in tariffs, but again seed and start-up stage investors rated PTC
low, offsetting the average score for this policy option.
Overall, one can understand why seed and start-up funds are less concerned by
market-pull policies than expansion or later stage funds. Expansion and later
stage funds are closer to technology deployment and seed and start-up funds
are involved mostly in technology development and early commercialization
challenge as opposed to fully commercial technology market challenges.
Therefore, expansion stage and later-stage focused-funds are probably first
139

more informed about market-pull policies out of either necessity or pure
exposure to their portfolio companies which face the policy-driven market on a
daily basis.
Meanwhile, CO2 emissions trading is not preferred as much by seed and start-
up funds, while later-stage funds clearly prefer CO2 trading with the
production tax credits. Again, later-stage funds who are more exposed to
market-mechanisms find more effective CO2 emissions trading on a regular
basis and their technologies are more mature which explains why they favor
such an economy-wide system intended to internalize environmental
externalities and make their lower-tech low emission technologies more on par
with conventional energy technologies. Finally, later-stage funds may be
associated with large financial institutions that have an interest in any trading
scheme, which allows them to take advantage of their size to stay competitive
in an uncertain market system, and allows them to take advantage of their
commodity trading expertise and resources. For example, firms with hedge
funds may find business opportunities in trading emissions (which require
similar skills to trading commodities like oil and gas). Certain investment
banks may also have such an interest in the business of carbon finance, and
may also be more informed about the benefits of CO2 emissions trading with
regard to their other investments in more traditional sectors, as well.
The fact that seed and start-up focused funds rated all policies slightly lower
than funds focused on other stages makes sense given that smaller firms or
funds do not have the resources or direct necessity to even become informed
about how market-pull policies affect (or should affect) their investment
decisions. Indeed, they are too early in the innovation chain, so market-pull
policies which impact the later parts of the innovation chain, as discussed
previously, probably do not affect their investment decisions as much as
market-pull policies appear to affect the investment decisions of funds focused
on expansion and later-stage company finance. Expansion stage-focused funds
are in the middle-ground, having more exposure to market-pull policies, but as
the literature review has shown they are more likely to be concerned with
market deployment policies, than barrier reduction policies. However, while
they rated feed-in tariffs quite high (a market deployment policy), they also
rated CO2 tax quite high, showing a general preference for price mechanisms
140

that are less exposed to market price uncertainty. Finally, later-stage investors
(most likely being larger firms) may therefore have more resources and ulterior
business interests relevant to market-based mechanisms with a certain level of
price uncertainty, allowing them a competitive advantage given their links to
commodity trading, etc. and thus explaining their preference for CO2 emissions
trading.
CO2!trading
CO2!tax
CDM,!JI
Red.!FFS
certificate!
trading
procurement!
5.0
4.0
3.0
2.0
1.0
0.0
RFS
Feed"in!tariff
RPS
Res!and!
comm!tax!
credits
PTC
Tech!perf.!
standards
Seed!and!Start"up
Expansion
Later!stages
All!stages
Figure 51: Mean scores for market-pull policies, by stage of investment focus
Note: 44% of all funds invested in expansion stages (recalling this includes
some start-up finance), while 28% of the funds invested in seed capital and
start-up stages only. 12% invested in late-stage deals and 16% invested in all
stages. N = 57.
In conclusion, views mostly diverge by investment stage for PTC, RPS, and
CO2 trading, and also but to a lesser extent for CO2 tax, RFS and CDM/JI.
Views are very similar among all investment stages for government
procurement, technology performance standards, and residential and
commercial tax credits.
By fund type, results show that cleantech funds and dedicated clean energy
funds have similar views about market-pull policies, while general private
equity and general VC funds have similar views with regard to policies that
141

affect earlier parts of the innovation chain. In addition, overall, general funds
are clearly less positive about the effect of market-pull policies than cleantech
funds or dedicated clean energy funds
Figure 52 shows that there are indeed some differences with regard to policy
perception among different types of funds. Most notably, cleantech funds and
dedicated clean energy funds have similar views in that they rate many market-
deployment policies higher than both types of general funds. General funds
then tend to have quite divergent views for policies that affect the later stages
of the innovation chain.
For example, with regard to renewable portfolio standards, general VC and
general PE funds both respond more negatively, when CTF and DCE funds
respond more positively, and the same is true for renewable fuel standards.
However, general funds diverge in views with regard to CO2 emissions trading.
More specifically, general PE funds favor CO2 emissions trading with CO2 tax
and reduction of fossil fuel subsidies (indeed, the three major economy-wide
barrier reduction policies), but general VC funds tend to rate these policies
much lower in comparison (at 3 or lower than 3). Overall, general funds are
less positive about the effect of market-pull policies than cleantech funds or
dedicated clean energy funds. This is particularly true for RPS, RFS, certificate
trading and feed-in tariffs. Supporting the findings in the previous section about
stage of investment, general PE funds’ preference for CO2 trading makes sense.
It is not surprising to find similar results here, because several general PE funds
also tend to invest more in the later-stages of company finance. Indeed, private
equity is defined as later-stage company finance.
142

CO2 tax
CO2 trading
CDM, JI
Red. FFS
certificate
trading
procurement
5
4
3
2
1
0
RFS
Feed-in tariff
RPS
Res and
comm tax
credits
PTC
Tech perf.
standards
Figure 52: Mean scores for market-pull policies, by type of fund
CTF
DCE
General PE fund
General VC
fund
Note: Cleantech funds make up 31% of the sample, dedicated clean energy
funds make up 23%, general VC funds are the next largest share of funds at
22% and finally general PE funds are 14% of the total sample. N =
approximately 51 for each policy.
Overall, there was not a large dispersion among views by fund size, but a few
policies were viewed differently among categories of funds by fund size
including: government procurement, CO2 tax, RPS, and technology
performance standards.
Overall, there was not a lot of consistency among views by fund size. For
example, large clean energy funds did not consistently find effective all the
market-deployment policy options. Some preferences can be explained. For
example, RPS was disliked relative to other fund sizes by the smallest fund size
category (0-10M Euros), but this makes sense. RPS also received quite low
scores from seed or start-up focused funds. RPS policies favor later-stage
renewable energy projects. Understandably a larger fund size which is likely to
invest more in expansion stage company finance will not benefit much from
government procurement. Meanwhile, the fund size category which favored
feed-in tariffs the most was the 250-500M funding category. This makes sense
given that they have the highest amount of money invested in clean energy, and
are likely to be even more sensitive to price risk in the sector, than funds with
143

lower financial commitments to clean energy. In addition, there was a pattern
with regard to technology performance standards. Smaller-sized funds were
more enthusiastic about performance standards, than larger-sized funds.
Looking at the interviews for some guidance on how such fund managers feel
about this option, one investor noted about this policy option the following, “If
they will lead to forcing technology adoption, then it could be good”. Probably
funds managing smaller amounts of money are also involved in earlier-stage
investments and therefore have a leaning for policies which tend to force
technology adoption than funds which invest in companies with technologies
which are later-stage and have less trouble with technology adoption.
CO2 trading
CO2 tax
CDM, JI
Red. FFS
certificate
trading
procurement
5
4
3
2
1
0
RFS
Feed-in tariff
RPS
Res and
comm tax
credits
PTC
Tech perf.
standards
Figure 53: Mean scores for market-pull policies, by fund size
0-10M
10-100M
100-250M
250-500M
Note: Euros are used for fund size; Small funds represent 27% of respondents,
medium-sized funds 31%, large funds 30% and very large funds 12%.) The
majority of clean energy funds (about 60%) were in the range of 0-100M Euros
of funding for clean energy technology ventures78. The next largest category
for fund size was in the range of 100-250M Euros (30%). N = 34 for CO2
emissions trading, N = 32 for FiTs, etc. (N varies by policy and is low here
because of a lack of full data on fund size).
However, fund size may not be the most relevant characteristic to turn to in
order to characterize policy preferences of fund managers, but clean energy
78 The number of small funds represents 27%, medium-sized funds 31% (58% were of a size lower than
100M Euros), large funds 30% and very large funds 12%.
144

fund size compared to firm size (total VC/PE funding of the firm) may be more
relevant. This measure would at least represent how important the clean energy
sector is in terms of financial risk (and therefore potentially policy, in general)
to the entire firm. In Figure 54, one can see that the smallest fund sizes (0-5M
Euros) for clean energy are mostly within firms of very small size (0-10M
Euros), with a few exceptions (one being a very large sized firm). The next
biggest fund size category is supported by firms of a slightly larger firm size
overall (35-75M Euros). The next category of 100-250M Euros for clean
energy VC/PE finance have firm sizes of about 175M Euros which are almost
equivalent to their total clean energy funding (meaning the financial risks
relevant to the clean energy sector are highly important for this category of
investors as their entire business is quite concentrated in the sector). The largest
clean energy fund sizes were housed in firms of very large size in two of the
four cases (implying that the risks relevant to investment in innovative clean
energy technologies is lower for their firms overall).
Million!Euros
4000
3500
3000
2500
2000
1500
1000
500
0
0"5M 10"20M 100"250M 250"500M
Series1 5 75 175 375
Series2 5 75 750 375
Series3 5 750 175 3750
Series4 2500 75 175 1750
Series5 10 35 175
Series6 5 35 1750
Series7 250 35 175
Series8 250 75 750
Series9 5 75 175
Series10 175 175
Figure 54: Firm sizes per fund size category
Note: N = 34.
The findings on policy preferences of funds grouped by core investors indicate
that funds supported primarily by banks tend to rate ‘barrier removal’ policies
145

most favorably, and much more favorably than other core investor types.
Overall, corporate investors rate market-pull policies lower than other types of
core investors.
Types of core investors in clean energy funds are another way to study
differences among funds. Sometimes core investors are a mixed variety
(especially for independent firms), however occasionally funds receive funding
primarily from corporations, banks or very wealthy families or individuals,
which is called “private” investors below.
Investors may be indirectly informed about how policy impacts their
investments via all types of actors (core investors, portfolio companies 79 and
other information sources or other investors 80 ) as shown in Figure 55,.
Innovation!Chain
Investment!Cycle
Core
Investors
Fund!Managers!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Information!Sources
Other!Investors
Portfolio!Companies
PUBLIC!POLICY!ENVIRONMENT
e.g.!
Internal!staff!intelligence,!
final!consumers,!
specialized!industry!
reports,!news!media,!
institutional!investors,
investment!banking!
reports,!etc.
Figure 55: The influence of a variety of stakeholders on fund managers’ views
about public policies
Entrepreneurs (portfolio companies) impact some investors more than others.
Others are probably more impacted by their core investors’ views about policy.
For example, corporate-backed funds or funds, which are co-funded by
79
Other potential important sources of information to VCs are trusted entrepreneurs with a track
record in a given area.
80
VCs tend to follow other VCs with regard to what is the investment area of fashion at a given time,
as discussed earlier in the second section of the literature review in this thesis.
146

corporations, may have a specific view about policy because of the
corporations’ previous experiences with given policies. In addition, core
investors influence fund managers by setting criteria for their investments, and
indicating what their investment preferences are, while some investors stay
farther removed from the fund managers’ domain.
In fact, funds supported primarily by banks tended to rate most favorably all
market mechanisms on the barrier removal side of the innovation chain (CO2
trading CO2 tax, and CDM/JI receive high scores). But bank-supported funds
also liked feed-in tariffs. Corporate-financed fund managers rated CDM/JI very
low compared to all other policies, by sharp contrast with banks, and also rated
RPS considerably low.
CO2 tax
CO2 trading
CDM, JI
Red. FFS
certificate trading
procurement
5
4
3
2
1
0
RFS
Feed-in tariff
RPS
Res and comm tax
credits
PTC
Tech perf. standards
Bank
Corporate
Private
Mixed
Figure 56: Mean scores for market pull policies, by type of investor of
prevalence in each fund (LPs)
Note: Mixed investors made up 36%, primarily banks made up 11%, primarily
private investors made up 22%, primarily corporate investors made up 22%,
government 5% and pension funds 4%. In the chart, pension funds were left
out, as there were only 2 funds with pension funds as their primary investors. N
= approximately 52 depending on the policy.
147

CO2 trading
CO2 tax
CDM, JI
Red. FFS
certificate
trading
procurement
5
4
3
2
1
0
RFS
Feed-in tariff
RPS
Figure 57: Market-pull policy views by type of firm
Res and
comm tax
credits
PTC
Tech perf.
standards
Bank &
SubPE
CVC
Gov.
Indep.
Note: Independent firms make up 61%, banks and subsidiaries of private equity
firms make up 19%, corporate venture capital (CVC) firms make up 11% and
government makes up 9%. N = 51-55 depending on policy.
Medium-sized private equity firm sizes preferred feed-in tariffs most.
Firms with a variety of sizes backed funds. The feed-in tariffs were liked best
by firms in the 50-100M Euros category, and next the 100-250M Euros
category (these are the small to medium sized firms). The largest and the
smallest firm sizes found them less effective. This can be explained in the
following way. The largest firms are likely to have the resources required to
deal with issues like high capital expenditure of clean energy technologies, or
they are investing in more mature technologies like wind energy, therefore they
probably believe that they do not need the support of feed-in tariffs. The
smallest firms, on the other side of the spectrum probably do not have the
resources to even become informed about feed-in tariffs or they do not believe
they need them because they believe they are investing in “breakthrough”
148

technologies that do not require government support. This was the view of one
fund manager in this smallest firm size category, which was interviewed. This
fund manager outlined that the only risk they perceived with regard to the clean
energy sector was technology-related risk.
CO2 trading
CO2 tax
CDM, JI
Red. FFS
certificate
trading
procurement
5.0
4.0
3.0
2.0
1.0
0.0
RFS
Feed-in tariff
RPS
Res and
comm tax
credits
PTC
Tech perf.
standards
Figure 58: Mean scores for market-pull policies, by firm size
Note: N = approximate 45 (exact N differs for each policy)
0-50M
(very
small
size)
50M-
100M
(small
size)
100M-
250M
(medium
size)
250M-1B
(large
size)
1B-5B
(very
large size)
Internal staff intelligence is a key information source determining policy views.
Information sources such as institutional investors have been shown in the data
to be important to the largest firm sizes, and smaller firm sizes naturally depend
on other information sources. However, the information sources which appear
to be more associated with differences in policy views are: staff intelligence
and advisers on technology. For example, one can also see that among funds
that did not find feed-in tariffs effective (rated 0-3), they tended to score the
importance of internal staff intelligence much lower than funds, which reacted
more positively to feed-in tariffs.
149

Other
specialised
industry reports
Investment
banking reports
News media
Financial
consultants
Institutional
Investors
5
4
3
2
1
0
Internal staff
intelligence
Other investors
Advisers on
technology
Corporate
buyers
Final consumers
Do like FiTs
Don't like FiTs
Figure 59: Information sources for funds with minority policy views among the
sample
Note: minority policy views are 5 for CO2 emissions trading (11 funds) or
ratings of 0-2 for feed-in tariffs (4 funds): “FiTs” stands for “Feed-in Tariffs”.
N = approximately 37 (depends on information source)
Overall, European-focused funds were more positive about the impact of
market-pull policies than North American focused funds.
It is interesting to note that funds with a focus on Europe were slightly more
positive about the impact of feed-in tariffs, while funds’ views about CO2
emissions trading were the same across European-focused and North-American
focused funds. European-focused funds were also more positive about: CO2 tax,
CDM/JI, government procurement and technology performance standards, than
North American focused funds. North American focused funds rated RPS more
positively than European-focused funds. This is the single policy that North
American-focused funds rate higher than European-focused funds, of course
because RPS is not implemented as much (or is not called as such) in Europe.
150

But overall, European-focused funds rated market-pull policies higher than
North American focused funds.
However, the difference of policy views by country of management (location)
was not as great as one would expect, especially with regard to CO2 trading
given that the Kyoto Protocol is not yet ratified in the United States.
Furthermore, Feed-in tariffs were equally liked by U.S.-based funds as by
European-based funds. Of notable difference were technology performance
standards that were not as well perceived by U.S.-based funds as European-
based funds and government procurement. Meanwhile, U.S.-based funds liked
the production tax credit slightly more than the other fund locations.
CO2 trading
CO2 tax
CDM, JI
Red. FFS
certificate
trading
procurement
5
4
3
2
1
0
RFS
Feed-in tariff
RPS
Res and
comm tax
credits
PTC
Tech perf.
standards
Europe
North
America
Figure 60: Mean scores for market-pull policy views, by region-focus
Note: N = 50.
There is not much change in policy views among investors that meet more
frequently with Policy-makers.
This finding is contrary to what had been expected. However, it shows that the
exposure to Policy-makers does not significantly change the funds’ policy
views in one way or another at least on aggregate levels.
151

Funds with more experience in clean energy investment meet less frequently
with Policy-makers.
However, funds that invested in clean energy previous to year 2000 are meeting
less often with Policy-makers than funds that are new to the clean energy sector,
as can be seen in Figure 61. This may imply that funds new to the sector are
aware that they need to keep informed of changes in policy by directly meeting
with Policy-makers, and funds which have been in the business for a while may
have already developed established means for obtaining information on policies.
Then again, meeting with Policy-makers is an active way of managing
regulatory risk. Without looking into other details, one would assume that
funds with experience would pursue such an active way of managing regulatory
risk as well. Perhaps funds new to the sector are investing larger amounts of
money and have more to loose from regulatory risk.
4.0
3.0
2.0
1.0
0.0
Partners w PMs Staff w PMs Partners w Co Staff w Co
Activity level of funds investing in CE pre-2000
Activity levels of all funds (average score)
Figure 61: Exposure to Policy-makers and companies for funds with experience,
compared to funds with less experience
Note: the frequency of meetings was translated into levels 1-5 to develop
statistics. N = 32 for policy makers, N = 34 for companies.
Looking at other characteristics of funds with experience 81 , one can begin to
understand where the above results are coming from. They are usually of a
fund size between 50-250M Euros, with a North-American focus, on average,
and a relatively high number of corporate investors in the funds. This means
81 At least more than 7 years of experience investing in clean energy technology ventures (measured by
year of first investment in clean energy VC/PE).
152

they may be able to obtain information on regulations via their corporate
investors and having a significant link to large corporations in the energy sector,
they may not be willing to reveal more information about their links to Policy-
makers, which is likely to be more complex than in other cases. They are
generally based in the United States, and have investment teams with a
significant proportion of energy backgrounds. Being based in the United States
may have an impact on their exposure to Policy-makers. Also, if they have
sufficient energy backgrounds, then they may already hold access to regular
information about energy policy. However, perhaps more importantly, the basic
investment preferences of these funds were: seed or start-up finance, solar and
biomass energy investments, and with 6 years time to exit. Given that they are
generally seed and start-up funds, they may not need to meet with Policy-
makers as much as funds involved in later-stage deals which have more to
loose on individual large investments from particular regulatory risks they face
by given policy environments. Perceived drivers, key investment criteria, and
perceived hindering factors for these funds were: competitive advantage and
security of energy supply (for drivers), management team capabilities (first
investment criteria) and the hindering factor they perceived to be of greatest
importance to the further growth in the space was long lead time for clean
energy technologies. Finally, their main policy preferences were: feed-in
tariffs, government demonstration grants and sector-by-sector based
international agreements.
The climate change driver is logically linked to a preference for climate
policies, and trading schemes
In terms of drivers, funds that cited that climate change was the most important
driver liked feed-in tariffs and CO2 emissions trading, CO2 tax, certificate
trading and RPS. Where climate change was mentioned as the least important
driver to stimulating their interest in the sector, CDM/JI and green certificate
trading received the lowest scores, as can be expected. Perceived important
drivers may originate from the firm’s original motivation to enter the clean
energy sector or it may be an opinion formed over several years of the fund
manager’s experience in the sector. Finally, it generally influences the fund
manager’s view about policies.
153

CO2 trading
CDM, JI
certificate
trading
CO2 tax
RFS
procurement
5
4
3
2
1
0
RPS
Climate Change 1st Driver
Climate Change last driver
Feed-in tariff
Res and
comm tax …
PTC
Tech perf.
standards
Figure 62: Market-Pull Policy views by climate change as a key driver or not
Note: N = 54.
Finally, a preference for feed-in tariffs appears to be linked to the hindering
factor about lack of consistent government commitment to clean energy, based
primarily on a qualitative analysis of the interviews.
In addition, funds which did not find feed-in tariffs effective (a minority of
funds 82 ) had not perceived the following hindering factors as important to the
clean energy VC/PE investment community: institutional investor interest, lack
of consistent government commitment to clean energy, lack of deal flow, lack
of track record, and to some extent long lead time. Compared to funds that
liked feed-in tariffs, they rated all hindering factors as less important, except
lack of competent venture managers. Clearly, funds that do not want much
government involvement in the market believe the market is just not mature
yet, but that it will be able to mature on its own.
82 The number of funds that liked feed-in tariffs (rated 4 or 5) was 47. The number of funds that did not
like feed-in tariffs that much (rated 0-3) was 11. However, the number of funds among these categories
that answered the question on hindering factors was 22 for the first category and 6 for the second.
154

Among those that liked CO2 trading, market power of incumbent firms was
perceived as more important than for funds that did not rate CO2 trading as
high 83 . This makes sense as those that found CO2 trading as effective were also
larger firms that probably invest in later-stages of the innovation chain and face
the problem of market power of incumbent energy firms more often than those
investing earlier in the innovation chain. Meanwhile, lack of track record was
the most important hindering factor, on average, for funds that also liked CO2
trading. They are clearly concerned about the maturity of the sector, compared
to other sectors, and this makes sense if they are large firms investing in a
variety of sectors.
7.2.3 Detailed analysis of views on Feed-in Tariffs
The majority of funds in the entire study sample thought that feed-in tariffs
were effective 84 , rating them with a 4 or a 5. From the previous literature
review on policies and risks in the clean energy sector, this empirical data
supports the major proposition that feed-in tariffs are among the most effective
policy options in terms of stimulating investment by VC or private equity fund
managers into companies supplying less mature clean energy technology.
For example, one Swiss-based fund manager showed a preference for European
policies and in particular feed-in tariffs when he responded, “Germany, the UK,
and sometimes the U.S. have good sized markets and good policy support, so
that is where we are looking…I prefer European power policies for renewable
energy like feed-in tariffs…” Even other types of investors interviewed for this
study preferred feed-in tariffs. For example, one European project financier
responded, “The most important policy is the feed-in tariff in Germany and
Spain. I am not a big fan of the ROCs scheme. The ROCs system is not
predictable, so it should not be repeated. Tax credits are not the way either.
…Production tax credits pose a barrier for European investors in the sector in
83 There was an even distribution among funds that rated CO2 trading high and those that did not. 27
rated the policy high, while 25 rated it low. Among those that liked CO2 trading high, 16 responded to
the hindering factors question, while 18 funds that did not rate CO2 trading high also responded to the
hindering factors question.
84 In this section, ”effective” refers to when a group of fund managers interviewed and surveyed
believed the given policy was at least above average (rated 4 or 5) effective in stimulating VC/PE fund
investors (fund managers) interest to invest in less mature clean energy technology portfolio companies.
155

the U.S.; first you need to use the tax credits, and then in addition, there is the
uncertainty in the regulation…” The venture capital division of a large
institutional investor based in Europe also agreed, responding: “Feed-in tariffs
are the best perceived policy because they set a steady cash flow and for us this
is important…CO2 related policies are like an incentive and down the line it
may impact us, but it is an indirect benefit…” One key U.S.-based VC fund
manager mirrored this comment in his views on what drives the institutional
investment community to invest in clean energy funds: “Policy risk is a barrier
to more people getting into the sector. As long as subsidies are there, there will
be enough interest from institutional investors because you have the portfolio
effect and take up the risk and there is a visibility of subsidies for the next 10
years. It depends on which jurisdiction you are buying in. In Germany, you
would look at the portfolio and see exactly how much income you get from
these assets for the next 10 years, as an institutional investor….Now there is
even a risk of a bubble as clean energy is becoming in-fashion. But the
generalist investors will keep a bit away (banks and fund management
investors).” Another U.S.-based fund manager said, “the PV rebate policy in
Germany - guaranteed pricing - works well because it is significantly higher
than utility rates, so with a rebate on every kWh, then the rebate system can get
a certain installed base and this is a sensible thing because with a reduction of
the subsidy, one should be getting the price down.”
Then again, policy is not everything. One corporate venture capital fund
manager makes the point, “It always helps if there is a subsidy, but if one of the
company’s people or co-investors is hot on a deal, policy would not have such
a big impact. We go with the base case, and assume that regulation is not
playing in our favor, but most likely it will be on the upside”. However, many
of the funds that gave high scores to feed-in tariffs, also gave high scores to
other renewable energy support policies. For example, a major European VC
fund manager that rated FiTs with a 5 (highest score) also rated almost all the
other market-pull policies with a 5, except for residential and commercial tax
credits for renewable energy. This fund manager stated, “Policies are needed
that accelerate the adoption (rather than the development) of clean technology.
Anything that helps utilities, industry and entrepreneurs to reduce the risk and
accelerate the adoption of clean technology is good like taking a pro-active
approach to developing renewable energy opportunities, or speeding up the
156

planning permission process, making grid connections for renewable energy
plants cheaper and easier to access, etc.” Another fund manager was
particularly fervent about the need for strong market-pull policies, saying:
“People have to be forced to change. We need long-term policy to de-risk the
project. Dictatorial regimes need to be put in place. Encouraging R&D is too
long-term for investors 85 ”.
Number of funds
50
40
30
20
10
0
47
Like FiTs (rated 4-5) Don't like FiTs (rated 3 or
lower)
Figure 63: Number of funds which found feed-in tariffs effective, or not
Note: N = 57.
While most funds in the sample rated feed-in tariffs high (4 or 5), 10 of the 60
funds interviewed and surveyed rated feed-in tariffs 3 or lower (16.6% of the
funds in the sample). A few quotes from these investors can be scrutinized to
try to understand their thinking. A few negative comments on feed-in tariffs
from investors that still rated FiTs with a score of 4, are included below.
To begin with, some investors may have rated policies low not because they are
not effective at deploying clean energy technologies and helping to attract
investment, but because they view such policies, in general, as not that
important to driving the sector on the whole. A few comments along this line of
thinking are: “Price of oil is more important. Policy plays into the equation,
but you can’t invest where there are government subsidies because it is not
necessarily sustainable. We need more of a free market approach. We need to
strip out the subsidies, because we are looking for a long-term approach”.
85 By “long-term” here he meant that it takes too long to stimulate change in the energy market with
R&D encouragement policies.
10
157

