14-1190b-innovation-managing-risk-evidence

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Investors face additional risks when investing in a variety
of new situations — e.g. new technologies, new policy
environments. Some of these risks can be mitigated by
policy (see Part B), but the nature of capital markets,
in which lenders also have to be persuaded of the yet
undemonstrated prospects, mean it is impossible to cover
them all.
• Behaviour different from that embodied in the
standard “rational” representation of individuals in
economic models can limit innovation. Our tendency
to focus on the short-term, to dislike risk and uncertainty,
and to stick with the status quo can lead to “innovation
neglect” in public and private institutions alike (see Part B).
• The development of human capital and associated
markets is restricted by its own spillovers. The
education of individuals provides social benefits, by
providing human capital upon which public and private
sectors, and society as a whole 20 , can draw. These benefits
are not fully captured by the educated individual, or by
schools or firms that may educate that individual, so
markets tend to provide less education than is socially
efficient 21 .
• Sustained support for incumbent technologies.
Most energy sectors, for instance, have been historically
designed for fossil fuel use, thus development of low-/
zero-carbon sources of energy may be slowed and many
aspects of the energy system may need to change in
addition to the sources. Existing institutions, infrastructure
and policies that support certain sectors, can result in
sector inertia that provides “barriers to entry for new
technologies” 22 .
It is not just markets that fail. Governments, with good
intentions or otherwise, having different competencies and
facing diverse pressures, can also fail. Attempts to pick
winners sometimes lead to second-guessing markets and
wasted resources 23 . A poorly designed policy, or one that
does not carry credibility, can present a greater threat to
innovation than the market failures it was supposed to
resolve 24 . Reasons for government failure include:
• asymmetric information;
• lack of experience or competence in business or science;
• rent-seeking or lobbying by private actors;
• short-term time horizons driven by electoral cycles.
The ‘systems of innovation’ approach focuses on how
firms of different types, government actors and other
economic agents, are embedded in ‘systems of innovation’
(sectoral, regional, national), or ‘innovation ecosystems’ 25 .
The approach emphasizes the importance of interactions
between actors in such systems (which are often non-linear,
involving important feedback loops), and how knowledge is
diffused throughout the economy 26 . In distinction from the
‘market failures’ approach, the innovation systems literature
focuses on the importance of both market and non-market
actors, relationships and norms in determining innovation
behaviour. This expands the possible scope of useful state
intervention 27 , but at the same time provides further
possible sources of government failure. Poor government
policy may, for example, override existing norms (such as
those for openness among academic researchers) and result
in unexpected negative effects on innovation 28 .
Both frameworks bring valuable insights to our
understanding of innovation and how it can be fostered
to promote growth. From here on, we focus more on the
market failure framework because it has a longer-standing
literature, but we draw on both.
(iii) Innovation, risks and incentives
There is significant potential for policy to boost innovation,
and thereby boost economic growth. To design policy
that effectively and efficiently fosters innovation, we must
understand how actors along the innovation chain respond
to the risks and incentives they face.
“Risk” and “uncertainty” in economic analyses are often
used interchangeably but the American economist Frank
Knight distinguished them along the following lines 29 :
• “Risk” can be thought of as measurable and
quantifiable in terms of probabilities, and is
most useful for describing investment in predictable
advances further along the innovation chain. Intel’s
investments in chip technology, for example, produce
incremental improvements that are predicted years in
advance according to Intel’s “tick-tock” model of chip
improvement 30 , where improvements are reliable enough
that the metaphor of a clock fits.
• “Uncertainty” can be thought of as that which is
not easily measurable in terms of probabilities, where
we may even be unsure of what possibilities exist. This
can be the case in complex, chaotic systems composed
of many interacting elements — and along the innovation
chain, “all of the actors operate under conditions of
uncertainty” 31 . This applies especially in early phases of the
chain, and in innovation over the long term. Policymakers
could not have foreseen that studying jellyfish would
found a large part of the biomedical revolution, or that
military packet switching technologies intended to make
military communication systems more resilient in the
event of a nuclear attack would lead to the internet, social
networking and the avalanche of apps spawned in Silicon
Valley.
Private actors face a diversity of risks — financial risks,
career risks, legal risks, and many beyond — when they
choose to innovate. The balance of risks and incentives
determines what choices innovators (entrepreneurs,
investors, inventors, bureaucrats, etc.) will make.
Being exposed to risk is part of doing business. But some
risks are appropriate guides to decision-making, while others
may be unhelpfully imposed. Deciding not to proceed with
an innovation investment because there is a high risk of
insufficient demand is a sensible decision — the kind of
decision that firms make routinely in order to maximize
their value. Deciding not to proceed with a very promising
innovation because of the risks imposed by regulatory
unpredictability (e.g. policy risk), lack of appropriability (e.g.