Another noted: “Policy does matter, but it provides only a slight advantage.
We have to be convinced that there is a market and (our market analysis)
includes considering regulations. In general, policy would affect our decision
to invest or not in a deal, but only a slight percent. We don’t see policy’s
impact on the small start-up companies yet.”
Others have a more negative perception of policy (seeing only the downsides
and not the upsides of regulations). For example one fund commented, “Policy
could threaten to destroy one of our clean-tech investments, although our
technology does not have environmental impacts, because sometimes Policy-
makers are not well informed…” This CVC fund manager tended to prefer
incentives to set of manufacturing facilities or grants “which allow companies
to write-off all R&D expenses and get a refund on a quarterly basis”. They
also commented, “the biggest thing the government can do is to continue
funding of the national labs; that is where a lot of innovative work goes on for
decades before it moves towards commercialization”. More generally, he
commented: “Policy did drive investments into this area, but a lot of it is not
based on sound fundamentals. We probably don’t need so many policies – and
we don’t need such stringent policies. I would let the market lead itself and if
you fund things let the decisions be in the hands of scientists and business
people and not in the hands of politicians”. However, another VC fund
manager which noted “Government should not choose winners – simply
establish incentives and let the market sort it out” happened to like FiTs, as did
another VC fund manager which noted a similar preference stating, “Policies
should be market-driven and most efficient”. The same was true for a major
Swiss bank that said, “Our thesis is that you need deals that are economic on
their own.” Another fund manager that avoided to rate policies 1-5, but
preferred to provide his general view on policy, noted: “We invest assuming
there are no government subsidies at all. What government can give can be
taken away. So, we never want to invest in anything that depends on a tax
credit or a subsidy. Having said that, if there is a tax credit available, we will
take it. The best subsidy helps get the market started and then goes away. So,
depending on the particular company we are talking about, or subsidy, we
would hope to see a 3-5 years sun-setting of that credit, and then it has to stand
on its own feet…As for regulatory issues, it is comical if you go to every
different state and it they have different problems. Standards are needed.
158

Dealing with local government bureaucracies can make you grow old. I prefer
R&D spending to all of the mentioned policies. Money in the hands of
entrepreneurs gets things done and policies distort markets, but sometimes they
go in your favor; however I prefer to look for businesses that do not need that
support”. Other more general policy-related comments by fund managers
included, “Policies should have a foundation in good market economics”. This
particular fund manager found, for example, the demand response in renewable
portfolio standards (RPS) effective:“RPS have been an opening of the door for
this work, with all the problems of it being due to it being a work in progress,
and there is no standard approach on what a REC is”, as well as production
tax credits (PTC), “with the caveat being the on again off again aspect”, the
system benefit charges at state level (in the U.S.) which, “have been very
important because it is a source of flexible funding for each state to try
different things”. However, he noted that in the U.S., the problem is that “how
you define clean energy requirements vary from state to state and there are
problems with trading across state lines”.
As for feed-in tariffs, a variety of characteristics of funds differ, on average,
among funds that found feed-in tariffs effective and those that don’t. This
section will explore these characteristics in an attempt to understand better why
such funds view FiTs in a more negative way, while the literature review in this
thesis shows them to be the most effective policy for encouraging deployment
of clean energy technologies. They are also viewed by many as being the
policy option which can lead most to the perception of certainty among
investors, reducing risks relevant to investors in less mature clean energy
technologies. Meanwhile, funds that were focused on the seed capital and start-
up funding stages more frequently rated feed-in tariffs less high.
It is interesting to note that besides stage of investment, other fund
characteristics like fund size, firm size, fund type and geographical focus
appeared to also correspond with different funds’ views on feed-in tariffs.
Table 12 shows these characteristics, on average.
For example, those that found feed-in tariffs effective were widely distributed
in terms of geographical focus among Europe, North America and other
regions. However, those that did not find feed-in tariffs effective were mostly
159

focused on the North American clean energy market. As for fund types, all
types of funds found feed-in tariffs effective, but the majority of fund types that
did not find feed-in tariffs effective were general VC or private equity funds
with some clean energy investments (7 funds out of 10, only one of which was
significantly investing in clean energy private equity, but not venture capital).
Also, the majority of funds that did not find feed-in tariffs effective were based
in the United States (8 funds out of 10), while only 18 of the 47 funds that
found feed-in tariffs effective were based in the United States. Therefore, one
could wonder if some of the U.S.-based funds did not find feed-in tariffs
effective so much because there are no feed-in tariffs in the United States yet
(feed-in tariffs are applied mostly in Europe at the moment). They, therefore,
have less experience with this policy, assuming they focus on North American
markets, and if they are a generalist fund they may not have heard much about
how this policy works in the first place. However, not all generalist investors
have this view.
One generalist venture capital fund which invests in a wide variety of sectors
such as biotech, stated the following view on feed-in tariffs which highlights
that the investor thinks about how the policy addresses both price risk and
volume risk as explained in the literature review: “Long term feed-in tariffs are
good, like in the German system, where the investors are certain that they will
get a return on their investment – if the technology works and is superior to
competing technologies. You also have the right to sell back electricity you
produce, and the guaranteed fixed price is a money machine for a short period
of time. It is good for the cleantech industry because they build up the home
market and expertise. Most of the investors we see look at the technologies.
Generally they are reluctant to base a decision on a policy, so when
guaranteed a price for 20 years, that is ok. I don’t think anybody feels
comfortable with policy-driven markets, but some investors might get in
anyway. We have pension funds in Denmark that to a certain extent live with
politicians so if politicians say they should invest some part in cleantech, then
the funding levels will increase…but this is not coming from investors’
rationale. Unless the policy is really really stable, policy remains more of an
indirect influence on investment levels.”
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Table 12: Basic fund characteristics that correspond to views on feed-in tariffs
Find FiTs
effective
Don’t find
FiTs effective
Fund
Size
Firm
Size
Fund Type Geographical
Location
107M 464 Various All All
12M 1042 General
funds
mostly
Geographical
focus
U.S. mostly NA mostly
Furthermore, those that found feed-in tariffs effective had a larger clean energy
funding size overall (as well as a larger portion of clean energy funding
compared to total VC/PE funding by the firm), which is what had been
expected. Meanwhile, the funds that did not find feed-in tariffs effective as
much tended to have a larger firm size than funds that found feed-in tariffs
effective.
1200
1000
800
600
400
200
0
F iT s e ffe ctive F iT s no t so effective
C E fund ing No n-C E fund ing
Figure 64: Level of clean energy funding compared to total VC/PE funding for
funds grouped by rating of FiTs
Note: N = 32.
Also the proportion between clean energy funding and total VC/PE funding of
the firm was much larger for those that found feed-in tariffs effective. The
overall figures (average fund and firm sizes) show that among those that did
not find feed-in tariffs effective, they spent only 1% of their total VC/PE funds
161

on clean energy technology companies, while among firms that found feed-in
tariffs effective, 23% of the firm’s total VC/PE funding was spent on clean
energy technology companies.
It makes sense that funds which are more concentrated on clean energy
investments will know more about what types of clean energy policies are most
effective at stimulating investment interest in the sector, especially if they have
extensive experience in the expansion stages of companies requiring clean
energy finance. It also makes some sense that funds that are based within larger
firms may have more information on how they can benefit across the board
from CO2 trading and other climate change policies or otherwise have an
advantage relative to smaller-sized firms as a player within an economy-wide
policy such as CO2 emissions trading. Therefore, they may view this policy as
similarly beneficial for their circumstances. Looking at the empirical data,
indeed funds that rated CO2 trading with a 4 or 5 also had larger total firm size
(on average). So, size of the total VC/PE funding of a firm (firm size) is one
factor. Another is clean energy sector focus.
Although clean energy funding levels were similar in both categories (Figure
65), funds that found CO2 trading effective (and those which did not find FiTs
effective) also had a smaller portion of clean energy funding compared to total
VC/PE funding. Perhaps they are investing in more traditional energy
investments that may also benefit from CO2 emissions trading, assuming they
reduce energy consumption, or the like. Another possible explanation is that
they are investing more in later-stage deals that would involve already fully
commercial clean energy technologies that already progressed along their
learning curves. Also, larger firms are likely to be more exposed to consultants
in the climate change and energy business that focus on the opportunities of the
carbon markets.
162

900
800
700
600
500
400
300
200
100
0
C O 2 trading effective C O 2 trad ing no t so e ffe ctive
C E funding No n C E fund ing
Figure 65: Average firm size for funds which find CO2 emission trading
effective (or not)
Note: Average firm size is defined as the total VC and PE funding of the firm
in millions of Euros. “Find effective” is defined as rated 4 or 5, “not” is defined
as rated 3 or less. N = 46 for firm size and 38 for fund size.
One might also argue that larger firms which manage large VC or private
equity funds for a variety of sectors in the economy will first naturally have a
more mainstream strategy to investment or otherwise a more mature investment
strategy. This influence of the larger firm is likely to affect the way the clean
energy fund managers view the clean energy market and various policy options.
Also, certain policies may be more suitable in terms of attracting the interest of
larger firms to invest in the clean energy sector. One consultant to large clean
energy funds and entrepreneurs in the field which was interviewed for this
study provided the following interesting perspective on how well-established
firms (e.g. corporate investors) view policy drivers and about the importance of
signal intent, long-term policy direction, and consistency which is expected
from the EU Emission Trading Scheme (ETS) and the Kyoto Protocol:
“How policy impacts investments depends on the attitude of the
investors. Investors in on-shore wind turbine technology are very
different from those in biofuels or fuel cells today. With wind, you get
corporates, which are well-established businesses with track records.
Whereas a lot of investments in emerging sectors are really option plays,
163

so their regulatory risk analysis is also far less robust. … In the past,
people got their fingers burned investing in things exposed to
government policy, and it was short-term policy…Now people draw
distinctions from things driving markets as a whole, and specific
technology-focused policies like the on and off again approach of the
U.S. (PTC) for wind energy deployment. Whereas, nowadays, policies
have a longer time horizon and are applied more broadly. As for the
ETS, people would look at emissions trading and Kyoto and say, ‘yes,
that will be a long-term requirement, but near-term policy, certainly in
the UK, has defined the degree to which carbon credits are scarce and
affect its price…So they (investors) will ask if the overall direction of
policy is good, and short-term affects of policy are not always right,
because policy makers are not able to have all information, so they are
aware of this. Risks in regulating emerging sectors, just like risks of
investing in the sector, are high so people realize this while policy-
makers will mostly get it right for the mature sectors. The key thing
about policy to stimulate their interest, however, is signal intent and
consistency.”
Now looking at the empirical data collected here, indeed, funds in the study’s
sample which rated feed-in tariffs low, rated CO2 emissions trading at least at
the same level, and rated CO2 tax even higher, but it also appears that they
were more agnostic to policy in general. Among the funds which did not find
feed-in tariffs effective, they also rated low all other market-pull policies
compared to the group of investors that found FiTs effective, except they
tended to find reduction of fossil fuel subsidies effective about as much as the
other group. A possible explanation for this is that these fund managers do not
find policy intervention (including subsidies) effective. They believe that
technology must be competitive on a fair basis. One can also easily note from
the data that they also had a relatively higher preference for market-barrier
reduction policies or market-based instruments, as compared to the instruments
intended for the earlier-stages along the technological innovation chain
(supported commercial or pre-commercial stages). A further look into what
characteristics belong to funds that gave high or low scores to CO2 emissions
trading will be provided in the next section.
164

Of interest, also, is that these funds tended to rate technology performance
standards relatively high as well, compared to other non-barrier reduction
market-pull policies. Technology performance standards are therefore their
favorite choice among the policy options for the supported commercial stages.
This is quite an interesting finding since technology performance standards are
not discussed as often, at least in the literature or public discourse in Europe at
least, as policies like feed-in tariffs. Perhaps technology performance standards
are more popular in the United States because of the recent passage of
legislation mandating automakers to respect new CO2 emission standards for
passenger vehicles in California. As many of the funds in the “do not like FiTs”
group were also based in the United States, geographical location and/or
investment focus (mainly North American markets) might explain this finding.
In addition, in the question about market-pull policies used there was a very
brief explanation about what a technology performance standard is which
included this example 86 .
CO2 tax
CO2 trading
CDM, JI
Red. FFS
certificate
trading
procurement
5.0
4.0
3.0
2.0
1.0
0.0
RFS
Feed-in tariff
RPS
Res and
comm tax
credits
PTC
Tech perf.
standards
Don't like FiTs
Do like FiTs
Figure 66: Other market-pull policy views of funds that found feed-in tariffs
effective, or not
Note: N = 47 in the “like” category (found effective, or score between 4-5), and
N = 11 in the “don’t like FiTs” category (did not find so effective, or score
between 0-3) 87
86 This policy was described in exactly the following way on the on-line and written survey:
“Technology performance standards (e.g. vehicle pollution standards)”
87 Note that N=11 in the don’t like FiTs category and the average scores among this category were
calculated based on very divergent views (e.g. only 2 funds in the smaller category rated RPS,
certificate trading or emissions trading high).
165

Meanwhile, those among this category also rated CDM/JI extremely low (some
saying it had no effect which is rated as 0), while CDM/JI is in theory a market-
based instrument under the Kyoto Protocol. This score makes sense however as
the question asked was how the VC or private equity fund managers rated
policies according to their effectiveness at stimulating less mature clean energy
technologies. CDM/JI is not intended to stimulate innovative new clean energy
technologies, but to stimulate investment in projects which substantially reduce
greenhouse gas emissions in developing countries, and it tends to promote
investment in “low hanging fruit”, not the most advanced clean energy
technologies, and often large projects are favored.
As for clean energy project finance in developing countries, one investor
explained: “In developing countries, the important thing is streamlining small
power production access into the grid with power purchase agreements,
interconnection requirements and international approvals and then it can work.
On international policy, there is a lack of understanding the people behind the
real projects; the entrepreneur drives a given project to success. Also,
investments can be done with less due diligence and investors do not really
need to consider regulatory risk in detail, if small transactions are made and
smaller returns are acceptable”.
Finally, two other factors have not been examined yet which are in fact within
the scope of the preferences of investors with regard to their investments in the
clean energy sector. They are: typical time to exit and their investment criteria.
Of interest is that the funds that did not find feed-in tariffs effective had longer
time to exit for their clean energy deals (6.5 years versus 5.5 years for funds
that found FiTs effective). However, note that the sample size was perhaps too
small to draw such a conclusion. Possible explanations for this result are: funds
in the “don’t like FiTs” category are much smaller funds dealing with earlier
stage investments and have less experience in the sector, leading them to take
longer to exit the deals they have in this space.
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Y e a rs to e x it
8
7
6
5
4
3
5.5
T im e to E xit
6.5
F iT s effective F iT s not so effective
Figure 67: Expected time to exit (average values) among funds that found FiTs
effective and did not find FiTs effective
Note: N =13 for “like FiTs”, N = 4 for “don’t like FiTs”
Examining the criteria of investment for funds that did not find feed-in tariffs
effective (see table 13 88 ), one can see that the capability of the management
team is important, as is financial prospects and the prospects regarding market
viability or opportunity. In some cases a strategic fit is important, in other cases
large growing markets, good patents and good management teams are
important. Some specific clean energy segments among their criteria, and
others are completely agnostic as long as the company is expected to deliver a
good return. These are the investment criteria that these funds scrutinize and
rely on in order to make a deal a successful investment, without assuming there
will be government subsidies at all.
88 Table 13 shows the top 5 investment criteria cited by each fund which rated FiTs low (1-3). The table
can be read with each row being the 5 criteria cited by a given fund.
167

Table 13: Top 5 investment criteria for each fund that does not like FiTs
Criterion 1 Criterion 2 Criterion 3 Criterion 4 Criterion 5
Can the
company work
at speed
Capability of
team
Make a return Agnostic to the
area of clean
technology
Can make
money
Promotes
sustainable
development
Adds value to
total food
chain of
industry
Market viability Technology Management Return
10x value
proposition
relative to the
customer's
needs
Market
Opportunity
OR IP control Leadership
Technical
Advantage
Strategic fit Business
Large growing
markets
within 2 years
Strong barriers
to entry
(patents)
Energy Balance Solar PV
Great
Management
Low or no
subsidy need
Generates
electricity using
renewable
energy sources.
upstream
companies &
enabling tech.
+ growth
dynamics
position in a sig.
industry
Regulatory
pathway
Stage of
company
technology
IRR potential Capital
Good
management
team
Wind developer
firms in NA
intensity
Potential for
explosive
growth for
company
Strong
partnership
prospects,
good
chemistry fit
Established Positive EBITDA Strong growth
Beyond
laboratory
stage
Manufacturer,
distributor or
installer of
clean energy
SME/Consumer/
Commercial (not
utility level)
End-user of RE
or advanced
clean energy
Established
distribution
channels
Water,
solar, coal
gasification
and ethanol
Business
model
Manage-
ment team
High trans-
parency
and
integrity
Less than
50 M to
profit
168

To conclude this section, it appears that funds which do not find feed-in tariffs
effective may have this view because they are not concentrated on clean energy
investments, they invest more generally and therefore they have other sets of
backgrounds in their fund management teams, and perhaps they rely on
different sets of information sources than funds which find feed-in tariffs
effective. Those that find feed-in tariffs effective tend to know the sector well,
having more energy backgrounds in their management teams, they tend to
interact more often with the entrepreneurs they finance and even Policy-makers,
they tend to invest more in the expansion stages of clean energy companies, as
opposed to the very early stages or the much later stages, meaning they must
know well the complexities of deploying clean energy technologies when
technologies are in the pre-commercial or even the supported commercial
stages (see literature review). They also turn to internal staff intelligence more
as an important source of information they use to make decisions on clean
energy deals.
Those that find feed-in tariffs effective also state that climate change is an
important driver, while those that don’t find FiTs effective say competitive
advantage is a much more important driver. Meanwhile, those that find FiTs
effective have larger clean energy funding sizes (on average) and a larger
portion of their firms’ VC and PE funding is invested in clean energy
technology companies (with smaller firm sizes, on average). They are located
and they invest all over the world, while those not liking FiTs are mostly in the
U.S. and focus on North American markets. All of these findings do make
sense and support the hypotheses or propositions developed in the conceptual
part of this thesis.
Therefore, a main finding is that policy is important to stimulating investment
in clean energy policies. Different types of funds with different characteristics
will tend to prefer certain types of policies to others. Still, feed-in tariffs were
the most preferred market-pull policy overall among investors surveyed and
interviewed. While, the majority of funds in the sample rated feed-in tariffs
higher than other options, this may also be due to the high prevalence of funds
which focus on the expansion stages of investment and which face many
hindering factors related to emerging technologies in the energy sector.
169

7.2.4 Detailed analysis of views on CO2 Emissions Trading
While CO2 emissions trading has already been discussed several times in
previous sections, this section aims to methodologically analyze the results of
the empirical data similar to the previous section on feed-in tariffs, which
involves a review of views on CO2 emissions trading (and the Kyoto Protocol),
using quotes from the interviews supplemented by an analysis of how key
characteristics relate, on average, to various views. While not every policy
could be analyzed in so much depth, it was decided to focus on these two
market-pull policies as there is more debate around these two policies in the
energy policy and climate policy literature than other policies looked at in this
thesis, with regard to the stimulation of renewable energy innovation 89 .
However, it should be mentioned that in some cases, CO2 tax was favored to
CO2 emissions trading. They had equal average scores, which makes sense as
they are intended to achieve the same thing (CO2 emission reductions) but in
different ways. CO2 tax sets a known price for CO2 emissions, while CO2
trading sets a target and develops a market which produces a variable price for
CO2 emission reductions according to market supply, demand, and other
factors which influence the price of emission permits. One last note on CO2 tax
is that CO2 tax tended to be supported more by European market-focused small
sized funds (not the smallest size) and tended to receive investment from banks
and private investors primarily. This makes sense as any type of tax-based
system has traditionally been considered a “non-starter” in the United States,
and secondly small sized funds supported by banks or private individuals are
probably the least influenced by a general dislike for tax-based climate policy
among large corporations.
Moving to this section’s assessment of the findings on CO2 emissions trading,
to begin with the expectations that CO2 emissions trading creates in the minds
of investors is reviewed. Recalling one of the comments noted from the
previous section, CO2 emissions trading is sometimes viewed by investors as
creating the right signal to the investment community that such policies are
long-term, but they are not directly affecting fund managers’ decisions
89 For CO2 emissions trading, see Bertoldi, et al. (2004); for feed-in tariffs, see: Rickerson, et al.
(2007)
170

egarding especially early-stage deals, so far. Another fund manager, which
invests mainly in fuel cell technology, explains his point of view, “Kyoto
creates expectations, but it does not have a direct impact. Government
procurement is the best option to stimulate adoption of new technologies.”
Another large clean energy fund manager from a large Swiss-based bank
commented, “The real question is what the market will pay for. If there is a
clear cost-benefit for the end consumers you can get the answer to the
question…A state RPS is fine, but a national RPS would be great. You also got
Kyoto as a potential overarching structure, but the developed world might
wander away from it for a variety of reasons, and you will see specific national
plans. It will continue to be a miss-mass of things, but even if you do it creates
a lot of opportunities.”
However, investors also had a variety of more skeptical comments to add about
CO2 emissions trading and the Kyoto Protocol. For example, one investor
noted: “For PV and wind energy, policy can have a strong impact, but I don't
know about emissions trading (in the long-term yes, it could have an impact)”.
Others had a realists view on how effective CO2 policies and the Kyoto
Protocol are at stimulating investment in clean energy technologies, such as
this large European-based firm’s venture capital fund manager’s comment:
“CO2 related policies are like an incentive and down the line it may impact us,
but it is an indirect benefit.”
Others had more positive comments to add about CO2 emissions trading. For
example, one fund manager from a large European bank which invests more in
clean energy projects than VC or private equity for companies, commented:
“As for international policy, the most effective policy would be to have an
international carbon tax, and the second best is the Kyoto Protocol type of
agreement which includes as many important countries emitting CO2 as
possible. Other solutions or activities are helpful, but they will not really drive
it forward. They will not cause a major change.” Other fund managers may not
have preferred CO2 emissions trading, per se, but had a preference for an
economy-wide or region-wide policy over a multitude of different support
schemes. One such European-based venture capital fund manager replied, “The
most important thing is to have one set of incentives for Europe and a strong
international market for sustainable energy. Different incentives like the
171

connected power incentives in Germany and the UK incentives based on CO2
emissions put different economical constraints on the technologies. There is
sensitivity of the technology to the incentives that vary and this is a problem.
This is why the U.S., which is a big open market, is better off than Europe 90 .”
However, sometimes investors appear to misunderstand how trading schemes
work. One fund manager, for example, gave a somewhat contradictory reply:
“We should not support any 1 st generation technology at all. We should
support 2 nd generation technology. Trading schemes are good…” The reason
this appears to be contradictory is that in particular CO2 emissions trading will
not support first generation technologies as it is designed to encourage
investment in the least costly emission reduction opportunities and usually the
least costly options are the 1 st generation technologies. Trading schemes for
renewable power are more effective, but also tend to stimulate the least-cost
option as discussed in the literature review of this thesis.
On the whole, before moving on to an analysis of the data, this qualitative
analysis implies that the Kyoto Protocol is viewed by investors largely as an
added incentive, but with little direct benefit, recalling one fund manager’s
comment: “Kyoto creates expectations but does not have a direct impact.”
Meanwhile, some investors highly regard CO2 emissions trading because “it
creates the right signals”, but others (which appear to be financing the early-
stages of companies) tend to see little direct benefit from trading schemes. One
of the VC fund managers interviewed described this perspective in the
following way: “…it is sometimes hard to see the linkage of the EU ETS and a
company we invest in. There is not a lot of impact on our little investments. It
impacts more the investment environment, than the actual investments”.
From Figure 68, we see by firm type that the funds which found CO2 emissions
trading most effective were from the following types of firms: banks and
subsidiaries of private equity firms, as well as other types of firms which were
90 On this point, it should be pointed out that a majority of the funds interviewed and surveyed
highlighted the same issue. The U.S. was esteemed to be a better market environment for investment
because first of all it is a bigger market, but secondly because it is at least perceived to be a much more
uniform market for clean energy technologies, compared to Europe, despite a variety of state-based
policies and the lack of a common definition for RECs which one U.S.-based fund manager pointed out
in the interviews.
172

not included in the options provided in the survey. Independent funds and
corporate venture capital funds were about equally split about CO2 emissions
trading.
16
14
12
10
8
6
4
2
0
Indep B ank C V C S ub P E F O F O ther
4 or 5 for C O 2 trading 0-3 for C O 2 trading
Figure 68: Number of funds for each firm type by rating for CO2 emissions
trading
Note: N = 49.
The cleantech funds also had about an equal split in terms of their views on
CO2 emissions trading. One of the most interesting results in terms of fund
type is that dedicated clean energy (DCE) funds clearly did not find CO2
emissions trading effective. This is probably because they are more informed
about the pros and cons of this more complex policy via internal information
sources with regard to the impact of the policy on their investments and less
influenced by the media or other superficial sources of information, because
they are concentrated on the clean energy sector which is highly impacted by
climate policy compared to other sectors. Also, general private equity funds
preferred CO2 emissions trading while general venture capital funds with some
or significant funding of clean energy did not find CO2 emissions trading
effective as much, although sample sized was too small on these categories in
order to conclude that this is the case for all general VC and general PE funds.
173

10
9
8
7
6
5
4
3
2
1
0
DCE
C TF
G vsig
G vsom e
G vno
G psig
Gpsom e
4 or 5 for C O 2 trading 0 -3 for C O 2 trading
Figure 69: Number of funds for each fund type by rating for CO2 emissions
trading
Note: N = 52.
As for stage of investment, there was not much difference between funds
focused on the expansion stages of finance or all stages. However, among seed
and start-up stage focused funds, there were slightly more funds in this
category which had less favorable scores for CO2 emissions trading. The most
robust finding was that funds in the later-stages had a much greater preference
for CO2 emissions trading, although again there were only 6 funds in this
particular category.
G pn o
Oth er
174

14
12
10
8
6
4
2
0
5
7
11
12
S e e d /S tart-up E xp ansio n L ate r s tag e A ll
4 o r 5 fo r C O 2 trad ing 0 -3 fo r C O 2 trad ing
Figure 70: Number of funds for each stages of investment focus by rating on
CO2 trading
Note: “Like CO2 trading” = rating of 4 or 5; “Don’t like CO2 trading” = rating
of 3 or less. N = 50.
Funding size is clearly related to funds’ views on CO2 emissions trading. The
firms with smaller total VC/PE funding sizes (firm size) did not find CO2
emissions trading effective as much as firms with larger overall VC/PE
funding. Also, within the funds that found CO2 emissions trading effective, the
portion of clean energy funding compared to total funding is quite small
compared to the case for funds that did not find CO2 emissions trading
effective.
5
1
4
5
175

9 0 0
8 0 0
7 0 0
6 0 0
5 0 0
4 0 0
3 0 0
2 0 0
1 0 0
0
4 o r 5 fo r C O 2 trad ing 0-3 for C O 2 trading
C E fund ing Non C E fund ing
Figure 71: Fund size (on average) for groups of funds with a given rating for
CO2 trading
Note: N = 34.
As for the funds that found or did not find CO2 emissions trading effective, we
can observe their average scores given to other policies in the market-pull set.
One can observe one significant difference among the set of policies that is that
a positive view on CO2 emissions trading appears to be correlated with a
positive view on CO2 tax and the Kyoto Mechanisms (CDM/JI). Their view of
green certificate trading and residential and commercial tax credits was also
slightly more positive than for funds that did not find CO2 emissions trading
effective.
176

CO2 tax
CO2 trading
CDM, JI
Red. FFS
certificate trading
procurement
5
4
3
2
1
0
RFS
Feed-in tariff
RPS
Res and comm tax
credits
PTC
4 or 5 for CO2 trading 0-3 for CO2 trading
Tech perf. standards
Figure 72: Other views on market-pull policies for funds grouped by rating on
CO2 trading
Note: N varies by policy. N is approximately 50.
Although the findings on hindering factors were not as informative as for
hindering factors by feed-in tariff preference, Figure 73 shows some slight
differences in hindering factors for funds that did or did not find CO2
emissions trading effective, such as less experience and market power of
incumbents. Funds liking CO2 emissions trading rated market power of
incumbents as an important hindering factor. This might have more to do with
the type of investors that they are (e.g. later-stage investors will face this more
than early-stage investors). Funds not liking CO2 emissions trading rated less
experience in the clean energy market as an important hindering factor for them,
along with technology risk, high capital expenditure in the energy market, and
long lead-time. Perhaps they perceive the CO2 emissions trading scheme as not
being helpful in addressing some of these key concerns.
177

Lack of competent
venture mgrs
Technology risk
Mrkt power of incumb.
Less experience
Institutional investor
interest
5
4
Lack of track record
Lack of gov.
commitment
Deal flow
3
2
1
0
High capex
Rated 4 or 5 for CO2 trading
Rated 0-3 for CO2 trading
Long lead time
Lack trade sale opp
Fossil Fuel Subsidies
Lack of competent VCs
Figure 73: Perceived hindering factors for funds grouped by rating on CO2
trading
Note: N = 34.
As for geographical location of funds, Figure 74 is showing one main finding
which is that U.S.-based funds tend to not find CO2 emissions trading as
effective as other funds which are not U.S.-based or UK-based. This makes
some sense, first of all because the U.S. did not ratify Kyoto, and second
because only Europe has experience with a mandatory CO2 emissions trading
scheme (the EU ETS). However, the U.S. has had experience with SOx trading.
Also of interest was that UK-based funds were equally split with regard to how
effective they viewed CO2 emissions trading to be at stimulating their interest
to invest in innovative clean energy technology companies.
178

14
12
10
8
6
4
2
0
US G B O ther
4 or 5 for C O 2 trading 0 -3 fo r C O 2 trading
Figure 74: Geographical location of funds grouped by rating on CO2 trading
Note: N = 51.
International policy was also viewed differently by funds according to their
views on CO2 emissions trading, which makes perfect sense because CO2
emissions trading is closely linked to the Kyoto Protocol. Obviously, funds that
found CO2 emissions trading effective also preferred extension of the Kyoto
Protocol over all other options (including all options presented, i.e. Kyoto
extension with sector-by-sector agreements and international R&D agreements).
Funds that did not find CO2 emissions trading effective clearly preferred
sector-by-sector energy-sector agreements (like internationally agreed clean
energy targets).
179

12
10
8
6
4
2
0
2
4
9 9
1
R & D K P S e cto r A ll None
4 o r 5 fo r C O 2 trading 0 -3 fo r C O 2 trad ing
11
Figure 75: International policy views for funds grouped by rating on CO2
trading
Note: N = 49.
Finally, in general one aspect that CO2 emissions trading, as well as feed-in
tariffs, must avoid in order to attract investors is inconsistency. CO2 emissions
trading, just like feed-in tariffs, have the potential to be a very consistent (albeit
CO2 trading would involve fluctuating prices for an indirect commodity and
feed-in tariffs provide fixed prices for the direct commodity in the case of green
electricity). This consistency is possible for CO2 emissions trading as well
assuming that the policy is well set within the framework of a long-term
climate policy, and features all the necessary monitoring and verification rules,
backed by a mandatory registry for CO2 (or carbon) reductions, and a legally-
binding long-term legislation.
One investor highlighted:
“The most important thing is consistent long term policies that provide a level
of certainty. Historic U.S. wind regulation provides a clear example of how
not to do it.”
6
4
0
3
180

7.3 Findings about technology-push policies
Now turning to technology-push policies, it is important to note that the
question asked about such policies did not specify that respondents should
consider only less mature technologies when rating these policies. However,
this was considered not necessary, because technology-push policies are
intended to encourage the development of new technologies in any case. Also
several such policies are not specific to the clean energy industry, but relevant
to technological innovation in general. Nevertheless, respondents were asked to
rate them with regard to clean energy private equity and venture capital
investments, in particular.
Furthermore, technology-push policies are further away from certain types of
private equity investors (e.g. buy-out or even expansion venture capitalists), but
closer to others (e.g. seed capital investors). Again, the placement of policies
along the venture capital and innovation cycle must be taken into account when
comparing policies. The policies or programs have been placed clockwise
along the radar chart in order of their relevance along the innovation chain, for
each of reference. Again, according to theory, the policies are best suited to
stimulate less mature technologies and then more mature technologies as you
move clockwise along the radar chart. After the last technology-push policy,
the first market-pull policy would follow in terms of innovation chain and
maturity of technology relevance.
181

7.3.1 Overall findings
Overall, such technology-push policies received lower scores than market-pull
policies, as shown in Figure 76.
Tax brks inv.
Govt. inv. priv VC
Inv. Subsidies
Government VC
funds
2.8
2.7
3.2
2.3
Grants for SMEs
3.2
R&D pub.
5.0
3.4
4.0
3.0
2.0
1.0
0.0
3.2
R&D priv.
2.3
3.1
2.7
3.8
Gov demo grants
Soft support
Incubators
Tax brks entre
Figure 76: Technology-Push Policies (overall scores for all funds)
Note: “Govt. inv. priv VC” stands for “Government investment in private VC
funds”, “Tax brks inv.” stands for “Tax breaks for investment in clean energy
funds”, “R&D pub” stands for “doubling publicly financed R&D”, “R&D
priv.” stands for “doubling privately financed R&D”, “Tax brks entre” stands
for “Tax breaks for entrepreneurs”, and “Gov demo grants” stands for
“Government demonstration grants”. N = 56-60 depending on the policy.
The lowest scores were 2.3 for Government VC funds and 2.3 for soft support
measures. The highest score was 3.8 for government demonstration grants or
other financial support for demonstration plants. Therefore, government
demonstration grants received an overall higher score than all the market-pull
policies, except feed-in tariffs.
182

A couple other policies or programs on the technology-push side were given
relatively good scores. That is, overall fund managers thought they encouraged
the development of innovative clean energy technologies and thus private
equity investment in such clean energy technology ventures best.
The other policies receiving relatively high scores were:
! Doubling public R&D for public institutions 3.4
! Investment subsidies for manufacturing facilities 3.2
! Grants for SMEs or communities to install equipment, etc. 3.2
! Doubling R&D for private institutions 3.2
! Tax breaks for entrepreneurs 3.1
Those receiving less than 3 out of 5 were (from lowest to highest):
1. Government VC funds 2.3
2. Soft support 2.3
3. Government investment in private VC funds 2.7
4. Tax breaks for investors 2.8
A final analysis of the mean with standard deviations for each policy’s score
among technology-push policies shows that there is somewhat more variance
and larger differences between average scores given to policies in this category,
compared to market-pull policies. The two policies with the greatest variance
were government funding for private VC funds and tax breaks for
entrepreneurs. The policy receiving the highest overall score is government
grants for demonstration plants, as shown in Figure 77.
183

5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
R&D priv.
4.7
3.2
1.7
Soft support
3.7
2.3
1.0
Incubators
4.1
2.7
1.4
Tax brks entre
4.3
3.1
4.6
3.2
1.8 1.8
Grants for SMEs
Gov demo grants
3.8
2.4
Government VC funds
3.7
2.3
4.4
2.7
4.6
2.8
0.9 1.0 1.0
Govt. inv. priv VC
Tax brks inv.
Inv. Subsidies
Figure 77: Average (mean) scores for technology-push policies with
corresponding standard deviations added to the mean and dispersions among
scores for each policy
Note: N = 56-60 depending on the policy. Ratings are 0-5, where 0 is no effect
and 5 is greatest effect.
25
20
15
10
5
0
Figure 78: Dispersions of scores for technology-push policies (for all funds)
Note: N = 56-60 depending on the policy. Ratings are 0-5, where 0 is no effect
and 5 is greatest effect.
4.5
3.1
1.7
184
0
1
2
3
4
5

In order to visualize the distribution of responses that make up a given policy’s
mean score, Figure 79 shows where most of the responses lie for each policy.
The size of the bubbles in this figure represents the number of responses
corresponding to a given rating. For example, quite a few respondents
answered “no-effect” for tax breaks for investors that also contributed to the
lower overall rating for this measure. Government VC funds and government
investment in private VC funds also received the score of “1” quite a few times
which contributed to the overall score being quite low. On the other hand,
government grants for demonstration plants received almost always the score
of 4 or 5, contributing to its being the overall most preferred technology-push
policy for clean energy private equity and venture capital investors.
Rating
6
5
4
3
2
1
0
11
18
13
7
3
5
6
7
12
19
6
7
6
15
16
5
4
5
17
18
9
3
3
10
17
15
8
1
5
Figure 79: Frequency of ratings for technology-push policies, for all funds
19
21
9
4
4
3
9
14
10
13
6
10
13
5
10
10
7
12
13
6
9
4
10
6
20
15
7
2
5
R&D!priv.
Soft!support!
Incubators
Tax!brks!entre
Tax!brks!entre
Grants!for!SMEs
Gov!demo!grants
Government!VC!
funds
Govt.!inv.!priv!VC
Tax!brks!inv.
Inv.!Subsidies
Note: N = 56-60 depending on the policy. The size of the circles is proportional
to the frequency. Ratings are 0-5, where 0 is no effect and 5 is greatest effect.
Policies are displayed starting with R&D on the left and ending with
investment subsidies on the right of the bubble chart.
185

7.3.2 Specific findings
Later-stage investors prefer government involvement in the earliest stages of
the technology-push part of the innovation chain.
Interestingly, one can see from the empirical data on technology-push policies
that later-stage funds actually prefer government involvement in the earliest
stages of the innovation chain. They rate R&D, incubators, tax breaks for
entrepreneurs, and government demonstration grants higher than other
technology-push policies relevant to the later stages of the innovation chain,
such as grants for SMEs to install equipment and government VC funds, in
particular.
They do, however, rate investment subsidies for manufacturing facilities fairly
well, with relation to later-stage technology-push options. The least favored
options in their opinion are grants for SMEs and government VC funds.
According to interviews conducted, this is because they feel that the
government is not good at choosing technologies that can work on the market
in reality, and they feel that the private sector (e.g. investors) are best able to
choose successful technologies for market deployment.
One investor interviewed highlighted this point:
“Most investors don't want the government to be in the position of picking
technologies - rather develop policies that are performance related (technology
agnostic)”
Meanwhile, seed or start-up funds tend to rate government VC funds higher
than other stages, probably as they see such funds as critical to bridging the
‘technology valley of death’ gap. Nevertheless, government VC funds received
the lowest overall score, together with soft support measures, according to
investors in all stages of company development. Soft support measures were
not perceived as critical to such investors, which often involve larger sized
investment firms. One such fund manager noted: “Coaching is not critical.
General advice is good, but not necessarily from the government”.
186

Tax!brks!inv.
Govt.!inv.!priv!
VC
Government!
VC!funds
Inv.!Subsidies
Grants!for!
SMEs
R&D!pub.
5.0
4.0
3.0
2.0
1.0
0.0
Gov!demo!
grants
R&D!priv.
Soft!support!
Incubators
Tax!brks!entre
Seed!or!Start"up
Expansion
Later!stages
Figure 80: Mean scores for technology-push policies, by stage of investment
focus
Note: N = 41.
There was some divergence of views on technology-push policies among the
different fund types
For example, one can see from Figure 81 that some of the divergence in views
with regard to government investment in private VC funds might be explained
by the differences in opinion among different fund types. Cleantech funds
appear to find this option more effective in comparison to other fund types,
such as dedicated clean energy funds. Meanwhile, incubators are found to be
relatively more effective by general VC funds which makes sense given that
they are more inclined to benefit from them as they are obtaining deals along
the early-stages of the innovation chain. However, dedicated clean energy
funds do not find incubators and soft support mechanisms as effective as others.
Dedicated clean energy funds prefer doubling R&D for public institutions
instead and grants for SMEs or communities to install equipment, or
government grants for demonstration plants which all fund types score well. To
conclude, the divergence of views along the left and right sides of the chart
All
187

might also explain the higher overall scores along the top and bottom parts of
the chart, where there was more agreement among fund types.
Tax brks inv.
Govt. inv. priv
VC
Inv. Subsidies
Government
VC funds
Grants for
SMEs
R&D pub.
5
4
3
2
1
0
Gov demo
grants
R&D priv.
Soft support
Incubators
Tax brks entre
Figure 81: Mean scores for technology-push policies, by fund type
Note: N = approximately 58 (depends on policy).
CTF
DCE
General PE
fund
General VC
fund
Investors with experience in clean energy investing viewed government
investment in private VC funds and government VC funds, as well as soft
support options, as the least effective technology-push option.
Fourteen funds, which invested in clean energy technology before the year
2000, scored very low government investment in VC funds as well as the soft
support policies and incubators. They also did not favor doubling R&D
spending for private institutions. Their favorite technology-push options were
government grants for demonstration plants and tax breaks for investors.
188

Tax brks inv.
Govt. inv. priv VC
Inv. Subsidies
Government VC
funds
Grants for SMEs
R&D pub.
5.0
4.0
3.0
2.0
1.0
0.0
R&D priv.
Gov demo grants
Soft support
Incubators
Tax brks entre
Figure 82: Views of experienced clean energy fund managers (invested pre-
2000)
Note: “experienced” means that the fund manager has relatively more
experience investing in the clean energy market than others because they
answered that they invested in clean energy already before the year 2000. N =
39.
As for technology-push policies, there was a large disparity among viewpoints
by fund size.
The differences can be understood quite easily. For example, government
funding for demonstration plants were favored by funds that were spending 0-
100M Euros on clean energy. While this category might include funds which
are less committed to clean energy than other fund sizes, they also are more
likely to be early-stage investors which can benefit most from such government
grants to demonstrate potentially breakthrough technologies in this sector
which they are betting on with smaller levels of finance, compared to private
equity investors. Similarly, funds spending 0-10M Euros found investment
subsidies effective for manufacturing facilities.
189

As for large clean energy funds, which are likely to be private equity investors,
overall scores for technology-push policies were very low, indicating that these
policies do not effectively encourage investors in this category to invest more
in the clean energy sector.
Tax brks inv.
Govt. inv. priv VC
Government VC
funds
Inv. Subsidies
Grants for SMEs
R&D pub.
5
4
3
2
1
0
R&D priv.
Gov demo grants
Soft support
Incubators
Tax brks entre
Figure 83: Mean scores for technology-push policies, by fund size
Note: N = 33. M = millions of Euros.
0-10M
10-100M
100-250M
250-500M
Government led investment in funds or SMEs is not supported by private firm
types.
Governments found public investment in government-managed VC funds
effective as well as private VC funds. Meanwhile, one independent general VC
fund manager investing significantly in clean energy technologies gave the
score of 1 to government VC funds and 5 to government investment in private
VC funds. He explained, “Public funds should invest in (private) VC funds
instead of investing directly in clean energy companies. Institutional and
private investors must invest more in VC funds in Europe, also in VC funds of
first time teams. Otherwise, Europe will loose its R&D edge over the U.S. In
the U.S. there is already much more cleantech VC money in the market”.
190

Another fund noted: “Always support private VC funds as opposed to public
VC funds. They tend to do better.”
Tax brks inv.
Govt. inv. priv
VC
Inv. Subsidies
Government
VC funds
Grants for
SMEs
R&D pub.
5
4
3
2
1
0
Gov demo
grants
R&D priv.
Soft support
Incubators
Tax brks entre
Figure 84: Technology-push policy views by type of firm
Note: N = approximately 56 (depends on policy).
Bank &
SubPE
CVC
Gov.
Indep.
There was quite a diversity of views on technology-push policies among firm
size.
The largest sized firms in particular had given lower scores to most of the
technology-push policies, however they really found R&D for public
institutions effective, and they rated government grants for demonstration
plants quite high. The smallest firm sizes also rated government grants for
demonstration plants high, with R&D for public institutions. Notably,
government investment in private VC funds was well perceived by small firm
sizes (50-100M Euros). They also found effective investment subsidies, R&D
for private institutions, and grants for demonstration plants. Medium sized
firms find tax breaks for investors and investment subsidies more effective,
than the other technology-push policy options.
191

Tax brks inv.
Govt. inv.
priv VC
Government
VC funds
Inv.
Subsidies
Gov demo
grants
R&D pub.
5.0
4.0
3.0
2.0
1.0
0.0
Grants for
SMEs
R&D priv.
Tax brks
entre
Soft support
Incubators
Figure 85: Mean scores for technology-push policies, by firm size
Note: N = approximately 46. Euros are used for firm size.
0-50M (very
small size)
50M-100M
(small size)
100M-250M
(medium
size)
250M-1B
(large size)
1B-5B (very
large size)
The technology-push policies were found least effective by funds supported
primarily by banks, except for doubling of R&D funding for public institutions.
Corporate and private investors, with mixed investor sets, rated grants for
SMEs or communities to install equipment quite high, while banks rated this
option very low in comparison. Bank-supported funds also did not rate the
highest-ranking technology-push policy (grants for demonstration plants) high.
192

Tax brks inv.
Govt. inv. priv VC
Inv. Subsidies
Government VC
funds
Grants for SMEs
R&D pub.
5
4
3
2
1
0
R&D priv.
Gov demo grants
Soft support
Incubators
Tax brks entre
Bank
Corporate
Private
Mixed
Figure 86: Mean scores for Technology-push policies, by core investor type
(LPs) of prevalence in each fund
Note: Pension was left out, as there were only 2 funds that were backed by
pension funds. N = approximately 45 depending on policy.
U.S. funds were the least receptive to the soft support measures and
government funding of private VC funds or government VC funds.
Meanwhile, the UK-based funds found very effective government investment
in VC funds. Tax breaks for entrepreneurs were also favored by UK-based
funds. Other European-based funds had more moderate positions, overall,
about technology-push policies.
193

Tax brks inv.
Govt. inv. priv VC
Inv. Subsidies
Government VC
funds
Grants for SMEs
R&D pub.
5
4
3
2
1
0
R&D priv.
Gov demo grants
Soft support
Incubators
Tax brks entre
Figure 87: Technology-Push policy views by country of management
Note: N = approximately 56.
North American-focused funds tended to find R&D for public institutions, and
both tax breaks for investors, as well as tax breaks for entrepreneurs, as more
effective, than European-focused funds did.
European-focused funds found investment subsidies effective for
manufacturing facilities with government investment in private VC funds, with
government grants for demonstration plants, the most of the all the options and
they found them more effective than North American-focused funds.
US
GB
Europe
-
Others
194

Tax brks
inv.
Govt. inv.
priv VC
Governme
nt VC
funds
Inv.
Subsidies
Grants for
SMEs
R&D pub.
5
4
3
2
1
0
Gov demo
grants
R&D priv.
Soft
support
Tax brks
entre
Incubators
Europe
North
America
Figure 88 : Mean scores for technology-push policies, by region-focus
Note: N = approx. 50.
7.4 Conclusions from a market-pull vs. technology-push
policy comparison
First, we find that overall, there were more market-pull policies that received
fairly high scores and there is a preference for market-pull policies over
technology-push policies, taking into account the entire set of market-pull
policies vs. the entire set of technology-push policies in the two questions
(Figure 89). However, these questions were not directly comparable as the
policies address different parts of the innovation chain, and it is important to
note that this preference might be due to the fact that in the full set of funds
surveyed and interviewed quite a few were expansion stage investors which
may be less affected by or interested in technology-push policies.
Furthermore, the differences (or similarities) among the policies in each set are
not exactly the same. Nevertheless, on average, it was clear from the calculated
mean results, and the distribution of responses, that overall funds scored
195

market-pull policies relatively higher than technology-push policies. Five
technology-push policies received scores of less than 3, while all market-pull
policies were rated more than 3 (5 of these policies were rated 3.5 or above).
While every respondent may have a different perception of what the average on
the scale of 1-5 is, a score of higher than 3 can generally be viewed as above
average, and the same respondents replied to both market-pull and technology-
push questions. Also, the option of answering “no effect” allowed the entry of 0,
which could bring down all the averages if many respondents viewed various
policies as having absolutely no effect on their interest to invest in the sector. In
fact, at least one investor (a large bank) rated all the technology-push policies
as “no effect” on their interest to invest in the sector, which also contributed to
bringing down the average score.
5.0
4.0
3.0
2.0
1.0
0.0
3.3
3.0
Average!market"pull!score Average!market"push!score
Figure 89: Average scores of average overall market-pull and technology-push
policies
Note: N = 56.
Among the technology-push policies, government demonstration grants (which
received a greater score than all market-pull policies, except feed-in tariffs) and
doubling of public R&D for public institutions received the top two scores.
Therefore, one proposition based on this empirical data is: Government
demonstration grants and doubling of public R&D support clean energy
196

technological innovation best, assuming that the early-stages of technological
innovation are the critical stages.
Meanwhile, the top two market-pull policies overall were feed-in tariffs and the
reduction of fossil fuel subsidies. These are both price-based mechanisms, but
one is affecting supported-commercial technologies and is a market
deployment instrument (feed-in tariffs) and the other is supporting fully
commercial technology and is a market-barrier reduction instrument (reduction
of fossil fuel subsidies). Investors are probably showing a clear preference for
feed-in tariffs because they highly value the reduction of price-risk in the
market that is related to their perception of market risk.
Meanwhile, clearly as a barrier reduction policy, investors prefer the reduction
of fossil fuel subsidies as it introduces the least amount of distortions into the
market, and would fit best with their ideal world policy environment. This is
the case even though many investors interviewed recognized the political
infeasibility of reducing fossil fuel subsidies without internationally doing so.
One U.S.-based VC fund manager highlighted, “Trying to tax negative
externalities is key. This allows clean technologies and fuels to be compared on
an equal basis in terms of cost, with more traditional inefficient forms of
transport. Elimination of all subsidies to agriculture and roadway
transportation will show their true costs and encourage investment in more
efficient transport systems.” Another European-based VC fund manager even
stated: “Government should be transparent about the real cost of traditional
energy sources (include external costs including all related effects such as
volatility of the energy price). We should start the debate about why buying
food from Africa is not in the national interest, but buying energy from
undemocratic governments is. Policies should help create market pull.”
Among the market-pull policies, we also contribute to the debate about barrier
reduction policies like CO2 emissions trading versus market deployment
policies like feed-in tariffs, with the finding of a clear distinction between the
individual scores for CO2 emissions trading and feed-in tariffs. For example,
there was clearly more dispersion among the CO2 emissions trading scores,
compared to feed-in tariffs.
197

The dispersion of views with regard to CO2 emissions trading was also true for
funds located in the United States. However, there was slightly more variance
in the scores for feed-in tariffs among funds located in the U.S., compared to
the full data set, which appeared to have resulted in an overall slight reduction
in their overall score for feed-in tariffs, compared to other fund locations.
Overall, looking at the policies according to the number of times they each
received the highest scores, one can notice quite evidently the superiority or
preference for feed-in tariffs. Also of interest, is that CO2 emissions trading,
along with CDM, JI, and certificate trading, received the highest number of
lowest scores (0-2) among the total sample. Therefore, as for market-pull
policies, feed-in tariffs are clearly preferred over CO2 emissions trading, with
regard to stimulating private equity investors’ interest to invest in early-stage
clean energy technology ventures. CDM/JI received the lowest overall score for
stimulation of interest to invest in less mature innovative clean energy
technologies. But it should be noted that 44% of the funds were U.S.-based
funds, and the United States does not participate in the Kyoto Protocol.
It is interesting to note that although many environmental economists today
believe that CO2 emissions trading is the most efficient market-pull policy
available to correct market failure, create a level-playing field, and cost-
effectively meet GHG emission reduction targets, the findings in this study
point out a possible failing of this type of policy to stimulate important
investment in innovative clean energy technology ventures. Perhaps it is simply
that investors do not perceive this policy as effective with regard to how it has
been implemented so far (a few fund managers interviewed commented on the
failures of the Kyoto Protocol – both regarding reliable long-term targets and
the realities of dealing with the Kyoto Mechanisms (CDM and JI). Finally, the
implementation of the European CO2 Emissions Trading Scheme has proven to
be quite difficult, as indicated earlier. Otherwise, perhaps they have heard from
their portfolio companies that it does not affect their businesses. This was the
case of one of one VC fund manager interviewed for this study. Therefore, one
would assume that the more a fund manager communicates with his or her
entrepreneurs, and the more they care about how policies can impact the
financial situation of their portfolio companies, the more the fund manager will
be skeptical about the benefits of CO2 emissions trading.
198

7.5 Findings about regulatory issues
For the sake of completeness, participating fund managers were asked to rate
their satisfaction with regard to various regulatory issues affecting clean energy
sources, although these regulatory issues are purely relevant to the electricity
sector and are pretty far detached from venture capitalists in particular. From
the literature review we have seen how important the good handling of
regulatory issues is, in addition to the setting-up of effective incentive
structures for clean energy technologies. According to one investor
interviewed: “Good handling of regulatory issues is more of a pre-requisite”.
Specifically, fund managers were asked about siting politics (e.g. for onshore
wind), grid access, and net metering regulations (for trading surplus electricity).
They could rate their satisfaction with these regulations on a scale of 1-5, with
their highest level of satisfaction being 5. They were asked to rate the chosen
regulatory issues with regard to their interest to invest private equity
(PE) and/or venture capital (VC) in all types of Clean Energy (for
example, both wind and solar investments).
Before, moving into the analysis, it is important to note that this particular
policy question received a significant amount of “N/A” responses, which
basically meant that a significant number of the respondents either did not
know how to reply to the question, or that such regulatory issues were so not
relevant to their investment related decision-making. This can be understood
for at least early-stage investors that are farther away from the realities of
regulatory issues such as siting, grid access and net metering. Figure 90 shows
the number of respondents answering “N/A” for each regulatory issue 91 .
91 Given that the sample size was approximately 60 funds, this question received only a 58-68%
response rate.
199

30
25
20
15
10
5
0
25
20
Siting!policies! Grid!access Net!metering
Figure 90: Number of funds answering “N/A” for each regulatory issue
Note: 28 funds answered all three regulatory issue questions with a rating.
Therefore, N=53 for siting policies, N=45 for grid access, N=47 for net
metering.
Nevertheless, Figure 91 shows that among funds that answered the question,
fund managers appear to be on the most part not satisfied (satisfaction level of
less than 3, overall) with the current implementation of the above regulations in
the electricity sector.
5.0
4.0
3.0
2.0
1.0
0.0
2.4 2.4 2.5
Siting!policies! Grid!access Net!metering
Figure 91: Levels of satisfaction with regard to regulatory issues
Note: mean scores 1-5; and “no effect” being 0; all funds. Not counting N/A
answers, N = 28.
19
200

Looking at these results by stage of investment, one can note that the least
satisfied group of investors was among funds focused on the expansion stages
of company finance.
5.0
4.0
3.0
2.0
1.0
0.0
2.7
2.1
2.3
3.3
2.5
2.2
Siting policies Grid access Net metering
Figure 92: Mean scores for regulatory issues by stage of investment
Note: N = 28.
2.8
3.7
2.7
2.5
2.6
3.3
Seed or Startup
Expansion
Later stages
By location of funds, one notes clearly that European-based funds are more
satisfied with regulatory issues than U.S.-based or UK-based funds (Figure 93).
In addition, by geographical focus, funds focused on North American markets
were the least satisfied with regulatory issues among all the issues. This
indicates that European countries are doing a better job at regulating the
electricity sector with regard to green electricity.
All
201

5.00
4.00
3.00
2.00
1.00
0.00
Siting policies Grid access Net metering
US
GB
Europe - Others
Figure 93: Mean scores for satisfaction levels with regulatory issues, by
country of management
Note: N = 28.
5
4
3
2
1
0
Siting policies Grid access Net metering
Europe
North America
Europe&North
America
Figure 94: Mean scores on satisfaction levels for handling of regulatory issues,
by regional focus
Note: N = 28.
Finally, the results also showed that general funds are somewhat more satisfied
with regulatory issues, overall, than dedicated clean energy funds. This makes
sense as dedicated clean energy funds have more at stake in the renewable
energy sector, and more knowledge on the sector, as well.
All
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7.6 Findings on international policy
As for international policy, fund managers were asked to choose among the
international policies that stimulate their interest to invest in clean energy
technology ventures the most. Three main approaches were provided as options,
including: 1) the Kyoto Protocol for climate change mitigation, 2) international
or regional R&D agreements, and 3) Sector-by-Sector approaches to climate
mitigation and/or clean energy 92 . Respondents could also choose between
“none of the above” if they felt that none of the international policies affected
their investment decisions or “all of the above” if the three mentioned options
were equally important.
Examining all funds’ responses for each type of international policy option, it is
clear that the majority of funds (22 funds) preferred the sector-by-sector
approaches to climate change mitigation and clean energy. Meanwhile, many
respondents (12 funds) found the idea of all three policy options most effective.
Few (only 4) believed that none were relevant. Only 10 funds thought that the
Kyoto Protocol, alone, was sufficient.
25
20
15
10
5
0
10
7
22
KP R&D Sector!by!
Sector
12
All!of!the!
above
4
3
None N/A
Figure 95: Choice preferences for all funds with regard to international climate
policy options
Note: N = 58.
92 The sector-by-sector approaches mentioned in the survey as examples were: clean energy targets by
sector or international agreements on sector-wide reduction of fossil fuel subsidies.
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Another way to understand the responses by funds with regard to international
policy options is to look at how their responses are associated with their views
on key clean energy investment drivers. In Figure 96, sector-based approaches
were chosen, on average, among funds that also mentioned energy security or
competitive advantage as the primary drivers for VC/PE investors to invest in
clean energy.
6
5
4
3
2
1
0
KP
R&D
Sector
All
None
N/A
Climate Change
Energy Security
Competitive
Advantage
Air Pollution
Figure 96: Number of funds responding for preferred international policy
option by the driver they mentioned as being most important among the four
Note: N = 53.
7.7 Findings on nuclear power
While the question asked regarding nuclear power was not about nuclear-
specific energy policy, the answers to this question might indeed interest
Policy-makers which are considering the re-birth of nuclear power in order to
address growing climate change concerns.
Respondents were asked whether they perceived that nuclear energy had the
potential to significantly reduce clean energy deployment (clean energy being
defined as renewable energy technologies and advanced alternative energy
technologies). While many respondents did not answer this somewhat delicate
question, the larger portion of those that did answer (20 out of 43 funds) replied
that it did not compete in such a way. Twelve funds, however, answered that it
did compete. From the interviews, the main reasons which fund managers gave
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for why they thought nuclear energy does not compete with renewable energy
technology were: 1) venture investments are of a completely different time
frame than nuclear energy investments, and 2) nuclear energy is not within the
typical scope of the private equity investment business. In a few of the cases
where the respondent answered that it did compete with renewable energy
technologies, there was a specific country context taken into consideration. For
example, one French VC fund manager answered that nuclear energy clearly
competes and has already substantially reduced the potential growth of
renewable energy markets, at least in France.
25
20
15
10
5
0
12
20
Nuclear!competes Nuclear!does!not! don't!know no!answer
Figure 97: Number of respondents that viewed nuclear energy as competing
Note: N=32 + 11 “don’t know”; Nuclear energy is defined as competing in
such a way that it might lead to a significant reduction in the market
deployment of clean energy technologies and potentially reduced VC/PE
investment in clean energy.
11
17
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8 Findings on Regulatory Risk Management
approaches
8.1 A typology of regulatory risk approaches
The policy analysis has shown that funds can have quite different views about
different policy options, but most among the private equity industry appear to
recognize the importance of policy with regard to their clean energy
investments. A number of fund characteristics were also found to be associated
with particular policy preferences among funds. Similarly, one would assume
that if investors found policy effective and important to the clean energy
industry, they would also be interested in regulatory risk management. It is also
possible that some fund characteristics will correlate with a fund’s individual
regulatory risk management approach.
It is proposed in this thesis that an investor’s interest to invest in a given clean
energy portfolio company is composed of the investor’s perceptions about
various risks and their ability to manage them, as well as their perceptions
about opportunities related to the deals they are considering, and these
perceptions may be formed through a learning process (including a learning
process regarding policies), but also as a result of the influence of a number of
factors such as basic fund characteristics (like type of fund or firm), as well as
management’s information sources, and the influence of key stakeholders such
as core investors.
We have seen from the literature review that investors may foresee
opportunities for competitive advantage in the clean energy sector, based on
their perception of:
1) Major trends in the economy and macro-economic drivers for
investment in clean energy which are perceived to not be going away;
2) Policies which they perceive will only get stronger and more wide-
spread with time;
3) Growth potential from increasing cost reductions in particular
technologies (partly because of policies like feed-in tariffs);
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4) Their perceptions of lower risk in certain countries because of well-
designed policies for investors;
5) Their perceptions about the likelihood of breakthrough technology
opportunities in the sector, which may emerge from government R&D,
and be supported by demonstration grants, and other technology-push
policies, and
6) Their perceptions about increasing demand due to increasing consumer
awareness and multi-stakeholder interest in clean energy technologies,
including the interest among the institutional investors and other core
investors that invest in their funds.
Meanwhile, at the same time even the most experienced investors in the area
may foresee a number of serious barriers and risks relevant the large-scale
deployment of clean energy systems such as technology, market, regulatory
and systems risks (Foxon, et al., 2005). Investors closer to the market realities
(expansion stage and later-stage investors) are likely to have more experience
and information about policies and the risks they pose, as well as more intricate
regulatory risk management approaches. In previous research, Wuestenhagen
and Teppo (2006) provided a classification of potential relevant risks from the
venture capitalists’ perspective with regard to clean energy technologies. They
are: ‘Market adoption risk’; ‘Technology risk’; ‘People risk’ (in particular the
ability of the entrepreneurs and venture managers); ‘Regulatory risk’; and ‘Exit
risk’.
Later-stage private equity investors are likely to face the same risks, as venture
capitalists, but at a greater or lower extent. For example, technology risk
(depending on how it is defined) may be less important for a private equity
investor that is investing in already proven technologies. Meanwhile, regulatory
risks become much more relevant to private equity firms when they invest in
later-stage deals like company buy-outs in the energy sector, and are especially
critical when one considers the potential risks to investors of investing in
highly polluting plants like “dirty coal” under the assumption of a CO2 tax,
CO2 cap and trade scheme or a similar policy 93 . So, it can be expected that
93 Even if such a policy is not yet implemented, as long as the regulatory outlook remains highly
uncertain, the safest option for many utilities may be to build fewer plants (the Economist, March 1 st ,
2007).
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there will be differences in risk management strategy undertaken among funds
depending on key characteristics of the funds such as fund type.
As for the most basic results from this study, this research has shown that
indeed VCs and private equity fund managers consider policy when they make
their investment decisions regarding clean energy technology. There is also
recognition among venture investors that the clean energy sector is a partially
policy-driven market. For one, findings from the surveys and interviews
showed that almost all the funds in the sample had investigated clean energy
policies with regard to how they influence their decisions on clean energy deals.
60
50
40
30
20
10
0
yes not
certain
no answer no
Did fund m anager inves tigate
polic y im plic ations on its
c lean energy inves tm ents ?
Did the fund inves t V C or P E
in c lean energy tec hnology
c om panies (as defined)?
Figure 98: Number of funds that investigated policy and invested in clean
energy
Note: N=54
The results from this research have shown that indeed clean energy funds
utilize a variety of approaches to dealing with clean energy-related regulatory
risks. This section will report on the findings from interviews and the longer
on-line survey in which funds replied to an open question about how they
manage risks relevant to the clean energy sector, and regulatory risks in
particular.
Based on the literature review and the findings from the interviews and surveys
in this study, the following conceptual model of regulatory risk management
strategies shown in Figure 99 below, was developed.
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ACTIVE
Fund-level management
Inbound Outbound
Approaches to manage regulatory risk
Diversification
over markets, etc.
PASSIVE
Fund & Firm-level management
Fund level Firm level
Other, e.g.
getting in cheap
Diversification
over markets, etc.
Choice of
Management
Figure 99: Typology of Venture Investors' Regulatory Risk Management
Strategies
For active risk management strategies, inbound and outbound risk management
approaches have been distinguished, where inbound means strengthening a
venture's policy expertise by hiring people with relevant expertise (and using
this expertise to make careful investment decisions), and outbound means
actively influencing the regulatory environment. As for passive risk
management strategies, there are diversification activities and non-
diversification activities. The diversification activities are distinguished on the
portfolio (or fund) level and on the firm level, as well as diversification across
markets (technologies and countries). Other passive activities included
approaches such as “getting in cheap” on the fund level and choosing good
venture managers for firm-level (as opposed to fund-level) risk management.
Each of these strategies will be elaborated further below, and they will be
illustrated with direct quotes from the interviews and survey responses.
As for actively managing regulatory risks, there is extensive literature about
how VCs manage the inherent risks of their investments, mainly focusing on
the risks resulting from principal-agent problems between VC and entrepreneur
(see for example Kaplan & Strömberg 2001a and 2001b, Hellmann 2004).
Since regulatory risk is not rooted in the VC-entrepreneur relationship, but
rather in the business-government relationship, actively managing risks must
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take different forms when it comes to regulatory risk. VCs may manage these
risks either on an individual firm level or by taking collective action (also
referred to as structural political action of firms by Schneidewind 1998, or as
policy development strategies by Dyllick et al. 1997) to influence the
regulatory framework for some or all of their portfolio companies. While the
idea of actively managing regulatory risk is relatively well established in the
corporate sustainability literature, it is largely neglected in venture capital
research.
Actively managing regulatory risk as a private equity fund manager can include
directly influencing Policy-makers to support policies that favour the
investments they make (individually or collectively), or having a high level of
interaction with the policy-making community in order to stay informed and
invest where policies are most favourable or at least not unfavourable. Another
often utilized active approach, according to these findings, is to actively
manage regulatory risks by obtaining specific know-how about the sector
(either in-house or through closely connected external experts) and perform in-
depth due diligence with regard to regulatory risk factors before investing. In
some cases, they may disaggregate different risk types and assess for each deal
specific actions that can be taken to mitigate each single area of risk, including
regulatory risk relevant to a given investment deal. Also in some cases, the
investor does not invest unless there is very low resulting risk. In other cases,
the fund will invest if they see “the right progression” in technological learning
which would indicate that the technology will be competitive soon even if the
regulatory environment changes in the next 5-8 years. Under the most diligent
process of decision-making a final judgement is made about what the investor
can do to mitigate each type of risk and whether the benefits and potential
upside clearly outweigh the addition of all the potential risks relevant to the
deal. Investors can also manage risks more actively by having 3 rd party
consultants do an analysis of the policy-related risks of each clean energy deal.
They may also recognize that cleantech or clean energy investments are
different from other investment types and actively follow their portfolio
companies, e.g. and help them to take advantage of favourable policy
environments (“how to get generating attributes in addition to electrons”
according to one investor). Finally, understanding how to avoid issues related
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to a long investment cycle of clean energy and adapting the funds’ investment
strategy accordingly is also an active (inbound) strategy.
Funds that are concentrated in a particular sector, like the clean energy sector,
are more exposed to regulatory risks particular to the clean energy sector.
Therefore, it is logical that they have more interest to behave actively, as
opposed to passively, and to develop specialized (and more active) regulatory
risk management approaches. This thesis aims to identify what are those active
and passive approaches and what factors play a role in defining a given strategy.
As for Passively managing regulatory risks, there are two basic forms:
diversification or non-diversification (other indirect) activities. It is true that
almost every fund manager applies to some extent a portfolio diversification
approach to reduce the risks of their investments. Diversification among
company types, technologies, locations, stages, etc. is used by fund managers
to manage a variety of investment risks. However, this is considered a passive
regulatory risk management approach when the fund manager has no other
means to manage regulatory risks, because this approach is used to manage all
other types of risks in an indirect way, and not specifically to deal with
regulatory risk. Therefore, it is defined here as a passive way of managing
regulatory risks, but this does not imply that it is not a good way to manage
regulatory risks. This will be explained later.
Continuing with this description of diversification approaches, diversification
of regulatory risks can occur by geography, by investing across a variety of
sectors, across the cleantech sector, or across different clean technologies. It
can also occur on the firm level across the value chain for one technology area
like the PV industry. In some cases, another firm-level diversification strategy
involves diversification across technological applications (e.g. companies may
have technologies which can serve applications in other markets besides the
clean energy market). This is often an important strategy for seed-capital or
other early-stage investors that invest heavily in a few clean energy deals which
harbour technologies that can apply to other industries. Otherwise, on the fund
level, some funds may concentrate on one particular stage of investment, but
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diversify across a wide variety of cleantech sectors (energy, water, air, solid-
waste treatment, etc., as well.
In the case of passive regulatory risk management, the decision to diversify in
such ways is usually made in order to address what the investor perceives as
risks relevant to their fund or the sectors they invest in, but not necessarily in
order to address regulatory risk. It is often already a business practice of the
firm or fund and a happy result of this decision is the impact it has on lowering
regulatory risk. However, when the investor undertakes a particular
diversification strategy such as across geographies specifically to address
regulatory risks of the clean energy or the energy sector, than this is considered
an active regulatory risk management approach.
Also considered a passive regulatory risk management approach, under firm-
level passive risk management, a fund manager might prefer to concentrate on
“gate keeping” which would mean that they fund only companies with, for
example, great management teams or financial prospects. In doing this they
would assume a “base case” scenario (assuming a no-policy scenario). Highly
competent venture managers could be considered by such funds to be the best
means for dealing with any sort of change in the industry including changes in
policy. One fund manager noted that funds can deal with regulatory risks, but
they can’t manage changes in policy. Funds with this viewpoint hope that the
venture managers they fund will be capable enough to deal with these changes
themselves when the time comes.
Finally, another two more general strategies to risk management on the fund-
level are to not invest in a deal unless: 1) the prospects are excellent, and 2) you
partner with another major venture capital fund or several funds, or a major
energy corporation (you don’t invest unless another partner thinks the prospects
are excellent).
The first option of the second strategy (partnering with other funds) is more of
a passive strategy with regard to regulatory risk management, because it does
not imply that the fund itself had investigated risks related to policy. The
second option (investing only with large energy corporations) may be
considered as more of an active RRM strategy, because it means that the fund
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has recognized that a large energy corporation will be more informed about
energy policies and will serve to assess, and possibly manage the relevant risks
of the investment, accordingly.
8.2 Illustration of RRM approaches and key differences
First of all, the results show from a qualitative examination of the overall
sample of funds which answered the question on regulatory risk that most funds
used some type of active approach to regulatory risk management, than not.
In fact, many investors use both active and passive risk management strategies
at the same time. This is mainly because all funds have some element of
diversification in their funds, so strictly speaking all funds are also passive
regulatory risk managers, but not all funds are active regulatory risk managers.
Therefore, in the qualitative analysis of the interview and survey data on risk
management, if funds featured any aspect of active management then they were
placed in the active category.
Table 14: Basic statistics on fund characteristics by type of regulatory risk
management (RRM) approach
Note: based on Table A4 -1.
Active category Passive category
22 funds 8 funds
5 investing seed capital (22%), 9 start-up
(41%), 10 expansion stage (45.5%), 3
buyout (13.6%), and 3 are investing in all
stages (13.6%) 94
5 dedicated clean energy funds (DCE), 7
cleantech funds, 3 general VC funds with
significant CE funding, 1 general VC fund
with some CE funding, 1 PE fund with
significant CE funding, 1 PE fund with
some CE funding, and 3 other types
3 investing in seed capital (37.5%), 5
start-up (62.5%), 5 expansion stage
(62.5%), 1 buyout (12.5%) and 1
investing in all stages (12.5%)
0 DCE funds, 3 cleantech funds, 3
general VC funds with some CE funding,
1 general VC fund without any CE
funding (yet), and 1 other type
94 Percentages do not add up to 100% because many funds invested in more than one stage.
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As can be seen in table 14, the majority of both types of funds were investing in
the start-up and the expansion stages, while those in the passive category were
slightly more active in the earlier stages. As expected, early-stage VC funds
have less to loose from particular regulatory changes, as their investments are
more diverse and smaller in size. In terms of fund type, there were no dedicated
clean energy funds in the passive category while the passive category had
proportionately more general VC funds with only some clean energy funding.
Again, as expected, funds concentrating on the clean energy sector are more
likely to apply more active strategies than general portfolio diversification or
other indirect forms of risk management.
This chapter will explore all characteristics of funds that appear to be
associated more often with a given approach. This is undertaken to characterize
the sector for regulatory risk management. However, it is important to point out
that because there are a variety of different funds active in the sector, a
generalized conclusion on a best RRM approach would not be appropriate. It
would neither be academically sound, without studying fund performance data
along with RRM approaches. Nevertheless, one can assume that a good way to
manage regulatory risks, if they are deemed to be high and concerning for a
given funds’ investments, is to apply a mix of passive and active approaches in
order to cover the risks with all methods possible.
Turning to the interviews for a few examples, several of the comments made by
fund managers who belong to the active RRM category indicated that the best
way to deal with regulatory risk in this sector is to understand the sector very
well and perform thorough due diligence on deals with regard to a number of
issues, including the potential impacts of policies on deals. However, some
fund managers in the passive RRM category thought that regulatory risk does
not have to be dealt with any differently for the clean energy sector. This
explains why they did not choose to apply other approaches beyond portfolio
risk diversification. Others believed it would be impossible, in any case, to
predict how policy would evolve over time. Finally, some had more confidence
that the policy environment overall will not move away from addressing the big
issues which they did not expect to change: climate change and energy security
concerns. So, a variety of mind-sets about policy-making are relevant to the
way the fund handles regulatory risk, as well as a variety of different fund
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characteristics that set different boundary conditions on the funds such as their
funds’ overall exposure to regulatory risk in the clean energy sector.
Meanwhile, the empirical data collected for this part of the study also allows
for an examination of how various key policy preferences may be associated
with a given RRM general approach (active or passive risk management).
8.2.1 Active regulatory risk management
8.2.1.1 Active risk management, inbound:
The rationale behind the first form of actively managing regulatory risk is to
strengthen the know-how of the investment team with regard to key clean
energy sector risks and uncertainties. This allows for two ways of inbound risk
management: 1) well-informed due diligence or ex-anti evaluation procedures
involving a specific look at regulatory risks, and 2) increasing the capacity of
the firm to react quickly to newly emerging regulatory opportunities and
challenges. The latter may include giving board seats to people with a strong
policy background.
"We create a strong advisory board for the portfolio company, preferably with
leads into the large corporates and utilities in the energy space."(#A11)
"The key is being aware of and responding to policy drivers."(#A20)
“We perform close controlling and coaching of our portfolio companies; we
take an active board seat, etc.” (#A06)
The former (regarding due diligence) is the most often applied strategy to deal
with regulatory risks. A few examples of how this is done are provided below:
“We don't take regulatory risk. We can get expertise by working with a big
partner investor or big fund.” (#A02)
“We manage regulatory risks the same way as for the other sectors: we
perform complete studies of the target & use the know-how of the investment
team.” (#A02)
“Don't take reg. risk. If company purely dependent on government grant,
wouldn't invest in it and has to have element to make money alone.” (#A05)
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“We estimate the cost reduction over time and when the technology can break-
even with power prices (when subsidies are no longer needed). If we see the
right progression, then it is fine.” (#A07)
We have broad expertise over many years. Each team member has specific
deep expertise, in a few areas. We also have connections to the best minds
globally, for further due diligence. (#A09) “We focus on select industry
segments in which we have particular knowledge and experience.” (#A12)
“We have knowledge about policies and how they impact our investments.”
(#A13)
“What percent of all investors consider policy? All of them. You have to
understand what the energy policy impact is going to be on your investment.”
(#A16)
“If a business is 100% based on policy, we have 3rd party consultants to do an
analysis of that.” (#A22)
Another inbound approach to active regulatory risk management is actually a
diversification approach with regard to regulatory risk specifically. The option
is to purposely invest in a portfolio of ventures in different countries in order to
primarily reduce regulatory risk. Funds in the passive RRM category may
undertake such an approach for other reasons, and the regulatory risk effects
are secondary in such a case. As clean energy policies still differ significantly
from country to country, and also the timing of legislative decisions with regard
to e.g. introducing or changing renewable energy support policies varies,
having a portfolio of companies acting in different jurisdictions is a good hedge
for regulatory risk.
"You can follow policy-making from Japan to California and that goes back to
the team and initial investment. You might have 3-4 countries where you are
betting on CO2 emissions policy in Europe and the United States (e.g.
California)." (#A10)
8.2.1.2 Active risk management, outbound:
The second form of actively managing regulatory risk is in a sense even more
proactive, in that the VC fund actively gets involved in the regulatory process
and tries to influence decision-making in the policy arena in a way that benefits
its portfolio companies.
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"We have several people working in groups that are involved in defining new
regulations. We actively manage regulatory risks. We are politically active as
investors. We ask for harmonisation of."(#A17)
"Also, one partner [in our fund] is involved in a political party."(#A19)
"Regulatory risk - we try to (…) influence the policy development getting as
much information as we can and also talking to the regulators themselves. We
meet 2 x a year with Policy-makers in the countries we invest in."(#A21)
In the context of this approach of active, outbound regulatory risk management,
we asked how often investors actually meet with policy makers. Figure 100
shows the results of this question, and uses the frequency of interaction with
the portfolio firms for comparison. It turns out that most VCs have rather rare
direct interactions (including meetings at industry conferences) with policy
makers. About 3/4 of the VCs meet with policy makers once a quarter or less.
On the other end of the spectrum, almost 10 % of investors indicated that they
interact with policy makers more than once a week or even almost every day.
An interesting finding with regard to these results is that the one type of fund
which meets with Policy-makers more often than they meet with portfolio
companies are funds that invest in late-stage clean energy deals. This
demonstrates the high importance of policy for especially later-stage clean
energy deals.
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1x/ quarte r 1x/ m onth every 1-2
weeks
2x/ week alm ost every
day
P artners m eeting with P olicy Make rs
S taff m eeting with P olicy Makers
P artners m eeting with com p anies
S taff m eeting with com panies
Figure 100: Frequency of direct interactions between VCs and policy makers vs.
portfolio companies
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Note: A significant number of funds answered N/A; these were not counted in
the average scores, N= 32
8.2.1.3 Detailed results on active RRM strategies
First of all, table A4-1 in the annex provides the answers by each respondent in
the active RRM category, to the RRM question in the survey and interview.
Table A4 -1 provides details about the type of fund, and the stage of focus for
each fund (two characteristics that the policy-analysis section had found
relevant to their views on policy). Names of firms and countries of location
were not provided as respondents were assured that the surveys and interviews
would be 100% confidential and that only very aggregate information would be
used in the reporting of results. Details on active RRM strategies have already
been discussed above.
8.2.2 Passive regulatory risk management
8.2.2.1 Fund-level, diversification across technology:
As for diversification, the first option is to deal with regulatory risk on the fund
level and invest in a portfolio of companies that represent different technology
segments. An example may be to invest in several clean energy technologies,
including solar, wind, biomass and fuel cells, which differ in the way that they
are dependent on policy support.
"Our portfolio companies are active (…) in different areas and technologies, so
this reduces the regulatory risk."(# P01)
“You need a portfolio approach with true diversifying factors” (# P02)
8.2.2.2 Firm-level, diversification across technology:
A distinction with regard to passive diversification can be made on the firm
level (defined in this section as the portfolio company level), as well as on the
fund-level. Two basic ways of diversifying on the firm level are possible:
across technologies and across countries. Fund managers often invest across
technologies or countries to mitigate other types of risks, but the effect is also
218

positive for regulatory risks. Of these two options, diversification across
technologies on the firm level is rare, especially in the case of early-stage
ventures that tend to be focused on a single technology. In a later stage of firm
development, diversification across technologies does become a possibility, for
example in the case of photovoltaic companies acquiring solar thermal energy
businesses, or wind energy project developers moving into biomass projects.
8.2.2.3 Firm-level, diversification across countries:
The more common form of diversification on the firm level is cross-country
diversification, or internationalization. This type of diversification approach is
taken to deal with country-level risks including regulatory risks. However, it is
also often employed to address other risks beyond regulatory risk, which
qualifies this approach under the passive category. Also, most firms that funds
invest in are active or plan to be active in more than one country, for market
reasons. Nevertheless, in terms of regulatory risk, the fund must check to be
sure that they are investing in a firm that is not 100% dependent on a policy in
a given country.
"Unless you are very comfortable about a particular legislation, you would
probably shy away from investing in a company that is 100% dependent on
policy in one country."(#P01)
"Our portfolio companies are active in different countries (…), so this reduces
the regulatory risk." (#P01)
Again, internationalization will typically occur in a later stage of company
development. However, there are also examples of very early
internationalization, as for example in the case of the VC-backed wave energy
company Ocean Power Delivery, headquartered in Scotland, but selling first
commercial products to Portugal due to the more favourable policy
environment.
8.2.2.4 Fund level, “getting in cheap”
On the fund-level, “getting in cheap” (#P01) is a strategy which fits especially
investors focused on smaller-scale investments. If a company “gets in cheap” it
will face less risk, but generally this approach is not taken by venture capitalists
because the assumption is that less risk also implies less potential payback.
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This is not always the case, however, as pointed out my one fund manager
focused on investments in developing countries, “Conventional due diligence
requires large transactions so large returns are expected. Our strategy is to
take more risk with a smaller transaction and see if it works. We believe in “Go
get me a rock” risk taking, not risk managing. This is simple, logical, etc. but
(this approach) has been buried (in the general practice)”. In these cases, it
will not be worthwhile to spend significant resources in due diligence to
“manage” regulatory risks. Going in cheap in many different deals is actually a
form of risk diversification but with a specific strategy attached.
8.2.2.5 Firm-level, choosing management for RRM
On the firm-level, regulatory risks can be managed by the venture’s
management team. This non-diversification strategy is not considered an active
approach to regulatory risk management because it is not the fund which is
actively managing risk, but the venture managers. The fund, however, is
making key decisions about the venture team managers that are best able to
adapt to change, as well as other aspects of the venture that may allow the
company to survive through regulatory changes. Other such “gate keeping”
involves financial and market-related criteria. Some fund managers that also
undertake active RRM strategies utilize this more passive approach, as well.
“...you need to have confidence in the venture's management team (that they
can make the necessary changes in the company if policy changes).” (#A10)
“We manage regulatory risk by sticking to our investment criteria” (#P04)
“If the management team lowers cost, increasing efficiency in the technology
(e.g. solar), you can win despite changes in regulatory issues.” (#A22)
“The management teams should be good.” (#A19)
8.2.2.6 Detailed results on passive RRM strategies
From the approaches provided in Table A4 - 2, one of the apparent differences
in this set of funds that pursue a more passive approach to regulatory risk
management is that they are generally either cleantech funds or general venture
capital funds. Cleantech funds are very similar to general VC funds in the sense
that they are often in the business of venture capital, but also in the sense that
their business model implies diversification across several areas, just like
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general funds. However, it is important to note that this general diversification
strategy taken at the designing of the fund in its formation years, is a business
decision made (most likely) prior to the funds’ formation of views on policies
and its evolution towards the funds’ current regulatory risk management
process. Also, these funds were designed mostly to address a variety of sectors,
so they must be designed to face a diverse set of relevant risks. Therefore, it is
proposed that cleantech and general VC funds tend to often pursue a passive
regulatory risk management approach as a result of the type of fund they are.
Furthermore, if they were less exposed to clean energy-related risks, it would
make sense that they do not pursue very active means of regulatory risk
management.
As for RRM strategies in the passive category, these funds appear to pursue the
chosen individual strategies more because they relate to their general method of
managing risks relevant to their portfolios, or because they related to: 1) their
key investment criteria (e.g. excellence in the management team), and 2) their
overall risk management strategy. It can be assumed that a fund’s investment
criteria and risk management strategy are defined even before the decision is
made to enter the clean energy sector, in these cases. Therefore, the emphasis
of a given fund on any given strategy in this category may be closely linked to
their firm’s basic firm or fund management characteristics, such as fund type,
firm type, core investors, stage of investment focus, etc.
8.2.3 Summary of regulatory risk management approaches
observed
To summarize, the choice of regulatory risk management options for a clean
energy fund manager which were found in the sample are (and listed according
to approximate order of significance in the sample):
1. Due diligence (Active, inbound) - become informed about policy and do
not invest in a deal unless you have thoroughly analyzed the potential
regulatory risks related to the deal and assessed that the risk is either low
or the deal has sufficient positive aspects, (e.g. the technology is on the
right cost-reduction path) to justify investing in it;
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2. Diversification on the fund-level (Passive or sometimes active, fund-
level) - ensure the fund targets several markets (countries and/or
technologies).
3. Be “hands on” (Active, inbound) – take a board seat on the portfolio
company or stay hands-on in another way in order to increase the
capacity of the firm to react quickly to newly emerging regulatory
opportunities and challenges. Possibly encourage the firm (your
portfolio company) to diversify regulatory risks via internationalization;
4. “Gate-keeping” (Passive, firm-level) - Choose excellent management
teams that can deal with policy changes;
5. Become politically active (Active, outbound)- influence the policy
environment for the entire portfolio of deals you manage in the clean
energy sector (or specific segments that the fund specializes in);
6. “Getting in cheap” (Passive, fund-level) - if you have little to lose, why
spend extensive resources on due diligence? Invest in several projects,
and see what happens.
8.3 RRM approaches analyzed by fund characteristics
8.3.1 RRM approaches by fund type and size
Besides the basic statistics shown in table 14 on fund type and investment
stages, an analysis of RRM strategies by a few other basic fund characteristics
and policy preferences is provided here. Before moving on, it is important to
note that the sample size is limited to the number of funds that answered the
regulatory risk management question (30 funds) as well as the relevant fund
characteristic question. For fund type the sample size is 30, but for other
characteristics featured below, the sample size is sometimes much smaller. It is
important to take this into account when interpreting the results. The sample
size is indicated in the notes for each figure. Indeed, not all characteristics are
covered here as the sample size was sometimes too small.
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8.3.1.1 Fund Type
The most important result was that dedicated clean energy funds were all active
(see Table 14 and Figure 101). This makes sense as they are entirely
concentrated on the clean energy sector and therefore must do everything
possible to manage the risks particular to this sector. Funds in the passive RRM
category were more often general VC funds or cleantech funds, as expected.
8
6
4
2
0
D C E C T F G V G P O ther
A ctive P assive
Figure 101: Regulatory risk management approaches by Fund Type
Note: y = number of funds in each category. N = 22 for active and N = 8 for
passive.
8.3.1.2 Fund Size
The size of the funds was also analyzed. The active category had a significantly
larger clean energy fund size (see figure 102). The proportion of clean energy
funding among the entire portfolio was also greater for those in the active
group (see figure 103). Indeed, funds focused on clean energy are more likely
to take a more active approach to managing regulatory risks, than a more
passive approach.
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200
180
160
140
120
100
80
60
40
20
0
Active Passive
Figure 102: Regulatory risk management approaches by average fund size.
Note: y= million Euros, N = 18 for active and N = 6 for passive.
18%
A ctive R R M
82%
Other
VC/PE
funding
CE!VC/PE
funding
P assive R R M
Figure 103: Proportion of clean energy funding for active (left) and passive
(right) RRM categories of funds
Note: N = 18 for active and N = 6 for passive.
8.3.2 RRM approach and other management aspects
This section analyzes in a more quantitative way the regulatory risk
management approaches by other fund management aspects.
8.3.2.1 Team backgrounds
The major difference shown in Figure 104 in terms of fund backgrounds is that
funds, which follow a more passive approach, are composed of investment
team members with more IT-related backgrounds than funds that are more
active with regard to RRM. Meanwhile, funds in the active category have more
team members with energy-related backgrounds. One way of actively
3%
97%
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managing regulatory risk may be to increase the investment team’s expertise
level in the energy sector. Also, a team with more experience in the energy
sector is more likely to recognize the difference between the energy sector and
other sectors and compose specialized approaches adapted to the sector.
Finance
Other
Consumer
5.0
4.0
3.0
2.0
1.0
0.0
IT
Science
Health
Active Passive
Other Ind.
Energy
Figure 104: Regulatory risk management approaches by Team Background
Note: 1 = not prevalent, 3 = somewhat prevalent, 5 = very prevalent. N=14 for
active, N=7 for passive.
8.3.3 RRM approach by clean energy hindering factors
Figure 105 shows a clear difference between perceived hindering factors
among funds that are more active and those that follow a more passive
approach. Among funds that were in the active category, the following factors
were relatively more important to them: long lead-time, lack of track record,
high capital expenditure, and less experience in the sector. In fact, funds that
are more active rate almost all hindering factors as more important, than funds
that follow a more passive approach. In particular, funds that take a passive
approach rated technology risk and lack of consistent government support for
clean energy slightly higher than funds in the active category. Perhaps fund
managers that take a passive approach feel they are not yet ready to invest more
heavily in the sector because policy is too inconsistent or they took on a passive
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approach because they do not believe that regulatory risk can be actively
managed because of inconsistent government support.
Institutional
investor interest
Less exp
5.0
4.0
track record
bad co. mgrs
3.0
lead time
Technology risk
Mrkt power of
incumb.
Gov. Comm.
2.0
1.0
deal flow
High capex
Active Passive
Lack trade sale
opp
FF Sub/No int.
Lack comp. VCs
Figure 105: Regulatory risk management approaches by Clean Energy
Hindering Factors
Note: N=14 for active, N=7 for passive
8.3.4 RRM approach and policy preferences
In this section, policy preferences of fund managers are compared to regulatory
risk management approaches. It must be noted that this data set is based only
on the number of funds that participated in the interviews and on-line survey
question on regulatory risk management. N=22 for the active category, and
N=8 for the passive category, however when combined with the data on policy
preferences sometimes the sample sizes reduced further. For example, only 6 of
the 8 funds in the passive category provided a rating from 0-5 for CO2
emissions trading. In some cases, funds also answered: “do not know”,
therefore these answers do not appear in the following analyses either.
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8.3.4.1 RRM approach by market-pull policies
One can see that funds in the active category like feed-in tariffs, renewable
portfolio standards, renewable fuel standards, and green certificate trading
slightly more than those in the passive category. Meanwhile, those that
undertake a more passive RRM approach prefer CO2 emissions trading and
CO2 tax, slightly more. This preference for CO2 trading and CO2 tax appeared
to be even more so when analyzing funds by whether they primarily
concentrated on the clean energy sector or diversified across several sectors as
part of their general investment strategy. So, this preference for CO2 emissions
trading may be more a result of the fact that the funds in the passive category
tend to diversify their investments in more general sectors, compared to those
in the active category.
CO2 tax
CO2 trading
CDM, JI
Red. FFS
certificate trading
procurement
5.0
4.0
3.0
2.0
1.0
0.0
RFS
Feed-in tariff
RPS
Active Passive
Res and comm tax
credits
PTC
Tech perf.
standards
Figure 106: Market-Pull policy preferences by regulatory risk management
approaches
Note: N=20-22 for active, N=6-7 for passive (range of N depending on the
policy)
Figure 107 shows that funds in the active category gave CO2 emissions trading
marks between 2 and 4, but a higher percentage rated CO2 emissions trading
with a very low mark of 2. In fact, there was not enough data for the passive
category to show any preference.
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10
8
6
4
2
0
1 2 3 4 5
Active Passive
Figure 107: Number of funds that rated CO2 emissions trading 1-5 for
regulatory risk management approaches
Note: N=22 for active, N=6 for passive
As for feed-in tariffs, among the 22 funds in the active category, 14 funds rated
FiTs with a 5, showing a high preference for FiTs. The majority of the funds in
the passive category rated FiTs with a 4. Therefore, we have seen that, funds in
the active category favor FiTs slightly more while they do not favor CO2
emissions trading as much. One fund manager that focuses on cleantech
investments and significantly funds clean energy deals, said: “…it is sometimes
hard to see the linkage of the ETS and a company we invest in. There is not a
lot of impact on our little investments. It impacts more the investment
environment, than the actual investments.”
8.3.4.2 RRM approach by technology-push policies
Funds that are more passive with regard to regulatory risk tend to like
government grants for demonstration plants, grants for SMEs, and investment
subsidies much more than funds that are more active.
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Tax brks inv.
Govt. inv. priv VC
Inv. Subsidies
Government VC
funds
Gov demo grants
R&D pub.
5.0
4.0
3.0
2.0
1.0
0.0
R&D priv.
Grants for SMEs
Active Passive
Soft support
Incubators
Tax brks entre
Figure 108: Technology-Push policy preferences by regulatory risk
management approaches
Note: N=19-22 for active (depending on the policy), N=7 for passive
They also found incubators more effective than funds in the active category. It
appears that funds that take a passive approach to regulatory risk management
believe much more in government involvement very early in the innovation
chain. Combining this result with the results for market-pull policies, we can
ask ourselves whether funds which prefer market-pull policies to technology-
push policies, and take an active regulatory risk management approach, have
taken this view and strategy because they deal with larger clean energy funds
and are slightly more involved in later-stage deals which market-pull policies
best apply to and which imply greater risks needing to be managed more
actively.
8.4 Conclusions on RRM approaches
We have seen that policy and regulatory risk is an important factor in the risk
management decisions of clean energy fund managers. One investor clearly
noted: “At the core of any innovation in energy, it is policy driven.” We have
also found that certain types of investors study every detail of a given deal
before investing, and therefore will not invest if they find policy is too great of
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a risk. Such investors often concentrate on particular clean energy segments
that they know best. Sometimes investors are active politically in order to stay
informed or influence policy-making. We call this category the “active
regulatory risk management approach”.
Another type of investor deals with regulatory risk more passively either by
diversifying on the fund level of “getting in cheap” or by “gate keeping” and
choosing deals according to the usual practice with the idea that the regulatory
risks will be dealt with on the firm-level (portfolio company-level).
Diversification on the fund-level can occur via different more general sectors,
cleantech sectors, or clean energy segments (technologies). They may also
diversify by geography on the firm level (or internationalization) 95 . Also, when
fund managers believe it is impossible to predict policy changes, they may
invest in companies according to their typical procedure. They expect that the
management teams and technologies they invest in will survive through
changes in policy because they carefully choose their management teams.
Meanwhile, although a concentration investment strategy (concentrating on
specific segments of the clean energy sector) generally implies a more active
regulatory risk management strategy, fund managers in the passive category
may also concentrate their investments in clean technologies (cleantech), but
they are placed in the passive category because they emphasize that they do not
commit new or different resources and strategies to dealing with the risks that
may be associated with various policies influencing a particular deal’s risks and
opportunities. They do not select out regulatory risk from a deal when they
evaluate deals, and they do not adapt their investment strategy or management
practices specifically in order to address risks particular to the clean energy
sector, such as regulatory risk. Such investors say that they treat clean energy
deals like other types of deals. We have seen this approach is particularly
prevalent among small funds in large firms.
While there are grey areas and sub-categories of risk management approaches
among the funds studied, we have found that in general funds that concentrate,
95 Note that geographical diversification on the fund-level would be considered a more active approach
if it is conducted on purpose to manage regulatory risks, and not as a result of the typical portfolio
diversification practice.
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and are actively managing regulatory risks, invest substantial resources ex-anti
to the investment in order to minimize regulatory risks faced by the fund. This
is the most prevalent strategy among the fund managers in the sample, but this
may be a result of the sample characteristics – that is the sample includes funds
with significant business interests in particularly the clean energy sector. As the
stakes are higher for larger clean energy funds, naturally the level of activity in
risk management with regard to sector-specific risks (such as regulatory risk)
call for a more significant investment in the ex-anti deal evaluation process.
Finally, it was found that for those in the passive RRM category, RRM is a
more unintended consequence of their overall investment strategy -to highly
diversify one’s portfolio of investments in a variety of sectors, countries,
segments of the sector or across various parts of a given segments’ value chain.
Indeed, a number of fund characteristics appeared to be associated with the two
identified approaches. For example, funds that tended to actively manage
regulatory risks were usually dedicated clean energy funds or private equity
funds involved in expansion-stage investments. This makes sense because
dedicated clean energy funds have greater stakes in the clean energy industry,
in general. Cleantech funds will be more aware and concerned about policies
than general VC funds, but in many ways they are similar to general VC funds
because they also diversify across several different cleantech sectors and
thereby they can diversify regulatory risks in this way. Therefore, it makes
sense that funds that tended to more passively manage regulatory risks were
general VC funds (and some general private equity funds) or cleantech funds.
Therefore, it is proposed that the chosen fund type has the greatest influence on
the funds’ views about policy and regulatory risk management approach taken,
as it influences the funds’ level of focus on the sector, the level of benefit the
fund will receive from active RRM, and their level of exposure to regulatory
risk.
Stage of investment focus also naturally influences the level of regulatory risk
relevant to each individual clean energy deal. As for stage of focus, a variety of
stages were being financed for the funds in the passive category. But the
expansion stage was relatively more important in the active category and the
earlier stages like seed and start-up finance were relatively more important in
the passive category. This makes sense as it was hypothesized earlier that
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private equity and expansion-stage-focused funds will also have higher stakes
in each individual clean energy deal, meaning ex-anti strategies such as an in-
depth due diligence process will be their typical strategy. Backgrounds in the
fund management team and exposure to Policy-makers and portfolio companies
will also affect the general way that the fund views government intervention in
the market. It is expected to affect the level of reliance the fund is willing to
have on favorable policy environments. Professional backgrounds did prove to
show an association, for example between teams with a high prevalence of
members with energy backgrounds and an active RRM choice.
Various views of fund managers also appear to relate to regulatory risk
management choices. For example, views on hindering factors were associated
with different RRM approaches. Funds with a more active approach to
regulatory risk management had rated several hindering factors as much more
important in their minds, compared to funds in the passive category. Key
hindering factors they mentioned were: high capital expenditure and longer
lead-time for clean energy ventures, and lack of a track record for clean energy
deals. Meanwhile, funds in the passive category rated technology risk as much
higher in comparison to the active category. This implies that those in the
passive category believe the real barriers are related to technological risks,
which can not be addressed by market-pull policies, hence this explains their
policy views as well. Relating this finding to their views on policy, funds
which took a more passive approach to regulatory risk management also tended
to favor a few of the technology-push options (such as government grants)
slightly more than funds in the active category. This is no surprise, again, as
investors which view technology risk as high should be relatively more
interested in government grants for research and development of technologies,
than policies which more directly affect the technology deployment stages and
only indirectly affect the early innovation stages of technology.
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9 Overall Conclusion
Few academic studies in the energy policy literature have considered venture
investors’ views in order to assess the effectiveness of policies in terms of
stimulation of technological innovation, regardless of the fact that venture
capital investors are important players in the innovation chain. Using empirical
data collected on 60 private equity funds via surveys and interviews held with
fund managers, this thesis has combined a conceptual analysis of policy with an
empirical data analysis to answer research questions on how policy impacts
both investors’ investment decisions and their regulatory risk management
practices.
9.1 Conclusions for Policy-Makers
To begin with, a number of key market drivers and hindering factors were
identified in this work. It is proposed by this thesis that they work to moderate
investors’ interest to invest in innovative clean energy technology ventures, as
well as their views on policies and their regulatory risk management
approaches. Key drivers identified (in the following order) were: 1) competitive
advantage, 2) security of energy supply, and 3) climate change. From the
interviews conducted for this study, one can gather that changes in the energy
market are themselves driving policy changes, and these policy changes
(related to energy and climate change), combined with core market trends are
now together working to drive investment in the clean energy market.
Meanwhile, perceived drivers varied slightly for different funds. For example,
North American-focused (and based) funds viewed climate change as less
important than European-focused (and based) funds. This makes sense given
the difference in policy environment, but there are signs that climate change
will become a more important driver in the United States in the coming years.
The most important hindering factors identified by this study were (in the
following order): 1) high capital expenditure involved in VC & later-stage
private equity clean energy deals, 2) lack of track record for clean energy deals,
and 3) longer lead time for clean energy deals compared to IT or other
traditional VC sectors. In the interviews, regulatory uncertainty was also a
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common concern, however most fund managers interviewed noted that the key
drivers for policy-making were not going to go away, which gave them some
level of comfort despite regulatory uncertainty in this market.
Overall, the results confirm that although regulatory uncertainty is a concern
for clean energy venture investors, on the whole, they believe market-pull and
technology-push policies provide more of an up side than a down-side for
investors, or more opportunities than risks. This was shown by scores higher
than 3 (out of 5) for all the market-pull policies and almost all the technology-
push policies. A rating of “no effect” was also an option, so the results indeed
indicate that all the policies have a positive effect on investors’ interest to
invest in clean energy ventures, with some policies having a much higher
positive effect than others. Feed-in tariffs received the highest rating for
effectiveness in stimulating investors’ interest to invest in the sector. More
specifically, funds that more actively manage regulatory risks also preferred
feed-in tariffs. Meanwhile, many investors interviewed said they supported a
wider application of incentive schemes for renewable energy such as feed-in
tariffs, but recognized that they should be applied only for a fixed period of
time, or until new technologies move up the “learning curve” and become
competitive without such supportive policy environments.
However, fund managers expressed a common concern about regulatory
uncertainty in the clean energy market. Several fund managers said they would
never invest in a portfolio company if it were 100% dependent on a given
policy. In this case, investors consider the “base case” (or the “no government
intervention” case) in their evaluations of a deal. This may imply on one hand
that policy does not always increase the chances of obtaining finance. On the
other hand, policy is generally viewed as providing an upside to clean energy
technology deals.
Finally, investors called for consistency in policy-making to reduce their
perception of uncertainty in the clean energy market. Some even preferred an
imperfect stable policy environment to an instable environment caused by the
pursuit of what would be the perfect policy option.
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More specific policy-relevant findings are:
! Feed-in tariffs were the most favored policy type among VC/PE fund
managers to stimulate continued finance of innovative clean energy
technology ventures. Fund managers (U.S. and European) also
mentioned Germany was the best policy environment for solar PV
technology. The empirical data therefore supports the literature review’s
expectations with regard to feed-in tariffs.
! Overall, market-pull policies were preferred over technology-push
policies, except that government grants for demonstration projects were
considered more important than all other market-pull instruments apart
from feed-in tariffs.
! Stage of investment focus, fund type, fund size, firm size and
geographical focus and location were the most relevant fund
characteristics found to associate with fund managers’ views about
policies. It is therefore proposed in this exploratory work that these key
factors play an important role in influencing their views and
management decisions. For example, North American-focused funds
were much more concerned about the reduction of fossil fuel subsidies
and increasing R&D spending than European-focused funds. Meanwhile,
European-focused funds responded more positively to market-pull
policies overall, than North American-focused funds. Larger fund sizes
tended to be more actively managing regulatory risks relevant to the
sector, and smaller-sized funds with less concentration in the clean
energy market were more agnostic to policy. A number of other
associations and possible explanations have been discussed in this thesis.
! Overall, CO2 emissions trading received mixed scores, resulting in an
overall score that is among the lowest of all policies. CDM/JI also
received very low overall scores with regard to stimulation of VC/PE
investment in innovative or “less mature” clean energy technologies.
Several fund managers interviewed explained that CO2 emissions
trading schemes do not directly impact their investments in innovative
clean energy technologies. CDM/JI is intended to encourage investment
in the “low hanging fruits” among CO2 mitigating technologies, so one
could expect the lower overall scores received for CO2 emissions
trading and CDM/JI.
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! On average, sector-based international agreements were the preferred
international agreement type among most funds, and the overall
satisfaction level among funds was extremely low with regard to
regulatory issues implying that improved regulatory support for
renewable electricity is extremely important. “Good handling of
regulatory issues is actually a pre-requisite” according to one
interviewee.
In conclusion, a combination of well-designed policies is critical to stimulating
VC/PE investment along the entire innovation chain. The most important
overall characteristic is that policies should be consistent (long-term) in order
to reduce investor-related uncertainty. However, more specifically the findings
in this thesis call for the implementation of a combination of both market-pull
and technology-push policies along the innovation chain. Policy-makers may
consider implementing the following combination of policies for the electricity
sector, if the goal is to stimulate in particular VC/PE investment in less mature
clean energy technology ventures: increase R&D spending, fund demonstration
plants or projects via direct grants, apply feed-in tariffs, improve the handling
of regulatory issues (grid access, siting and net-metering), apply a sector-based
international policy together with the Kyoto Protocol, and reduce or eliminate
fossil fuel subsidies. It is proposed that the implementation of such policy
environments would lead to further growth in VC/PE finance in the clean
energy sector, as policies help overcome key market hindering factors and risks,
and in particular reduce investors’ perceived level of uncertainty around the
market adoption of innovative clean energy technologies.
9.2 Conclusions on Regulatory Risk Management
There are two different forms and consequences of regulatory uncertainty. One
is the uncertainty imposed on industry because of looming potential changes in
a general energy policy environment (e.g. the introduction of an eventual
carbon pricing scheme). The other is the uncertainty regarding future changes
in incentive structures for clean energy technology deployment. The second
type of regulatory uncertainty (or regulatory risk) was the general focus of this
work.
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Regulatory risk management for this second type of uncertainty was identified
via empirical data collected from interviews with clean energy fund managers,
and an open survey question. The responses included various forms of active
and passive strategies. When fund managers appeared to actively get informed,
or use specialized resources for due-diligence, or actively engage in policy-
making, this indicated an active approach to regulatory risk management.
Among those that dealt with regulatory risks more passively, there were a
number of funds that dealt with regulatory risks primarily via risk
diversification across a portfolio of investment types. Another more specific
passive strategy is to deal with regulatory risk on the portfolio company level,
as opposed to the portfolio fund level. In such a case, investment criteria such
as a high quality venture management team were found to be important.
Finally, in hypotheses built from the literature review, certain characteristics of
funds were correlated with policy views, and chosen regulatory risk
management approaches. A combined quantitative (via survey data) and
qualitative exploration (interviews) of fund characteristics showed that the
following were of highest relevance: stage of investment, fund type and
fund/firm size. For example, later-stage private equity fund managers (e.g.
expansion stage-focused investors) were expected to be more active in the
management of regulatory risks relevant to their clean energy investments, and
this was confirmed in the empirical findings. In fact, funds which had
significant clean energy allocations and which were focused on the expansion
stages were the most concerned about market deployment policies and were
also active in the management of regulatory risks. Small-sized funds within
small-sized firms were more agnostic to policy in general, and had a more
passive approach to regulatory risk management. In addition, cleantech and
general VC funds were slightly more agnostic to policy compared to other fund
types, such as dedicated clean energy funds and general private equity funds, as
expected. Cleantech and general VC funds were also prevalent among funds
that more passively approached regulatory risk management. This is
understandable because investors in this category have less to lose from clean
energy deals, in proportion to their total fund portfolios of VC/PE investments,
especially when they have very small portions of funds allocated to the clean
energy sector.
237

Therefore, it is proposed that the way that funds deal with regulatory risks is
influenced by a few key characteristics. For example, their fund type will
influence their focus and the level of stakes involved in a given clean energy
deal. Their skills or backgrounds in the fund management team will affect the
general way that the fund views government intervention in the market and
therefore, the level of reliance on favorable policy environments (level of
regulatory risk management) that the fund managers are willing to take. But
backgrounds of investment teams are more a function of fund type,
emphasizing the importance of fund type to the regulatory risk management
approach of a fund.
It is also proposed that fund managers’ policy views may impact their RRM
approaches taken, and vice versa. For example, funds that found feed-in tariffs
effective tended to be more active fund managers with regard to regulatory
risks. Perhaps because they are more active and concentrated in the clean
energy industry, they have recognized that they have more to loose from risks
like price uncertainty in the energy market, and therefore developed their
policy preference as a result of their experience and exposure to entrepreneurs
dealing with these issues everyday. However, it appears that the causal
relationship described is derived mostly from the original type of fund chosen
which than determines the best regulatory risk management approach, as well
as the fund characteristics, such as team backgrounds, that will most likely lead
to a given policy preference.
Finally, this thesis proposes that the initial choices with regard to 1) fund type,
2) choice of investment stage-focus and 3) the amount of funding allocated to
clean energy deals (i.e. level of focus on clean energy) are the most influential
factors that determine a fund’s views on policy and their regulatory risk
management approaches. Fund managers’ experience with clean energy
investment and exposure to relevant policies appears to cause a feedback
influence on the evolution of their regulatory risk management approach over
time. It is a back-and-forth process of influence, but the funds’ original
preferences and strategies originate from the most basic fund characteristics,
such as fund type, fund size and stage of investment focus.
238

10 Limitations and Further Research
The results and propositions developed from this exploratory research are
based on a significant, but still rather limited number of structured surveys and
semi-structured qualitative interviews with venture capitalists and private
equity fund managers. Further research with an even larger sample can help to
assess the relative importance of the identified regulatory risk management
strategies, policy preferences, and the proposed cause and effect relationships
between them. Also, fund managers were the main source of information for
our categorization of regulatory risk management strategies. Surveying the
management teams of entrepreneurial firms would be a valuable extension of
this research. In addition, this study chose to focus on a fund-level of analysis.
A different study design could focus on the individual-level of analysis in order
to asses the potential for personal biases and other heuristic variables which
play a role in forming the opinions of the team members in a given investment
fund, or firm. Finally, a selected number of longitudinal case studies that
ideally could also be compared with longitudinal performance data might be
useful to assess the success of certain regulatory risk management strategies in
coping with unexpected changes of the policy environment. A longitudinal
study of fund managers’ investments in clean energy technology ventures and
changes in policy environments could also provide further support to the
proposition that certain policies like feed-in tariffs indeed lead venture capital
and private equity investors to participate more in the clean energy market, as
this proposed in this thesis.
239

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255

Annex 1: Survey Questions 96
The University of St. Gallen is a leading European business school.
Questionnaire on Clean Energy Private Equity and Public Policy
Thank you for your important contribution to our research on Private Equity
investor's perceptions about Climate and Clean Energy policies. This
survey takes 15 minutes to complete. It is intended for private equity
fund managers and advisers which manage Clean Energy private
equity investments. Our goal is to learn more about different types of
investors' policy perceptions, inform Policy-makers in Europe, and
contribute to the environmental management field.
You do not have to answer every question, but we do request that you
provide us with at least the type of fund you manage and the name of your
firm so that we can track responses to our survey. All responses will
be 100% confidential. Only aggregate responses will be made available
in our reports.
At the end of the survey you can choose whether you would like to
provide further contact details to allow us to send you a free copy of the
exclusive results in an Executive Summary format (we estimate about 10
pages of graphics) in the spring of 2007. You are also welcome to receive
a free copy of our final report.
Also, if you are interested to know more about how the responses will be
used in our study, please contact Mary Jean Bürer at
maryjean.burer@unisg.ch
Thank you once again for 15 minutes of your time. We hope that obtaining
our study's results for free, in return, will make it worth the time you have
invested.
Yours Sincerely,
Mary Jean Bürer, Research Associate, Institute for Economy and the
Environment, and Visiting Scholar at the College of Management of
96 The same questions in the on-line survey were used for the telephone and in-person interviews. The
shorter survey distributed at the Cleantech Venture Network conference in San Francisco was
composed of just two pages including the questions on market-pull, technology-push, international
policies, drivers, and investment criteria. These questions were composed in exactly the same way as
seen here (for the on-line survey). This select set of policy questions for the shorter survey was chosen
as they were considered the most important questions for the study. Drivers with investment criteria
were two simple questions which were chosen as well in order to analyze the data collected from this
mostly U.S.-based sample of funds. Informal interviews were also conducted at the CTN conference
(on the side-lines) to understand how funds manage regulatory risks relevant to the sector.
256

Technology (CDM), Swiss Federal Institute of Technology (EPFL)
& Dr. Rolf Wüstenhagen, Vice-Director, Institute for Economy and the
Environment
University of St. Gallen
More information about our research can be found at:
www.iwoe.unisg.ch/VC We would like to also thank the Chair of Corporate
Strategy and Innovation at EPFL (http://cdm.epfl.ch/homepage.php) for
supporting our research, and for use of EPFL's Feedback Server software
for this on-line survey.
Note: For this study, "Clean Energy" means your firm's private equity (PE)
or venture capital (VC) investments in renewable energy technologies, as
well as fuel cells, energy storage and hydrogen from renewables.
Attn: Please use the "save progress" button if you plan to take your time to
fill-in the questionnaire. This will avoid any loss of information if there is a
server error and it allows you to resume progress at a later time. In order to
do so, "cookies" should be enabled.
Also Note: "Restore previous answers" should only be clicked when you
have already submitted the survey and you would like to change your
answers at a later time.
Your Policy Views
Note: If the following have no effect on your investments, please check "no effect".
1. First, has your firm ever invested (private equity) in companies in the
business of clean energy technology?
yes
no
2. Has your firm ever investigated relevant sustainable energy policies and
their possible effects on your firm's clean energy investment opportunities?
yes
no
not certain
3. Do you believe that nuclear energy is a competing alternative which could
substantially reduce renewable energy deployment?
257

yes
no
don't know
4. Energy & Climate Policies - In your opinion, for the following sustainable
energy and climate change policies, how do you rate them 1-5 (your highest
preference being 5), with regard to private equity (PE) and venture capital (VC)
investments in Clean Energy? (Note: Please consider for example the solar
energy market when answering these questions, as opposed to more mature
clean energy markets such as wind energy.)
Feed-in tariffs (e.g. subsidies for renewable
energy market take-up)
Reduction of fossil fuel subsidies
GHG or CO2 emissions trading
Renewable Portfolio Standards (RPS)
Renewable fuel standards or targets
Green (renewable energy) quotas and
certificate trading
General CO2 tax or energy tax
Residential and commercial tax credits for
RE
Kyoto Mechanisms (e.g. CDM, JI)
Government procurement of clean energy
Production tax credits (e.g. for wind)
Technology performance standards (eg.
vehicle pollution standards)
1 2 3 4 5 No
effect
Don't
know
5. Would your answers to the above questions with regard to national policy
options be significantly different if you were to answer them taking into
consideration a more mature clean energy market like the wind energy
market?
yes
no
6. Innovation Policies - In your opinion, for the following policies and
instruments, how do you rate them (1-5), your highest preference being 5, with
258

egard to private equity (PE) and venture capital (VC) investments in Clean
Energy? (Note: Please consider all clean energy sectors to answer this
question)
Tax breaks for clean energy investors
Government VC funds
Government investment in private VC funds
Investment subsidies for entrepreneurial firms
(e.g. to set up manufacturing facilities)
Soft support measures (e.g. coaching for
entrepreneurs, business plan competitions)
Incubators/technoparks
Tax breaks for entrepreneurial firms
Government grants or other financial support
for pilot and demonstration plants
Doubling public R&D spending for private
institutions
Doubling public R&D spending for public
institutions (e.g. technical universities)
Grants for SMEs or communities to install
equipment
1 2 3 4 5 No
effect
Don't
know
7. Current handling of regulatory issues - In your opinion, given the current
handling of the following regulatory issues around the regions in which your
invested companies operate, how do you rate your satisfaction 1-5, (with
your highest level of satisfaction being 5), with regard to private equity
(PE) and venture capital (VC) investments in all types of Clean Energy (for
example, both wind and solar investments)?
Siting policies (eg. for onshore wind)
Grid access
Net metering regulations (for trading
surplus electricity)
1 2 3 4 5 No
effect
Don't
know
259

8. International agreements to promote all types of Clean Energy - which
approach do you prefer, assuming they have some effect on your interest to
invest in the sector?
(If they have no effect, please click "no effect")
Extension of and focus on the Kyoto Protocol
Agreements to increase R&D and technology cooperation
Sector-by-sector energy-related agreements (eg. subsidy reform or clean energy
targets)
no preference (all of the above)
No effect on our investments
N/A, no opinion, or don't know
9. Some investors say that climate and energy policies should be "LOUD,
LONG AND LEGAL".
What specific views would you like to add to the debate about which types of
policies, and which general characteristics of policies, are most important to
stimulate further investment in Clean Energy?
Your Investment Criteria, Drivers and Hindering Factors
10. Please state up to five of your firm's key investment criteria for private
equity or venture capital investments in Clean Energy technology
companies, and as much as possible in their order of importance.
Criterion 1
Criterion 2
Criterion 3
Criterion 4
Criterion 5
11. How do you rank the following drivers for Clean Energy investments (1-
4, where 1 is the most important)?
Air pollution or other health concerns
Climate Change
Security of energy supply
Competitive advantage
260

12. Recognising that Clean Energy is an emerging investment space, what
constraints do you see on the growth of Clean Energy as a private
equity investment category?
Less experience in new
investment space; will take
some time to grow
Technology risk (e.g. that
another technology will
dominate)
Institutional investor interest
Lack of a track record of
successful Clean Energy exits
Longer technology lead times
compared to e.g. internet
companies
Large energy corporations as
potential trade sale buyers lack
a venturing culture (unlike e.g.
big pharma)
Lack of internalisation of
external cost, subsidies for
conventional energies
Lack of competent VCs
Lack of competent venture
managers for deals
High capital expenditure and
long investment cycles in the
energy sector
Not enough good deal flow (low
supply of good Clean Energy
investment options)
Not enough consistent
government commitment to
sustainable energy
Market power of incumbent
energy providers (increasing
difficulty to enter the market)
1 of no
importance
2 3 somewhat
important
Your Region Focus & Policy Environment Preferences
4 5 very
important
13. Which general regions does your firm focus its Clean Energy investments
on?
Europe
North America
N/A
261

Asia
Latin America
Africa
Australia/New Zealand
Other
14. Which country do you generally view as offering the best (or one of the
best sets of) government incentives or policies for PE and VC investment for
each Clean Energy investment space mentioned below?
for PV [Select Country]
for solar thermal [Select Country]
for wind [Select Country]
for geothermal [Select Country]
for marine [Select Country]
for biomass for power [Select Country]
for biofuels for transport [Select Country]
for stationary fuel cells [Select Country]
for fuel cells (for transport) [Select Country]
for energy storage [Select Country]
for hydrogen from renewables [Select Country]
15. Clean energy investment has taken off last year in most regions of the
world. But venture capital and private equity investment appears to have been
the largest in the US (larger than for Europe). How would you explain this?
Your Investment Stage, Exit and Space Preferences
16. Which stage(s) does your firm focus on most?
Seed capital
Start-up
Expansion
Replacement Capital
Buyout
262

17. What is your typical time to exit (e.g. IPO or trade sale) for Clean Energy
companies?
1-2 years
3-4 years
5-6 years
7-8 years
9-10 years
10-11 years
12-13 years
more than 14 years
N/A
18. Please indicate the number of investments that your fund has done for
each Clean Energy technology area.
PV
Solar thermal
Wind
Geothermal
Marine (Wave and Tidal Energy)
Biomass for power
Biofuels for transport
Stationary Fuel Cells
Fuel cells (for transport)
Energy storage
Hydrogen from renewables
263

Your Information Sources and Risk Management
19. How often does your firm interact with the following?
Partners meeting with
policy-makers
Staff meeting with policymakers
Partners meeting with your
typical Clean Energy
company
Staff meeting with your
typical Clean Energy
company
1x / quarter,
or less
About 1x/
month
Every 1-2
weeks
2x a
week
Almost
every day
20. How influential are the following information sources with regard to your
investment decisions on Clean Energy VC and PE?
Institutional
Investors
Other fund
managers
Corporate buyers
Final consumers
or users in the
market
Advisers on
technology
Internal staff
intelligence
Financial
consultants
Investment
banking reports
Other specialised
industry reports
News media
1 not at all
important
2 rather
unimportant
3 somewhat
important
4
important
5 very
important
N/A
don't
know
21. How does your firm manage risks particular to Clean Energy investments
(e.g. regulatory risks)?
264

Your Capital Under Management
22. Approximately how much capital in Euros is currently managed by your
firm for all PE and VC?
0-5 Million
5-10 Million
10-20 Million
20-50 Million
50-100 Million
100-250 Million
250-500 Million
500-1000 Milion
1-2.5 Billion
2.5 - 5 Billion
> 5 Billion
N/A
Approx. amount, if known
23. Approximately how much capital in Euros is currently managed by your
firm only for Clean Energy PE and VC?
0-5 Million
5-10 Million
10-20 Million
20-50 Million
50-100 Million
100-250 Million
250-500 Million
500-1000 Million
N/A
Approx. amount, if known
265

24. By how much do you expect your firm's Clean Energy investment level to
increase by 2015?
0
0-20%
20-40%
40-60%
60-80%
80-100%
more than 100%
N/A
Your Clean Energy Investment Experience
25. Approximately when did your firm begin investing PE or VC in Clean
Energy companies?
Pre-1990
Pre-2000
2000-2001
2002-2003
2004-2005
2006
N/A
Exact date, if known
26. Approximately when was your firm's last PE or VC investment in a Clean
Energy company?
Pre-1990
Pre-2000
2000-01
2002-3
2004-5
266

2006
N/A
Exact date, if known
Your Firm and Fund Type
27. What best describes your firm's type?
GP - Independent (no parent)
GP - Subsidiary of Private Equity Group
GP - Corporate venturer - Industrial Company
LP - Corporate Investor
LP - Bank
GP - Bank subsidiary
GP - Insurance Company Subsidiary
LP - Fund of Funds
GP - Government
Other
Please specify
28. What describes your Clean Energy fund best? If you have more than one
fund, please answer for the one with the strongest clean energy exposure.
Dedicated Clean Energy Fund
CleanTech Fund (including energy, water...)
General VC Fund with significant Clean Energy allocation
General VC Fund with some Clean Energy allocation
General VC Fund without Clean Energy allocation or investments
General PE Fund with significant Clean Energy investments
General PE Fund with some Clean Energy investments
General PE Fund without Clean Energy investments
Other
267

Please specify
29. Please choose the main types of investors which invest in your Clean
Energy-related investments.
Corporate investors
Private individuals
Banks
Pension Funds
Insurance companies
Funds of funds
Government agencies
Academic institutions
Foundations
Not applicable (in case your fund has no clean energy investments)
30. In how many of the funding rounds for Clean Energy companies that your
firm invested in, has your fund been the lead investor?
none
a few
many
almost all
Your Team and Contact Information
31. Of the following backgrounds, please rate their prevalence in your senior
team involved in Clean Energy investments.
IT-related
Health-related
Energy-related
1 Not
prevalent
2 3 Somewhat
prevalent
4 5 Very
prevalent
268

Other industrialrelated
Science-related
Consumer-related
Finance-related
Other
32. Please select your function in the firm.
Director, Partner, or similar
Investment Manager, Investment Analyst, or similar
33. Please enter the following details about your firm. Providing us with your
contact information will enable us to send you the Executive Summary of the
results.
Firm Name
Website
Your email address
Telephone
Street address
City
State, if applicable
Zip code
Country [Select Country]
34. Further Information
Check here if you would be available for a 15-20 minutes follow-up interview by phone
Check here if you would like an Executive Summary and the full report of results sent
to your office
Your first name
Your last name
Your position
269

Annex 2: Fund characteristics defined
Basic characteristics
For any thorough analysis of policy views or regulatory risk management
approaches, it was considered of key importance to differentiate between clean
energy stages of focus, as well as other basic characteristics such as country of
management, fund type and firm type assuming that these would have a big
influence on the views and practices of the firm because of set way of thinking
or set strategies among the funds and firms. Similarly, core investors in the
funds may influence the fund managers because they provide the financial
resources for the fund, but also because they may be sources of information and
bias, for example they may have expressed an interest to see the fund invest in
certain strategic areas relevant to the core investor such as particular clean
energy segments or technologies. Finally, the fund size and firm size will be
relevant assuming that the more a fund is committed to clean energy financially,
the more it may perceive particular levels of risks and opportunities relevant to
that sector.
CE stages focus
Funds focus on different investment stages. Stages investigated in this work
include (definitions are provided in EVCA, 2006):
o Seed capital – financing provided to research, assess and develop an
initial concept before a business has reached the start-up phase.
o Start-up – financing provided to companies for product development
and initial marketing. Companies may be in the process of being set up
or may have been in business for a short time, but have not sold their
product commercially.
(Note: Other early-stage refers to financing to companies that have
completed the product development stage and require further funds to
initiate commercial manufacturing and sales. They will not yet be
generating a profit.
o Expansion – financing provided for the growth and expansion of an
operating company, which may or may not be breaking even or trading
profitably. Capital may be used to finance increased production, market
or product development, and/or to provide additional working capital.
270

Under the regrouped Expansion category are the following: Expansion,
Bridge Financing – financing made available to a company in the period
of transition from being privately owned to being publicly quoted,
Rescue/Turnaround – financing made available to existing business
which has experienced trading difficulties, with a view to re-establishing
prosperity.
o Buy-out – financing provided to enable current operating management
and investors to acquire existing product line or business. Within the
regrouped category Buy-outs the following are also considered:
Management Buyout, Management Buy-in (financing provided to enable
a manager or group of managers from outside the company to buy-in to
the company with the support of private equity investors), and Venture
Purchase of Quoted Shares (purchase of quoted shares with the purpose
of delisting the company).
o Replacement Capital – (or Secondary Purchase) – Purchase of existing
shares in a company from another private equity investment
organization or from another shareholder or shareholders. Within the
regrouped category Replacement Capital the following are considered:
Secondary Purchase/Replacement Capital, and Refinancing Bank Debt
(to reduce a company’s level of gearing).
Note: In the survey, funds could choose from among a variety of the above
stages, because the reality is that most funds invest across more than one stage.
This means that there was a multitude of different combinations in the results.
For ease of reporting they were combined into easier to use categories.
Therefore seed-stage and start-up investors only were combined in one
category. Investors which invested in expansion stages (even if they also
invested in start-up stages as well) were included in the expansion stage
category. Later-stage was defined as buy-out and replacement capital, but many
of these fund managers also invested in the expansion stage.
Country of management
In this study, the location of the fund’s corporate office is classified as: the
U.S., Great Britain, and EU + Other OECD.
271

Fund type
The categories chosen for fund type include:
o Dedicated clean energy funds (DCE) – these are funds dedicated to
funding clean energy technology ventures only
o Cleantech funds (CTF) – these are funds which invest in all types of
cleantech deals, including clean energy technology ventures
o General VC funds – these are funds which invest in all types of VC
deals, including clean energy VC deals in mainly start-up and expansion
stages
o General private equity funds - these are funds which invest in all types
of private equity deals, including later-stage clean energy deals like buy-
outs.
o Other (government VC funds, funds of funds, or financial intermediaries
Firm type
between investors and clean energy deals)
The main firm types which back the funds reviewed in this work include:
o Independent firms – These firms are independent, meaning they are not
captured by corporate, banks, governments or other particular
institutions.
o Corporations (CVCs) – Corporate venture capitalists often co-invest
with traditional venture capitalists. Besides being savvy investors, many
corporate VC’s provide their portfolio companies access to corporate
distribution channels and potentially important strategic partners.
o Banks / subsidiaries of banks
o Government
Core investor types
The core investor types include:
o Corporations
o Private investors (individuals)
o Banks
o Pension Funds
o Governments
o Mixed (other above, funds of funds, insurance companies, etc.)
272

Fund size
Categories for fund investment levels for clean energy funds considered in
this section are 97 :
o 0-5M, 5-10M, and 10-20M (small fund size)
o 20M-50M, 50M-100M (medium fund size)
o 100M-250M, 250M-500M (large fund sizes)
Firm size
Categories for firm size (total firm spending on VC and PE investments)
considered are:
o 0-50M (small size)
o 50M-100M (small size)
o 100M-250M (medium size)
o 250M-1B (large size)
o 1B-5B (very large size)
Management & skills
It was considered important to consider the level of expertise which is required
today in the private equity field and the level of expertise that may be required
for a successful private equity fund in the clean energy sector. Private equity as
well as venture capital investment requires serious professional expertise; and
clean energy private equity funding appears to require even more specialized
expertise, although this assumption needs to be researched further. Yet, like
other investors, private equity investors will often not have any firm specific
knowledge, although they may have some practical experience in a particular
industry sector. This appears to support the hypothesis that private equity
investors are highly influenced by external stakeholders, the most important of
which would appear to be their core investors (corporations, pension funds,
private investors, banks or governments). Another possible important source of
information may be entrepreneurs themselves. The portfolio companies they
invest in first of all indicate the fund’s technology focus or preference, but
97 In other sections of the analysis (e.g. the regulatory risk management approaches analysis) a different
fund size break-down was used for analytical purposes and also because of a reduced data set for the
RRM approach question. In such a case, the fund size was broken down into just two categories (small
size and large size).
273

secondly would be one of the major sources of information, assuming they
communicate regularly with their portfolio companies, with regard to how
policies impact their decisions in the clean energy area. This is why this set of
management practices and skills was chosen for the analysis.
Team backgrounds
The following backgrounds were rated by respondents (1-5):
o Energy-related
o Other Industrial-related
o Science-related
o IT-related
o Health-related
o Consumer-related
o Finance-related
o Other
Fund backgrounds prevalent among the team are bound to have some impact
on the views of fund managers with regard to various policies. First of all,
funds with a high level of energy-related experience will probably have a much
more realistic view of what policy can change in the sector, and second, funds
with more personnel with financial backgrounds may tend to think a certain
way about the interference of government into the market.
Fund experience
The following periods of time were used to collect information on when the
fund made their first and last clean energy investments. Note that most of
the funds made their last investment in 2007, so their answers to that
question were not reported in this thesis.
o Pre-1990
o Pre-2000
o 2000-2001
o 2002-2003
o 2004-2005
o 2006
o N/A
274

Leadership
Information was collected on the number of funds corresponding to the
approximate amount of times the fund was a lead investor on a given
funding round, including the following extimated times:
o None
o A few
o Many
o Almost all
Whether the fund is often a lead investor, or not, was also explored. Venture
capital research indicates that syndication may be a mechanism through which
venture capitalists resolve information uncertainties about potential investments.
Gompers and Lerner (2004a) write that while the following three hypotheses do
not exhaust the rationales for syndication, they lend themselves to empirical
examination. 1) Syndicating first-round venture investments may lead to better
decisions about whether to invest in firms. Another venture capitalist’s
willingness to invest in a potentially promising firm may be an important factor
in the lead venture capitalist’s decision to invest. Sah and Stiglitz (1986) show
that hierarchical organizations, in which investments are made only if several
independent observers agree, may be superior to ones in which projects are
funded after one affirmative decision. 2) Syndicating later round financing may
avoid opportunistic behavior. Admati and Pfleiderer (1994) develop a rationale
for syndication in later venture rounds, based on informational asymmetries
between the initial venture investor and other potential investors. Under the
model’s assumptions, the only way to avoid opportunistic behavior is if the
lead venture capitalist maintains a constant share of the firm’s equity. 3)
Syndication may help venture capitalists exploit informational asymmetries and
collude to overstate their performance to potential investors. Lakonishok,
Schleifer, Thaler, and Vishny (1991) suggest that pension funds “window
dress 98 ” (Gompers and Lerner, 2004a). Syndication may also be a regulatory
risk management strategy for some investors when they wish to enter an
investment in the clean energy sector. Syndication of first-round venture
98 “Because institutional investors may examine not only quarterly returns but also end-of-period
holdings, money managers may adjust their portfolios at the end of the quarter by buying firms whose
shares have appreciated and selling “mistakes”. Venture capitalists may similarly make investments in
the late rounds of promising firms, even if the financial returns are low. The strategy allows them to
represent themselves in marketing documents as investors in these firms” (Gompers and Lerner, 2004).
275

investments may lead to better decisions about whether to invest in a given
clean energy deal. This may be especially true if other investors (which may
become the lead investors) are perceived to have the resources and capabilities
to undergo the due diligence process for clean energy investments. Another
potentially more preferable option for a more generalist VC fund, without
significant energy sector expertise, may be to specifically syndicate with CVCs
in the energy business.
Interaction
The following questions pertain to this aspect: How much time do your
funds’ Partners and Staff meet with Policy-makers; and How much time do
your funds’ Partners and Staff meet with your funds’ portfolio companies.
The categories of time spent included:
o 1 time per quarter or less
o About 1 time a month
o Every 1-2 weeks
o 2 times a week
o Almost every day
o N/A
Whether a fund is an active or passive communicator with policy makers and
their portfolio companies was equally explored. The link between policy
preferences and the extent of influence the fund attempts to have on Policy-
makers wass considered to be a possible key factor related to a fund’s views
about policies. Furthermore, the amount of interaction that the fund managers
have with their invested companies would indicate whether they have a
relatively important ex-post risk mitigation strategy (e.g. a “hands-on
approach”) compared to the usual ex-anti risk mitigation strategy.
Information sources
Information sources which were rated 1-5 according to importance to the
fund in helping them with regard to decisions to invest VC or PE in the
clean energy sector, included:
o Institutional investors
o Other fund managers
o Corporate buyers
276

o Final consumers or users in the market
o Advisers on technology
o Internal staff intelligence
o Financial consultants
o Investment banking reports
o Other specialized industry reports
o News media
Important information sources used by the funds were also rated by the
respondents as it was felt that investor’s perceived important information
sources in the field of clean energy would be related in some way to their
policy preferences, given that this information would be interpreted in their
own way to help them develop their particular views, as well as their regulatory
risk management or opportunity management strategies and general approaches.
Clean energy views and preferences
The following areas additional views and investment preferences were thought
to be relevant to in particular the funds’ views on policies. In particular, fund
perceptions about hindering factors and drivers for investment in clean energy
technology ventures were thought to also be relevant to building policy
perceptions.
CE drivers
The fund managers’ perceptions about what drives the clean energy market
were to be ranked 1-4, where 1 was the most important driver. Options
available to the respondents included:
o climate change
o security of energy supply
o competitive advantage (of firms)
o air pollution
CE hindering factors
How do various possible hindering factors rate in terms of importance?
These were hindering factors for continued growth of the clean energy
space. The factors provided as options for selection in the study were based
on research previously conducted by Wuestenhagen and Teppo (2006). The
277

idea of including these same factors was also to update this work based on a
larger sample of venture capitalists and private equity investors in the clean
energy sector. It should be noted therefore that the two sets of results might
not be directly comparable or contrastable because this sample includes
funds which invest in later-stages, as well as typical venture stages:
o Less experience in new investment space; will take some time to
grow
o Technology risk (e.g. that another technology will dominate)
o Institutional investor interest
o Lack of a track record of successful clean energy exits
o Longer technology lead times compared to e.g. internet
companies
o Large energy corporations as potential trade sale buyers lack a
venturing culture (unlike e.g. big pharma)
o Lack of internalization of external cost, subsidies for
conventional energies
o Lack of competent VCs
o Lack of competent venture managers for deals
o High capital expenditure and long investment cycles in the
energy sector
o Not enough good deal flow (low supply of good Clean Energy
investment options)
o Not enough consistent government commitment to sustainable
energy
o Market power of incumbent energy providers (increasing
difficulty to enter the market)
Hindering factors viewed by the funds may be one of the most important
indicators of what a funds policy views are likely to be. If a fund views the
lack of internalization of external costs as being important, it would follow,
for example, that they would highly rate the importance of reduction of
fossil fuel subsidies, or market barrier reduction policies like CO2 or energy
taxes.
278

CE investment criteria
This was an open question, in which funds were asked to state the top 5
investment criteria they use in assessing clean energy deals. The major
categories of criteria which had been mentioned most often were:
o Technological aspects
o Financial aspects
o Management aspects
o Market aspects
An important indicator of the fund’s investment behaviour with regard to clean
energy which might be related to their policy preferences is investment or
screening criteria for deals. In very few cases, funds volunteered required
return rate information in the scope of such criteria. The fund’s 5 top
investment criteria for clean energy deals were collected.
CE geographical focus
Major regions which were available to choose from included:
! North America
! Europe
! Asia
! Latin America
! Africa
! Australia/New Zealand
! Other
! Mix of the above
In addition, investors were also asked the following additional question: Which
country do you generally view as offering the best (or one of the best sets of)
government incentives or policies for PE and VC investment for each Clean
Energy investment space mentioned below?
CE technologies funded
The fund managers were asked to indicate the number of investments that
their fund has done for each Clean Energy technology area below:
! Solar PV
279

! Solar thermal
! Wind
! Geothermal
! Marine (wave and tidal energy)
! Biomass for power
! Biofuels for transport
! Stationary fuel cells
! Fuel cells (for transport)
! Energy storage
! Hydrogen from renewables
This information was collected about what technology areas were invested in
because it reveals some information about particular decisions made already by
the funds and investment preferences with regard to early-stage versus later-
stage clean energy technologies, but also because their choices already made
will have provided investors with a source of information (information about
realities of the market and policy-drivers in different sub-sectors from their
portfolio companies) which is particular to different clean energy sub-sectors,
and might also influence their policy perceptions over time as they gain
experience investing in different sub-sectors of the industry.
CE typical time to exit
The fund managers were asked what their typical time to exit (e.g. IPO or
trade sale) for Clean Energy companies was, among the following choices:
! 1-2 years
! 3-4 years
! 5-6 years
! 7-8 years
! 9-10 years
! 10-11 years
! 12-13 years
! more than 14 years
! N/A
280

Furthermore, it was expected that fund expectations for exit of clean energy
deals may also be relevant to policy preference. Unfortunately, expected or
required returns for clean energy deals were not requested, as it was deemed to
be too sensitive to collect required returns and risk premiums from fund
managers, so time to exit expected for clean energy deals (3-4, 5-6, 7-8, or 9-10
years), was collected.
281

Annex 3: Further analysis of fund characteristics -
Supplemental information to section 6.2
Backgrounds, sector experience, information and
exposure
This section of the annex accompanies section 6.2 as it provides information on
how the results in 6.2 were obtained. In this section many charts feature a
scaling of 0-5, 5 being very important. Academic and professional backgrounds
of venture capital or private equity investment teams were also considered to be
important to influencing fund’s perspectives on clean energy policies.
Overall, the most important professional backgrounds in the clean energy
funding teams were: energy sector-related and finance-related. Science-related
backgrounds and other industry-related backgrounds were also perceived by
those interviewed and surveyed as being prevalent in their investment teams.
Looking at backgrounds by fund type, dedicated clean energy funds gave
energy-related backgrounds and finance-related backgrounds especially high
scores. This makes logical sense as they are more concentrated on energy-
related investments. Funds with the least energy-related backgrounds in their
teams were general VC funds. In such teams, IT-related backgrounds were
prevalent. However, cleantech funds rated energy-related backgrounds quite
highly, as did general private equity funds. Finance-related backgrounds were
also perceived as being high in cleantech funds.
282

4.1
Finance
Other
Consumer
2.8
2.4
5.0
4.0 2.9
3.0
2.0
1.0
0.0
IT
3.6
Science
2.0
Health
4.2
3.6
Other Ind.
Energy
Figure A3 -1: Qualification of management team (overall scores for importance
in the fund’s investment team)
Note: 1 is not so important and 5 is very important. N = 38.
Finance
Other
Consumer
5.0
4.0
3.0
2.0
1.0
0.0
IT
Science
Health
Other Ind.
Energy
CTF
DCE
General PE
fund
General VC
fund
Figure A3 -2: Backgrounds of importance to different types of funds
Note : N = 37.
283

As for other characteristics compared with fund backgrounds, fund location is
not very telling of backgrounds. By stage of investment, it was clear that
backgrounds differed significantly by the fund’s stage of investment focus. For
example, funds focused on expansion stages rated other industrial backgrounds
as high in their teams, but interestingly they also rated IT-related backgrounds
as quite high in their teams. Finance and energy-related backgrounds were very
important to all fund types, but they were relatively very important compared to
other backgrounds in teams which invested across all stages.
Backgrounds by firm type showed that banks and subsidiaries of private equity
firms tend to have significant finance and energy-related backgrounds in their
teams. Government-backed funds have significant science-backgrounds. CVCs
have significant other industrial-backgrounds, as well as science-related and
energy-related backgrounds. Independent firms have quite a good balance of
backgrounds, with slightly more health-related backgrounds than other firm
types.
Finally, by firm size, the results showed that very large firm sizes have
significant presence of other backgrounds, very few health-related
backgrounds, and more consumer-related backgrounds. Small sized firms have
significant science-related backgrounds, and more health-related backgrounds
than other firm sizes.
Clean energy fund experience (first investment made in clean energy and last
investment made in clean energy) was collected as well. Almost all funds had
made their last investment in 2007 or 2006. This information could be used to
see if there was any potential link between fund experience and policy
preferences, although one could argue that the experience in a given team is
due to the team’s personal professional experiences, so a very new clean energy
fund could be acquiring high levels of experience (and knowledge) from new
hires with extensive experience in the clean energy field.
284

30
25
20
15
10
5
0
Pre-2000 Post-2000
Figure A3 -3: Number of funds developed pre-2000 and post-2000
Note: N = 38.
One should note that probably because the VC and private equity industry is
more experienced in the United States, it is normal that more clean energy
related funds with experience are seen among the sample, which are based in
the United States. This may also explain the higher level of financing in the
United States for clean energy ventures.
12
10
8
6
4
2
0
US GB Other EU
Figure A3-4: Country location for the most experienced clean energy funds
Note: N = 58. Experience = invested in clean energy pre-2000.
Other information collected from a quick analysis of the data on experience
shows that half of the investors only invested since 2000. Only about 1/3 rd
invested pre-2000 in this sector. Finally, about 1/5 th has still not invested yet.
285

Meanwhile, dedicated clean energy fund (DCE) tend to have slightly more
experience investing in this sector. About half of the dedicated clean energy
funds had started investing in clean energy pre-2000. About a quarter of these
funds started pre-1990. Still, another half had started investing between the
years 2002 and 2005.
It is interesting to take note of how many funds in the sample are acting as lead
investors in clean energy investment rounds, and how many are seldom lead
investors on syndicated deals. The majority of the sample is taking the lead on
funding rounds for syndicated deals (that is many times or almost always).
Number of funds
14
12
10
8
6
4
2
0
none a few many almost all
Number of times fund was lead investor on a deal
Figure A3 -5: Number of funds corresponding to the approximate amount of
times the fund was a lead investor on a given funding round
Note: N = 39.
Venture capital research points the following relevant findings about
syndication 99 (i.e. joint investment by several venture capitalists). Very
experienced venture capitalists suffer from potential competition. Therefore
they are more reluctant to syndicate, while this potential competition between
venture capitalists is harmless for inexperienced venture capitalists because
their evaluation of the project is not accurate enough to allow them to invest
alone. One would therefore expect the funds with less experience to first of all
99 See for instance Bygrave (1987, 1988) or Lerner (1994).
286

syndicate. However, whether they are more likely to be a lead investor on such
syndicated deals is another question.
As for entrepreneurs and Policy-makers, while policies were rated by investors
showing the relative influence of policies themselves on investors decision-
making, information obtained about the frequency of meetings between fund
managers and policy makers revealed that individual Policy-makers are perhaps
less influential than overall policies on the investment decisions of fund
managers.
Specifically the question on time spent with Policy-makers revealed that:
! Most fund managers (both partners and staff) meet with Policy-makers
less than 1 time/quarter
! Very few fund managers meet with Policy-makers 1x/month or almost
every day
As for time spent with portfolio companies, many Partners met with companies
more than 1x / quarter.
Many fund managers said in the interviews that they remain well informed
about policy through experts, partners, news/reading, and sometimes they meet
informally with policy makers at conferences that they all attend (meetings
which are probably not always included in the estimation of time spent which
they provided).
Therefore, information about the impacts of policies, which help form fund
mangers’ opinions about various policy options, is probably indirectly provided
to fund managers via the entrepreneurs they invest in, since they are more often
meeting with these entrepreneurs and it is the entrepreneurs which might
directly experience the impacts and benefits of policies on their businesses (or
at least receive more information about the possible effects from their
counterparts in the industry).
In addition, comparatively few fund managers receive information about policy
directly from Policy-makers. Neither do they appear (on the most part) to
287

substantially influence Policy-makers via lobbying efforts, at least not directly.
Only about 10% of the funds’ Partners meet with Policy-makers almost every
day and another 10% of funds’ Partners meet with Policy-makers every 1-2
weeks. Only one-fifth of all funds are politically-active in such a way. Thus, it
is proposed that most fund managers form their opinions about policies from
indirect sources of information about policies, and a key source of information
for these funds may be the entrepreneurs that they have invested in.
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1x/ quarter 1 x/ m onth every 1-2
weeks
2 x/ week alm ost every
day
P artners m eeting with P o licy Makers
S taff m eeting with P olicy Makers
P artners m eeting with com panies
S taff m eeting with co m p anies
Figure A3 -6: Frequency of meetings between Partners and staff with Policy-
makers or portfolio companies
Note: A significant number of funds answered N/A; these were not counted in
the average scores. N = approximately 34 depending on question.
The most important information sources cited by the reviewed funds, overall,
were:
! Internal staff intelligence
! Final consumers
! Other specialized industry reports
288

Other
specialised
industry
reports
Investment
banking
reports
News media
3.6
2.9
Financial
consultants
2.6
2.3
Institutional
Investors
5.0
4.0
2.6
3.0
2.0
1.0
0.0
4.0
Internal staff
intelligence
3.2
3.5
Other
investors
3.4
3.7
Advisers on
technology
Figure A3 -9 : Important information sources for all funds
Note: N = 35.
Corporate
buyers
Final
consumers
Examining rated information sources by stage of investment shows that funds
focused on later stage deals tend to diverge a little away from the norm towards
the following information sources: institutional investors, other investors,
investment banking reports, and slightly diverge away from news media as
sources of information which influence their investment decisions in clean
energy, according to this self-reported data. This makes sense assuming they
are also closely linked to large institutional or other investors, and not so much
other types of investors such as wealthy individuals or family offices.
289

Other
specialised
industry reports
Investment
banking reports
News media
Financial
consultants
Institutional
Investors
5.0
4.0
3.0
2.0
1.0
0.0
Internal staff
intelligence
Other investors
Advisers on
technology
Corporate
buyers
Figure A3 -10 : Information sources by stage of investment
Note: N = 33.
Typical time to exit
Final consumers
Seed and start
up
expansion
late stage
Another aspect of investment screening, is finding deals that would meet
expectations regarding time to exit for a deal. As mentioned before the average
time to exit for all funds was just below 6 years. The most often mentioned
range was 5-6 years. However, many respondents did not answer this question.
18
16
14
12
10
8
6
4
2
0
10
17
3 to 4 5 to 6 7 to 8 9 to 10 N/A
Figure A3 -11: Typical time to exit for funds
Note: N = 46 (or 32 not counting the N/A).
3
2
14
All
290

Looking at time to exit by region focus, Figure A3-12 shows that European-
focused funds seem to accept slightly longer typical time to exit than funds
investing only in North America only.
7
5
3
1
Time to Exit
Europe North America
Figure A3 -12: Typical time to exit by region-focus (Europe vs. North
America)
Note: N = 32.
Also, the longest typical time to exit by stage of investment was naturally for
seed and start-up stages (6.5 years), compared to only 5 years for expansion-
stages, and 5.5 years for later-stage investments.
Clean energy drivers, hindering factors and investment
criteria
This section describes the different motivations, investment expectations and
concerns of various types of funds. It is considered important to explore what
companies perceive as key drivers, hindering factors to further clean energy
investment overall, (looking at their ranked order of importance or rating their
importance) and what investment firms use as criteria to screen investments in
the early part of their decision-making process.
291

Drivers for clean energy investment
On average across the entire sample, the drivers were ranked in the following
way:
! Competitive advantage
! Security of energy supply
! Climate Change
! Air pollution
The following figures on drivers versus other characteristics of funds show
rankings according to the original data, where 4 is the lowest ranking order.
The drivers can be analyzed by observing the average rating for each driver by
fund characteristics like fund type, fund size, firm type, firm size, etc.
15
11
13
15
10
24
16
Climate Change Security of energy
supply
4
1 2 3 4
25
13
10
Competitive
advantage
6
4
6
15
Air pollution
Figure A3 -13: Frequency of times each driver type was mentioned as 1st, 2nd,
3rd, and 4th
Note: N = 54.
By geographical focus, the data indicated also that the climate change driver
was significantly less important for U.S. funds, than for European-focused
funds. The same was true by fund location (U.S. vs. Europe). It makes sense
that the U.S.-based or focused funds would rank climate change low, given that
the United States has not ratified the Kyoto Protocol and most states do not
29
292

have significant climate policy in place. When this changes, climate change is
bound to be ranked higher as an important driver for investment for U.S.-based
or focused funds.
By firm size, the data also shows an obvious divergence of views with regard to
climate change. Investment firms with funds in clean energy which have total
VC and PE funding levels of 0-50M Euros (very small firm size) as well as for
50-100M Euros (small firm size) tend to view more consistently that climate
change is a less important (ranked 3 or 4) driver than other firms (e.g. firms
with larger total VC and PE investments). Another observation from this data is
that most firm sizes view air pollution as the least important driver, although
this is not as pronounced for firms with overall VC and PE funding levels in the
range of 250M-1Billion Euros (large size).
Looking at rankings of drivers by fund size shows that competitive advantage
and climate change are important drivers for very small fund sizes (0-10M
Euros) as well as for funds in the size range of 100M-250M Euros. For those
between 10M-100M Euros, competitive advantage was much more important
and security of energy supply was the second most important driver. For very
large clean energy funds (250M-500M Euros) both climate change and security
of energy supply were important drivers, with competitive advantage the third
most important driver. Air pollution was generally the least important driver for
the smallest and largest clean energy funds. For funds with 10-100M Euros, air
pollution with climate change is sometimes mentioned last. For clean energy
funding sizes of 100M-250M, air pollution is sometimes the first or second
most important driver for funds. There is a larger diversity of views in this
category. This is probably because some of these funds are based in the United
States where air pollution has historically been an important driver for clean
energy activism and legislation.
293

3
2
4
0
Climate!Change Security!of!energy!
supply!
3
3
1
3
Climate!Change Security!of!energy!
supply!
1
1
6
1
1
3
0"10M
1 2 3 4
1
5
100"250M!
0
1 2 3 4
0
3
4
0
Competitive!
advantage
3
1
2
Competitive!
advantage
0
1
0
8
Air!pollution!
1
1
3
3
Air!pollution!
0
4
1
3
Climate!Change Security!of!energy!
supply!
2 2
0
2
3
3
10"100M
1 2 3 4
0
5
1
1
1
Competitive!
advantage
0 0 0 0
1
0
3
4
Air!pollution!
1 1 1 1 1 1
Climate!Change Security!of!energy!
supply!
250"500M!
1 2 3 4
3
Competitive!
advantage
0
3
Air!pollution!
Figure A3 -14 : Drivers for clean energy investment by clean energy funding
size
Note: N = 53.
Looking at the results by fund type, show that most fund types also rate air
pollution last, with General VC (GV) funds rating it slightly higher than other
fund types. They also rated other drivers about equally. General Private Equity
(GP) funds tend to rate climate change slightly lower than competitive
advantage and security of energy supply. Meanwhile, Cleantech Funds (CTF)
rated competitive advantage clearly higher than other drivers and Dedicated
Clean Energy Funds (DCE) rated security of energy supply high with
competitive advantage.
294

Hindering factors for further investment
As for hindering factors, overall the hindering factors most relevant to all funds
were high capital expenditure, long lead times, and lack of track record for
clean energy venture investment success, less experience and technology
risk.
bad co. mgrs
Technology risk
Mrkt power of incumb.
3.3
3.0
Gov. Comm.
Less exp
3.0
3.2
3.4
deal flow
Institutional investor
interest
5.0
4.0
3.0
2.0
1.0
0.0
2.9
3.0 3.5
track record
2.7
2.5
3.4
2.8
lead time
Lack comp. VCs
3.6
High capex
Figure A3 -16 : Perceived hindering factors (overall scores)
Lack trade sale opp
FF Sub/No int.
Note: “bad co. mgrs” stands for “bad company managers”, “lack trade sale
opp” stands for “lack of trade sale opportunity”, “FF Sub/No int” stands for
“Fossil fuel subsidies and no internalization of environmental costs”, “High
Capex” stands for “High capital expenditure”, “Gov. Comm.” Stands for “Low
Government Commitment”. N = 37.
It is also interesting to note that funds focused on Europe vs. those focused on
North America, tend to perceive slightly different key hindering factors for the
clean energy industry.
North American focused funds, in particular, mentioned less experience in the
sector (just a matter of time before it grows), as important, along with high
capital expenditure, long lead times, fossil fuel subsidies (no internalization of
environmental costs), and lack of track record for clean energy deals. This
implies that North American focused funds believe it is more or less a matter of
295

time and experience before the space becomes a much more mature investment
category. However, the fact that they mention long lead times does imply that
clean energy may be less of a typical venture type investment and might evolve
into a category for more appropriate types of investment.
European-focused funds tended to rate lack of consistent government support
as slightly higher than North American focused funds, but on the other hand
they rated fossil fuel subsidies or lack or internalisation of environmental
externalities (costs) of dirtier technologies lower than North American focused
funds. They also rated technoloy risk and lack of trade sale opportunities
slightly higher than North American focused funds.
Technology
risk
bad co.
mgrs
Mrkt power
of incumb.
Gov. Comm.
Less exp
deal flow
Institutional
investor
interest
5
4
3
2
1
0
High capex
track record
Figure A3 -17: Hindering factors by region focus
Note: N = 33.
lead time
Lack comp.
VCs
Lack trade
sale opp
FF Sub/No
int.
Europe
North
America
Looking at hindering factors by fund type shows that general VC funds are
overall slightly less concerned about hindering factors than other funds types.
But they are quite concerned about technology risk. One fund manager said:
“The biggest challenge for renewable energy remains post-pilot, pre-
commercial technology risk, and policies need to be created to incentivize
investors, developers and lenders to build such projects. Feed-in tariffs are the
best way to promote the development of clean energy.”
296

Meanwhile they are relatively less concerned about fossil fuel subsidization, or
perhaps they are not as aware of how fossil fuel subsidies impact the sector
(compared to for example, dedicated clean energy funds).
Compared to general VC funds, general private equity funds are more
concerned about hindering factors overall, and they are particularly concerned
about the market power of incumbents in the energy sector. This makes sense
as many private equity funds are investing in biofuel investments. General
private equity funds are also concerned about deal flow in the clean energy
sector, high capital expenditure, lack of trade sale opportunities and long lead
times in the sector.
Cleantech funds are more concerned, comparitively, with lack of government
committment, technology risk, and lack of track record in the sector. Dedicated
clean energy funds are concerned most about high capital expenditure, fossil
fuel subsidies (lack of internalization of costs), and less experience in the
sector.
bad co. mgrs
Technology risk
Mrkt power of
incumb.
Gov. Comm.
Less exp
deal flow
Institutional investor
interest
5
4
3
2
1
0
High capex
track record
Figure A3 -18 : Perceived hindering factors by fund type
Note: N = 35.
lead time
Lack trade sale opp
FF Sub/No int.
Lack comp. VCs
CTF
DCE
General PE
fund
General VC
fund
297

In the interviews, many investors mentioned that investors new to the market
(because of the bandwagon effect) did not understand the fact that the clean
energy sector is very different from other venture spaces in that there are much
higher capital expenditures needed in the energy market. They noted that they
believed many other investors are having difficulties with this realization, and
that some investors will have difficulties reaching their profitability
expectations in the sector because they are not prepared to deal with this issue.
To be successful in this space, they noted the importance of having the capacity
and know-how to deal with this issue.
Long lead times for clean energy investments to maturity or exit, were also
mentioned as an important hindering factor, especially for private equity
investors. Time to exit is one indicator of what investors expect with regard to
lead time. However, from an analysis of fund characteristics it was found that
the fund types with lower typical times to exit are cleantech funds and general
VC funds, not private equity funds. In any case, all fund types are limited by
the investment cycle with about 10 years to close a funding round for most
funds. Private equity investors must return liquidity to their core investors.
Core investors may have other reasons to invest in clean energy funds, other
than liquidity 100 . Meanwhile, general venture capital funds may find various
ways to exit their deals before products enter a competitive market and face
competition with conventional sources of energy. Finally, private equity funds
are likely to suffer the most from long investment lead times, as they are closer
to market realities.
It is interesting to find that funds based in the United Kingdom rated a number
of hindering factors quite low like long lead-time, lack of trade sale
opportunities, market power of incumbents, and fossil fuel subsidies, while
funds based in other European countries and in the United States had more
similar views about such hindering factors being relevant to them. On the other
hand, funds based in the UK also rated high technology risk, lack of
100 A study of German private equity investors conducted by Unigestion and GreenparkCapital show
that from the buyers’ perspective, the primary motivator, in any case, for investing in private equity, is
a perceived attractive yield. Increased diversification and an attractive risk/return ration also ranked
highly. Liquidity was ranked in 5 th place as for reasons they invest in private equity
(Unigestion/GreenparkCapital, 2006).
298

government support, lack of competent VCs and lack of competent venture
managers.
bad co. mgrs
Technology risk
Mrkt power of
incumb.
Gov. Comm.
Less exp
deal flow
Institutional
investor interest
5
4
3
2
1
0
High capex
track record
lead time
Lack trade sale
opp
FF Sub/No int.
Lack comp. VCs
Figure A3 -19: Hindering factors by country of fund management
Note: N = 37.
US
GB
Europe -
Others
One of the most notable differences among fund views with regard to hindering
factors was the difference of opinion for funds managing very large funds for
clean energy investments and those managing less large funds. It makes sense
that their views would be distinctive compared to funds which invest less
heavily in clean energy. They are likely to fund larger or later-stage deals
because of the fund sizes in this category, but also in terms of financial risks,
they are likely to be funds which are less risk adverse with regard to this sector.
Naturally, if this was true they would view fewer hindering factors, or they
would rate all hindering factors lower than other fund types. However, this data
shows that they rate some factors higher and others much lower.
Funds in the size category of 250-500M Euros thought that three factors in
particular were not important (1) fossil fuel subsidization/ no internalization of
environmental costs, (2) lack of competent VCs, and (3) high capital
expenditures for clean energy deals. It makes sense that funds which are
heavily involved in clean energy would believe they are competent enough to
299

deal with the sector, and in this respect they should also be competent enough
to deal with issues relevant to private equity investments with high capital
expenditures which are characteristic of this space. They also rate lack of
government commitment for clean energy much higher than the rated fossil
fuel subsidization. Other factors important to large funds for clean energy
investments were: lack of deal flow,institutional investor interest, and market
power of incumbents.
bad co. mgrs
Technology risk
Mrkt power of
incumb.
Less exp
Gov. Comm.
deal flow
Institutional
investor interest
5
4
3
2
1
0
track record
High capex
lead time
Lack trade sale
opp
FF Sub/No int.
Lack comp. VCs
Figure A3 -20 : Perceived hindering factors by fund size
Note: N = 38.
0-10M
10-100M
100-250M
250-500M
Funds which invest in clean energy technologies also think differently with
regard to their perceptions about hindering factors for further growth in the
sector depending on the type of firms they are.
Corporate venture capital firms have a distinctive viewpoint. First of all, they
were most concerned about hindering factors for this sector. However,
institutional investor interest and fossil fuel subsidization/lack of internalization
of environmental costs of fossil fuels are not seen as important at all to these
fund managers. Meanwhile, high capital expenditure is a very important issue
for this group of investors, also lack of competent venture managers was seen
as important, with lack of track record and long lead-time for clean energy
investments.
300

Government-backed funds also had particular views. First of all, they perceived
the mentioned hindering factors as less important overall, compared to other
types of firms. For example, lack of competent company managers, less
experience in the sector, institutional interest, lack of track record, market
power of incumbents, lack of competent VCs, and fossil fuel subsidization
were not viewed as important hindering factors by government-backed funds.
Technology risk was the one hindering factor they perceived as important. This
may be the case because most of the government sponsored funds are investing
in early-stage technologies.
Banks mentioned lack of consistent government commitment as their main
hindering factor. They also mentioned less experience in the sector as quite
important.
There was a slightly higher score given to high capital expenditure and lack of
track record in the clean energy sector in the independent firm category. Less
experience in the sector was also relevant to this group.
bad co. mgrs
Technology risk
Mrkt power of incumb.
Gov. Comm.
Institutional investor
interest
Less exp
5
4
track record
deal flow
3
2
1
0
High capex
lead time
Lack trade sale opp
FF Sub/No int.
Lack comp. VCs
Figure A3 -21 : Perceived hindering factors by type of firm
Note: N = 37.
Bank & SubPE
CVC
Gov.
Indep.
301

Looking at only independent firms, by type of fund, we also see that there is
quite a difference of opinion among independent firms. This makes sense given
that there are 34 independent firms and they have a variety of different
characteristics, most notably fund type. Independent dedicated clean energy
firms perceived fossil fuel subsidies, lack of track record for clean energy
ventures, less experience in the sector as important hindering factors. Cleantech
funds which are independent (many of them being based in the United States)
perceived lack of track record, lack of consistent government commitment for
clean energy, and technology risk as being important. Independent general
private equity funds perceived market power of incumbents as a very important
factor along with high capital expenditure in the clean energy sector. The next
group of slightly less important, but still quite important, hindering factors for
these firms were: lack of competent venture managers, lack of trade sale
opportunities, longer lead time, less experience in the sector, and lack of
competent venture managers. Interestingly, this group of investors did not think
technology risk or lack of consistent government commitment to clean energy
were important hindering factors to the growth of this investment space.
Meanwhile, independent general venture capital firms mentioned institutional
investor interest and less experience in the sector as important. However,
overall they thought that other hindering factors mentioned were not extremely
relevant to the continued growth of the space. Nevertheless, the factors which
they mentioned as having a score of over 3 besides institutional investor
interest and less experience were: lack of deal flow, high capital expenditure,
lack of track record, long lead time, and technology risk.
302

ad co. mgrs
Technology
risk
Mrkt power of
incumb.
Gov. Comm.
Less exp
deal flow
Institutional
investor
interest
5.0
4.0
3.0
2.0
1.0
0.0
High capex
track record
lead time
Lack comp.
VCs
Lack trade
sale opp
FF Sub/No
int.
Figure A3 -22 : Mean scores for independent funds only, by fund type
Note: N = 33.
CTF -
Independent
DCE -
Independent
General PE -
Independent
General VC -
Independent
other -
Independent
Finally, as for core investor types or Limited Partners (LPs), hindering factors
were rated differently in the case of banks, in particular. Some of these findings
appear to overlap with the findings for firm type (e.g. corporate investors and
CVCs both rate high capital expenditure very high), but core investors like
banks may also invest in independent firms, which means an analysis by core
investor type is also required. Other investor types had about the same
perceptions but at varying levels, e.g. funds backed by only corporate investors
and those backed by mixed investors tended to rate high capital expenditure as
an important hindering factor, but those which were only corporate-backed
rated this factor even higher. On the other hand, banks rated this factor very
low, while they rated lack of consistent government commitment much higher
than other investor types. Banks also rated less experience in the sector of very
low importance, while both corporate-backed and mixed investor funds rated
this factor quite high.
303

ad co. mgrs
Technology risk
Mrkt power of
incumb.
Gov. Comm.
Less exp
deal flow
Institutional
investor interest
5
4
3
2
1
0
High capex
track record
lead time
Lack trade sale
opp
FF Sub/No int.
Lack comp. VCs
Bank
Corporate
Private
Mixed
Figure A3 -23 : Perceived hindering factors by type of core investor type
Note: N = 37.
Investment criteria
This section analyses the first investment criteria mentioned by investors when
asked to provide their top 5 investment criteria for clean energy investments.
To begin with, criteria is divided by country. Financial returns or market
aspects were most important for funds based in the United States. Two funds
mentioned the need for the company to be profitable without (or with low need
for) supportive laws or incentives. Funds located in the United States cited the
following first criteria:
Table A3 - 1 : First investment criterion for funds located in the United States
US Prior experience in sector
US economic viability
US Doesn't rely on laws or incentives to be profitable
US Great Management
US People
US Market viability
US Economic value proposition
US Technology
304

US Large (1 Billion +) growing markets
US Economic Sense
US Strategic fit
US IP
US Business vs. Technology
US Market Opportunity
US Low or no subsidy need
US Return on investment
US Financial return prospects
US Can the company work at speed
US IP very important
US Overall return profile - cash return and what is the IRR potential
US
A company or venture that generates electricity using renewable energy
sources.
A strong management team was mentioned several times by funds located in
Great Britain. Funds located in Great Britain mentioned the following as their
1 st criteria:
Table A3 - 2 : First investment criterion for funds located in the UK
GB USP/innovative IP
GB Market size and growth
GB Strong management team
GB Management Team
GB A strong experienced team with focus and vision
GB Management
GB Large growing markets
GB Outstanding management
GB Earning growth potential within the next 3-4 years
GB Financial Position
Technology was important for the funds based in Switzerland, management and
financial returns were important for the funds located in Germany, and finally
305

financial returns and market demand were important for funds located in other
European countries. Funds located in other European countries mentioned the
following criteria as their 1 st criteria (note that the specific country is not shown
for confidentiality reasons):
Table A3 - 3 : First investment criterion for funds located in other European
countries
EU Technology
EU Technical USP
EU Energy Balance
EU Proof of concept
EU Make a return
EU management team
EU Financial return potential
EU management
EU Big market
EU idea or co offers innovative product or service opps
EU Market need
EU Return on investment
EU profitability
EU Established revenue model
EU good management
It is difficult to analyse investment criteria for a variety of fund characteristics
because funds often have very similar investment criteria for venture capital or
private equity investments. The following two ways of analyzing investment
criteria found that technology is the most important criteria, based on a higher
weight assigned to the first mentioned criteria. However, management and
financial aspects were more often mentioned among all funds’ full five criteria,
meaning that while technology is the first criteria they look at (e.g. is the IP
sound, etc.) and after this aspect is found satisfactory the companies must
demonstrate clearly that they have the managerial capabilities and the company
has the financial or economic aspects required by the funds to receive their
support.
306

Simple analysis type by number of mentions in the full list of criteria (up to 5
criterion) –
When looking at the overall investment criteria cited by firms regardless of
placement in terms of importance (1-5), management teams and financial
aspects were mentioned as the first criteria most often (both 13 times each),
meanwhile technology and IP were mentioned 39 times overall, but it was
mentioned 9 times under the 1 st criteria. Market was mentioned 9 times overall.
According to such a simplified analysis the result would be the following order
of importance:
! Management (mentioned 34 times, but mentioned 13 times as 1st
criteria)
! Financial (mentioned 30 times, but mentioned 13 times as 1st criteria) :
Return (12); profit (5); financial (5); economic (8)
! Technology and IP (mentioned 39 times, mentioned 9 times as 1st
criteria, and 11 times as 2 nd criteria)
! Market (mentioned 9 times)
Management and financial criteria were mentioned more often as the 1 st
criteria, while technology was mentioned more often as the 2 nd most important
criteria. This reflects the bias of the venture capital and private equity industry
towards good management teams as opposed to just good technologies. While
technology is obviously important, the first thing that comes to their mind as a
factor which can make or break a company is the management team. This is
also probably where VCs believe they have a higher value added in terms of
choosing companies, while the technologies are reviewed in many cases
already by the academic or the technical community, if not a hired technical
team.
Performing the same simple analysis for U.S.-based funds only, the same
results were obtained, except that market-related aspects would be placed
above technology-related aspects for the U.S.-based funds.
307

More complex analysis type – weighted average of the first 3 mentioned
criteria –
Performing an analysis which takes into account the three first mentioned
criteria and taking into account the relative higher importance of the first
mentioned criteria compared to the second and third mentioned criteria (using
multipliers for the criteria mentioned corresponding to the order of mention),
the following results were obtained for the analysis when run by fund type.
Overall, technology was most important, followed by financial and
management aspects. Market aspects were considered a bit less important
overall. This means that technology was mentioned more times in a high
position than other criteria, but it was not necessarily mentioned more times as
the most important criteria.
The overall order of importance, according to the improved analysis is:
! Technological aspects
! Financial aspects
! Management aspects
! Market aspects
Other findings were:
! Cleantech funds favored financial, technological and management
aspects.
! Dedicated clean energy funds clearly favored technological aspects first,
and then financial and management aspects.
! General private equity funds favored financial aspects and management
aspects.
! General venture capital funds clearly favored market aspects and then
technological aspects.
! Other fund types favored financial aspects.
It is understandable that in the cleantech sector, technological risks are of great
importance to funds, especially for those focused on specific technological
areas. Financial aspects would also be critical given that clean energy deals
have been criticized with regard to their potential for profitability given that
they compete in a market which is dominated by conventional energy
308

technologies. As for the importance of managerial capabilities, this is
understandable as well as the literature on venture capital finance indicates that
“a lack of managerial capabilities significantly increases the perceived
risk…Managerial capabilities have the strongest effect on reducing the
riskiness of the deal and resistance to environmental threat has the next highest
effect. Other characteristics of the deal do not influence the perceived risk at a
significant level” (Tyebjee and Bruno, 1984). Market aspects are mentioned
last probably because investors in clean energy have already examined the
relevant markets they are willing to invest in (e.g. clean energy markets) and by
deciding to invest or investigate investment opportunities in this sector, they
are most likely already convinced about the overall market opportunities.
However, general VC funds may still be discovering the market aspects of
clean energy segments (and may be hesitant to assume good overall market
potential). Their strategy may also require sufficient additional market
applications outside of the clean energy sector. Finally, the market aspects of
clean energy technology ventures might be the most interesting aspect of such
ventures for this type of generalist venture capital fund. Therefore, it makes
sense that they emphasize this aspect among their first investment criteria.
Meanwhile, general private equity funds have the resources and capabilities to
study market opportunities in depth. Once they have an idea what is a good
market to invest in they appear to use their key investment criteria (financials
and managerial capabilities) to screen and assess deals in the markets they
decide to invest substantially in.
309

Annex 4: Regulatory Risk Management Strategies
Table A4 - 1: Active regulatory risk management strategies among sample 101
A Risk Management Strategy Stage Fund Type
1 Cleantech is different than IT because you are
making something and it takes time. So you
come out investing late, instead of early, as an
investor in this space. Many others don't
understand this. There are two types of VCs,
one that builds a company and the other that
anticipates a fad or wants an exit quickly. We
develop the company with the time it takes.
Also, we don't follow fads like the majority of
VCs today (many other VC firms hire new
MBAs afraid of losing their jobs and who don't
know the area well). Also, we know how to take
advantage of policy, e.g. how to get generating
attributes in addition to electrons.
2 We don't take regulatory risk. We can get
expertise by working with a big partner investor
or big fund.
Top issues are the low IRRs expected (4 of 4)
and policy uncertainty (3 of 4). We deal with it
by investigating and not investing if there is too
much regulatory risk. We invest in technologies
that are maturing and where there are no
market incumbents not allowing VCs to make
money (like fuel cells for the auto companies).
We don't depend on government or a few large
corporates. We take no big risks. Meanwhile,
Start-up;
Expansion
Expansion;
Replace-
ment;
Buyout
Other
CleanTech
Fund
(including
energy,
water...)
101 Regulatory risk management approaches are listed here in no specific order. Numbers are used to
identify funds by their RRM when quoting funds in other areas of this thesis.
310

we diversify in energy, materials, water and
agriculture.
3 We manage regulatory risks the same way as
for the other sectors: we perform complete
studies of the target & use the know-how of the
investment team.
4 You can't invest based on government policies.
We try to understand the adoption cycle ---
which is different from IT and biotech. You
have a very well established path with
investors at each stage in energy, but for
biotech there is no set path, no regulatory path,
each company is different. While in energy you
have all stages ---- systemic issues, structural
issues (people are terrified about oligopolies),
and it is a paradox that the world's largest
industry where every solution has a potential
global market is based on an industry structure
with monopolies and oligopolies which are the
anti-thesis of industry innovation. We manage
the relevant risks by first understanding this.
Traditionally in this sector you had to invest in
different stages to get to the finish line. You
didn't have larger firms to do the growth equity
in the later stages. Today the fundamental
trends are here for a long time, so you will see
large amounts of capital chasing clean energy
deals. Solar has emerged and will continue to
be an important arena, smart grid is just
coming on the screen and might be more
important than solar in the medium term. Wind
All CleanTech
Fund
Expansion Dedicated
Clean
Energy
Fund
311

will continue, but will be a big company game
as a result of warranty and balance sheet
issues. Long investment cycles are only a
problem for people that don't understand how
to avoid those issues. It's not a systemic
problem. At the core of any innovation in
energy, it is policy driven. But policy which has
been in place for 30 years is a good bet. It is
only likely to strength vs. policies which were
proposed only in the last 3 years and which are
going through legal challenges. This stability is
needed to provide stable markets. What we
ask ourselves is whether a policy-driven
opportunity is based on a newly introduced
policy (or soon to be introduced). But that being
said, a lot out there today is driven by demand
response drivers, e.g. dual fuel engines (and
you can also get regulatory credits). Our
portfolio mostly makes incumbent
infrastructures more efficient.
5 Don't take reg. risk. If company purely
dependent on government grant, wouldn't
invest in it and has to have element to make
money alone.
6 We perform close controlling and coaching of
our portfolio companies; we take an active
board seat, etc.
Seed &
Start-up
CleanTech
Fund
Buyout General
VC Fund
with
significant
CE
312

7 We estimate the cost reduction over time and
when the technology can break-even with
power prices (when subsidies are no longer
needed). If we see the right progression, then it
is fine. The company mostly invests in large
infrastructure related investments and there we
don't invest unless we are certain to benefit
from the regulatory environment. There is
pretty low risk.
For early stage company investments, it is
different scenario.
8 Our fund concentrates on solar and wind. We
make big bets because our investors want us
to take the risks. We manage the risks by
diversifying across the value chain of the
industry we invest in.
9 We have broad expertise over many years.
Each team member has specific deep
expertise, in a few areas. We also have
connections to the best minds globally, for
further due diligence.
10 We interact with Policy-makers, but only at
conferences, etc. We need to have enough
time to know how to work with any given policy.
We can manage the policy, but we can't
manage the changes in policy. As for
regulatory risk management, you hopefully
made an investment where the policy is
additive, but not the totality of what you are
betting on. Also you need to have confidence in
the venture's management team (that they can
make the necessary changes in the company if
policy changes). You can follow policy-making
Start-up;
Expansion
Expansion;
Replace-
ment;
Buyout
General
PE Fund
with
significant
CE
Dedicated
Clean
Energy
Fund
Expansion CleanTech
Fund
Expansion Dedicated
Clean
Energy
Fund
313

from Japan to California and that goes back to
the team and initial investment. You might have
3-4 countries where you are betting on CO2
emissions policy in Europe and the United
States (e.g. California). But other sectors also
have policy requirements. So there is no
special regulatory risk management approach
for the clean energy sector. It is the same thing
for venture investing; it is nothing unique. We
have the same metrics and require the same
growth potential.
11 We create a strong advisory board for the
portfolio company, preferably with leads into
the large corporates and utilities in the energy
space.
12 We focus on select industry segments in which
we have particular knowledge and experience.
13 We have knowledge about policies and how
they impact our investments. Many other
investors have difficulty with the market being
policy-driven. For them, it is not worth the
hassle. There is not sufficient deal flow there to
be worth developing the management
capability to deal with it properly and only do 1
to 2 deals a year.
14 We study each technology on a project by
project basis (rather than a company basis)
and we use our in-house technical expertise to
try to evaluate the risk/return for each project.
15 We use a hands-on entrepreneurial approach
to deal with the risks.
Seed &
Start-up
Seed &
Start-up
General
VC Fund
with some
CE
Other
Start-up Dedicated
Seed
capital
Start-up;
Expansion
Clean
Energy
Fund
Other
General
VC Fund
with
significant
314

16 What percent of all investors consider policy?
all of them. You have to understand what the
energy policy impact is going to be on your
investment. But otherwise, our fund invests in
renewables and energy efficiency as a service
to the community. We get informed about
specific community issues and we have a
captured market - we specialize in one
geographical area.
17 One needs to understand policies. One needs
to understand how to deal with high capital
requirements. We have several people working
in groups that are involved in defining new
regulations. We actively manage regulatory
risks. We are politically active as investors. We
ask for harmonization of the most effective
policies in Europe. Policies should not differ
from country to country because then we must
work with too small markets. We also stay
away from seed and start-up investments. We
believe they do not work in the renewable
energy technology space because of the high
degree of capital required. We believe they
should be done by large corporations and
governments. Most VCs show very poor
performance and we see only good
performance in the expansion stages. IPOs
also show this. Deal flow is also ok here. On
deal flow, the question is the pricing of deals. If
there is excessive pricing, deals become
unattractive. Too much competition in the
CE
All Dedicated
Clean
Energy
Fund
Expansion CleanTech
Fund
315

market is one of the main risks. Another one is
if someone comes out saying all our
assumptions on Global Warming are wrong.
19 We manage regulatory risks by reading. Also,
one partner is involved in a political party. We
only invest if prospects are excellent. The
management teams should be good. Prices
should be cheap. Technologies should be
proven. We only invest if we think we can make
5 times our money in three years, and we very
rarely seek high risk-return deals.
20 The key is being aware of and responding to
policy drivers.
We make sure our companies have other
applications and other countries in which they
can sell their technologies. The level of risk
mitigation is high in our fund. Other funds are
concentrating too much. Not everyone is doing
good due diligence on deals in the space.
Investors are coming into the market because
there is demand, but they don't know much
about it. They see various projects being built,
etc. and they enter.
21 We try to diversify like any bank, but also try to
influence the policy development getting as
much information as we can and also talking to
the regulators themselves. We also look at past
records, to see how they dealt with these
questions in the past. Sometimes it is difficult
because things are changing, but we can
deduct if it is a reliable investment. We meet 2
x a year with Policy-makers in the countries we
invest in.
Seed
capital
General
VC Fund
with
significant
CE
All CleanTech
Start-up;
Expansion
Fund
General
PE Fund
with some
CE
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22 If a business is 100% based on policy, we have
3rd party consultants to do an analysis of that.
Most of the business plans we see are 100%
based on policy, and with 5-8 years out, there
is no way to know if that risk is going to stay
the same, so the answer, we feel, is to look at
how to scale production. This goes back to
gate keeping - is your IP sound, is the business
sound. This is the approach assuming that the
regulatory risk will change over the period of
time you are investing (e.g. it may change
much less in the first year, but in years 2-5 you
don't know how it will change). If the
management team lowers cost, increasing
efficiency in the technology (e.g. solar), you
can win despite changes in regulatory issues.
So you need to make the investment and look
at the regulation in detail ex-post - how to
spread the risk by entering various markets,
etc. You look at a portfolio of investments and
while you might have a lot of biomass risk,
solar is different - and you spread over different
policies for diff. technologies. Some will change
and some won't. So you are somewhat ok in
that sense. Most VCs look at each policy as it
relates to each company.
Start-up CleanTech
Fund
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Table A4 - 2: Passive regulatory risk management strategies among sample
P
Risk Management Strategy Stage Fund Type
1 Our portfolio companies are active in different
countries and they are active in different areas
and technologies, so this reduces the
regulatory risk. That portfolio effect can also
come from investing in different countries, but
we like that to happen in one company we
invest in. Unless you are very comfortable
about a particular legislation, you would
probably shy away from investing in a company
that is 100% dependent on policy in one
country. If not, your perception of risk would
increase, and you would expect more money.
2 We focus on the final consumer/ user in the
market. There needs to be an established
business model for the technology initiative to
target. Plus, you need a portfolio approach with
true diversifying factors.
3 Building a balanced portfolio Getting in cheap
and Being hands on and knowing what's
happening.
4 We manage regulatory risk by sticking to our
investment criteria.
5 We make sure the technology has other
applications (than ecological).
6 Our strategy is no different than for other
investment types.
Start-up;
Expansion
Seed/Start-
up;
Expansion
CleanTech
Fund
(including
energy,
water...)
Other
All CleanTech
Start-up;
Expansion
Seed/Start
-up
Expansion;
Replace-
ment
Capital;
Fund
CleanTech
Fund
General VC
Fund with
some CE
General VC
Fund with
some CE
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7 Our investments do not rely on subsidy
supports, or at least they rely very little on
them.
8 We manage RR no differently than we manage
risk in any sector. Disaggregate different risk
types, understand what can be done to mitigate
the different risk, make a judgment about those
areas where significant risk remains. Don't
forget that policy risk is not unique to cleantech
- think about healthcare, telecoms, etc.
Buyout
Seed/Start-
up
General VC
Fund with
some CE
Expansion General VC
Fund
without CE
(yet)
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Curriculum Vitae
Email maryjean.burer@epfl.ch
Address Chef Lieu
Marlioz
74270 France
Telephone +33 450 44 56 24
Mary Jean Bürer
Mary Jean Bürer received her Masters Degree at UCLA in Integrated
Manufacturing Engineering and her Bachelors degree at Claremont McKenna
College in Environment, Economics and Politics. She has over a decade of
experience working to develop and analyze climate and energy policy, having
worked for various UN organizations (UNEP, UNCTAD and the IPCC), various
research institutions (the Swiss Federal Institute of Technology in Lausanne,
the University of St. Gallen, Imperial College and the Lawrence Berkeley
National Laboratory), as well as a US government agency - the California
Energy Commission. She also contributed to starting-up a climate change
trade organization (the International Emissions Trading Association), a clean
energy technology firm, and an environmental non-profit organization.
Therefore, her doctoral research work naturally evolved while working in the
field.
Experience
current Post-doc Researcher, Corporate Strategy & Innovation
(CdM-CSI) at the College of Management and
Technology, Swiss Federal Institute of Technology,
Lausanne, Switzerland. Research work regarding the
impact of public policy on wind energy finance in
Switzerland.
9/2007-3/2008 Program Manager, Investor Programs (INCR), Ceres,
Boston, MA, USA. Co-manager of the Investor Network
on Climate Risk (INCR), the INCR policy working group,
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and team-organizer of the Ceres/UN Foundation 2008
Investor Summit held in New York City with over 400
high-level participants from across the investment
industry.
4/2006-9/2007 Visiting Scholar, Corporate Strategy & Innovation (CdM-
CSI) at the College of Management and Technology,
Swiss Federal Institute of Technology, Lausanne,
Switzerland. Research on policy and private equity
investment in the clean energy sector and dissertation
writing.
6/2005-9/2007 Research Associate, the Institute for Economy and the
Environment, University of St. Gallen, Switzerland. Coauthor
of a study for the Swiss Federal Office of Energy
on the role of government in promoting venture capital
finance for start-up companies developing innovative
clean energy technologies. Co-organizer of “Social
Acceptance of Renewable Energy Innovation” held in
Switzerland in 2006. Doctoral research work was also
performed during this period.
8/2006-11/2006 Climate Adviser, Clean Energy Group, USA. Strategic
input and support on two projects: 1) A transatlantic
initiative on technology innovation policy measures and
instruments, and “Parallel Regimes” to the Kyoto Protocol,
and 2) the development of a European forum of clean
energy public finance institutions with UNEP Sustainable
Energy Finance Initiative.
9/2005-4/2006 Deputy Secretary of the Task Group on New Emission
Scenarios (TGNES) at the Intergovernmental Panel on
Climate Change (IPCC), Geneva, Switzerland.
Contributed to a set of recommendations in relation to the
new emission scenarios for future climate change
assessments of the IPCC.
9/2004-9/2005 Consultant, Intergovernmental Panel on Climate Change
(IPCC), Geneva, Switzerland. Management of numerous
IPCC activities and outreach work for the Secretariat, the
IPCC working groups, the IPCC Bureau and the Plenary
of the IPCC.
10/2004-4/2005 Research Officer, Environmental Policy and
Management group, Imperial College, London.
Coordinated the Innovation Modelling Comparison Project
(IMCP) - a comparison effort of bottom-up and top-down
economic and energy model results on endogenous
technological change.
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8/2004-10/2004 Independent Contractor, Clean Energy Group, USA.
Contracted to prepare a report on emissions trading in the
EU and impacts on clean energy technological innovation.
4/2003-4/2004 Policy Analyst, Natural Resources Defense Council, San
Francisco, California, USA. Contributed to the analysis
and design of California’s global warming auto emission
standards and cooperated with a coalition of non-profit
organizations, government and industry. Performed policy
analysis on GHG mitigation policies for the transportation
sector in California and the United States.
March 2003 Consultant, the Lawrence Berkeley National Laboratory
(LBNL), Berkeley, California. Performed consulting work
on greenhouse gas emissions reporting (for municipal
activities).
6/2002-3/2003 Climate Policy Analyst, California Energy Commission,
Sacramento, California, USA. Developed guidance on
reporting of greenhouse gas emissions in the oil and gas
sector, under California’s voluntary reporting program.
Also provided input on biofuel policy and vehicle CO2
emissions policy in California.
10/2001-3/2002 Consultant, The Environment Business, London, UK.
Climate change business development and climate policy
analysis.
10/2001-8/2004 Co-founder, Eneftech Corporation, initially based in San
Francisco, California. Co-founded and managed the initial
stages of this start-up company. Company now provides
a technology using energy from biomass, solar, or
geothermal heat and is based in Lausanne, Switzerland.
4/2000-4/2001 Program Manager, International Emissions Trading
Association, Geneva, Switzerland. Co-developed this
organization and managed the first year of service
independently.
6/1999-3/2000 Consultant, GHG emissions trading project at the United
Nations Conference on Trade and Development, Geneva,
Switzerland. Performed research on national and
corporate GHG emissions trading schemes and worked
with the private sector to create the International
Emissions Trading Association (IETA).
6/1998-2/1999 Consultant, United Nations Environment Program
(UNEP), Geneva, Switzerland. Managed an international
inter-agency project on the institutional, financial, legal
and trading aspects of the Clean Development
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Mechanism (one of the Kyoto Mechanisms). Mission work
in Kyrgyzstan and Bulgaria for a joint UNEP/WHO project.
10/1997-4/1998 Research Assistant, Institute for Industrial Energy,
Mechanical Engineering Department, Swiss Federal
Institute of Technology, Lausanne, Switzerland.
1/1995-12/1996 Co-founder, Incorporated an environmental non-profit
organization called Evolving Minds Communications,
which produced public service announcements on various
environmental themes. Los Angeles, California.
Qualifications
! Doctor Oeconomiae, University of St. Gallen, St. Gallen, Switzerland,
2008. Dissertation at the Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG): “Public Policy and Clean
Energy Private Equity Investment”.
! Masters of Engineering, Integrated Manufacturing Engineering in
Advanced Transportation Systems, University of California, Los
Angeles, USA, 1997
! Bachelors degree in Environment, Economics and Politics,
Claremont McKenna College, Claremont, California, USA, 1996
Selected Publications
! Bürer, M.J. and Wüstenhagen, R., 2008. Cleantech Venture Investors
and Energy Policy Risk: An Exploratory Analysis of Regulatory Risk
Management Strategies, in: Wüstenhagen, R., Hamschmidt, J.,
Sharma, S., Starik, M.: Sustainable Innovation and Entrepreneurship,
Edward Elgar Publishing, pp. 290-309.
! Wüstenhagen, Rolf, Wolsink, Maarten, and Bürer, Mary Jean, “Social
acceptance of renewable energy innovation: An introduction to the
concept”, Energy Policy, Volume (Year): 35 (2007), Issue (Month): 5
(May), Pages: 2683-2691.
! Bürer, Mary Jean, Menichetti, Emanuela and Wüstenhagen, Rolf, “The
Quest for Energy”, Background Paper for Session 3 – Panel 4 “Energy
and Climate”, Convention on International Law and Politics, November
– 2 December, 2006, St. Gallen.
! Bürer, Mary Jean and Wüstenhagen, Rolf, “The Influence of Regulatory
Risk on Sustainability-Related Venture Capital Investment Decisions”,
Gronen Conference Proceedings, Proceedings GRONEN 2006:
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Sustainability Management, Innovation and Entrepreneurship, July 10-
12, 2006
! Bürer, Mary Jean and Wüstenhagen, Rolf, “The Role of Government in
Supporting the Emergence of Clean Energy Venture Capital
Investment in Switzerland” for the Swiss Federal Office of Energy
(SFOE), October 31, 2005.
! Bertoldi, Paolo, Rezessy, Silvia, and Bürer, Mary Jean, “Will the Kyoto
flexible mechanisms promote end-use energy efficiency and renewable
energy projects”, presented at the 2005 ACEEE Summer Study on
Energy Efficiency in Industry, July 19th - 22nd, 2005, New York.
! duVair, Pierre, Bürer, Mary Jean, and Wickizer, Douglas, “Climate
Change and the Potential Implications for California's Transportation
System”, paper published by the U.S. Department of Transportation for
The Potential Impacts of Climate Change on Transportation: Workshop
Summary and Proceedings, Oct 2002.
! Bürer, Mary Jean “Greenhouse Gas Emissions Trading: Cogen case
studies in the early trading market”, published in Cogeneration and On-
Site Power Production, James & James, Volume 2 Issue 2, March—
April 2001.
! Bürer, Mary Jean “The emerging carbon market - A new means of
financing climate-friendly technology transfer”, published in Asia Pacific
Tech Monitor, by the Asian Pacific Centre for Transfer of Technology,
APCTT, Nov-Dec 2001.
! Bürer, Mary Jean “Funds Offer Carbon ‘Kickers’”, published in
Environmental Finance magazine, October 2001.
Languages
! English (mother-tongue), French and Spanish
Nationality
! U.S. and Dutch nationalities
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