MEASURING MARKET COMPETITION IN THE EU ... - Bank of Valletta

Mario Borg
§ The views expressed in this paper do not necessarily reflect those of the Economic Policy Division.
* Mario Borg is Economics Analyst at the Economic Policy Division of the Ministry of Finance,
the Economy and Investment, of the Government of Malta. He possesses an MA(ISSS) from
the University of Malta and an MSc in Public Economics from the University of York.
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Bank of Valletta Review, No. 39, Spring 2009
MEASURING MARKET COMPETITION
IN THE EU: THE MARK-UP APPROACH §
Mario Borg*
Abstract. A competitive and well-functioning market is imperative
for the efficiency of the economy. The reasons are various; however,
they can be grouped into two categories. First, competitive markets
help correct distortions in the structure of production and thus raise
productivity levels and secondly, stronger competition provides an
increased incentive for producers in the form of lower prices, higher
quality and increased variety. Having a general estimate of the level
of competition of the local market can provide useful information
about internal market functioning. This paper provides an estimate of
the level of market competition for Malta and a number of other
economies. This permits a direct analysis of which sectors of the
economy are operating near their marginal cost function.
Introduction
A competitive and well-functioning market is imperative for the efficiency
of the economy. The reasons are various; however, they can be grouped into
two categories. First, competitive markets help correct distortions in the
structure of production and thus raise productivity levels and secondly,
stronger competition provides an increased incentive for producers in the
form of lower prices, higher quality and increased variety.
Having a general estimate of the level of competition of the local market can
provide useful information about internal market functioning. This paper
provides an estimate of the level of market competition for Malta and a
number of other economies. This permits a direct analysis of which sectors
of the economy are operating near their marginal cost function.
This paper will present a brief theoretical background of what constitutes
market competition. Section 3 will give a general introduction of how

Measuring Market Competition in the EU: The Mark-up Approach
market competition can be measured and will outline the methodology for
measuring market competition. Section 4 will present the results while
Section 5 will explore possible factors underpinning market competition.
Section 6 outlines some methodological issues and limitations.
Theoretical Background
Conventional wisdom in economics posits that there is a negative relationship
between the degree of market competition and profits level of firms.
Consequently, according to classical models, it is in the best interest of profitmaximising
firms to reduce the degree of market competition, especially if
it can be done through some legal means, such as product differentiation
and horizontal merger. Irrespective of the assumptions made, increase in
the contestability of markets and the reduction of the incumbent’s market
power motivate firms to set prices closer to marginal costs. As a consequence,
super normal profits tend to decrease while the allocation of both resources
and goods becomes more efficient.
Recent empirical studies have pointed to a positive effect of product market
competition on productivity growth, particularly at low levels of competition
(Aghion et al., 2005). An increase in competition may also impact on the
dynamic efficiency of firms where firms will have an incentive to innovate
and hence to speed up the move to the modern technology frontier. Such
improvements can have a significant impact on productivity (Ahn, 2002;
Griffith and Harrison, 2004). The general idea behind this argument is that
when regulatory reforms lead to a more competitive output markets, the
wedge between prices and marginal costs is minimised, resulting in lower
degree of market distortion.
Furthermore, a more competitive climate will lead to pressure for the less
efficient firms to exit the market. Through this channel, market shares will
shift from lower productivity to higher productivity firms. A highly influential
contribution in this area was provided by Nickell (1996) who used firm level
data to investigate where changes in competition affect productivity levels
and growth rates.
Until recently, the relationship between the level of market competition and
price dynamics did not receive particular attention, with research being
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Mario Borg
more focused on the relationship between competition and price level. The
connection between market competition and inflation was systematically
dealt with only recently, with an important contributions made by Martins
et al., (1996) and Neiss (2001). Neiss (2001) focused on the empirical evidence
relating the overall degree of competition among firms, as measured by the
mark-up of price over marginal cost, and inflation. The author found that
mark-up is in fact an important determinant in cross-country average
inflation rates. Przybyla and Roma (2005) tested the hypothesis that higher
mark-ups lead to higher inflation and found that competition in product
market plays an important role in explaining average inflation rates across
countries and sectors.
Measuring Market Competition
Several approaches can be utilised to measure market competition, ranging
from the use of indicators to econometric based methods. A method based
on a set of indicators is built on the belief that market competition is a
multidimensional concept which cannot be captured by a single index. The
analysis can be further complicated if it is restricted to specific sectors as this
requires a definition of ‘relevant’ markets. Generally, an indicator-based
approach aims to capture information about the market structure,
performance of firms in the market, and conduct (such as infringements). A
drawback of such an approach is that conclusions drawn from indicators
depend heavily on the benchmark chosen. However, they have the advantage
that many of these indicators are readily available for comparative purposes.
A second approach is to use national accounts data to infer conclusions about
the difference between the selling price and the marginal cost. For obvious
reasons, this cannot be done at firm level; however, sufficient data is available
to permit attempts at a more aggregated level. This approach generally attempts
to estimate mark-up ratios. An advantage of such methods is that they are more
grounded in theory than indicator-based approaches. On the other hand, care
should be taken when interpreting the results as several factors, including data
measurements, might influence the final estimates.
The Mark-up Approach
The approach adopted in this paper is to estimate econometrically the level
of market competition by following the methodology adopted by Roeger
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Measuring Market Competition in the EU: The Mark-up Approach
(1995). This methodology is based on the hypothesis that in a situation of
pure competition the selling price is equal to marginal cost while in a less
competitive environment, the price diverges from marginal cost. The idea
then is to use the ratio between the selling price and marginal cost to assess
the competitiveness of the market. However, while selling price is directly
observable in practice, the marginal production cost is not. This drawback
was overcome by Hall (1988) and later Roeger (1995) who both showed that
under a pure and perfect competition, the nominal growth rate of the Solow
residual is independent of the nominal capital productivity growth rate. It
then follows that the coefficient linking the nominal growth rate of the Solow
residual to the nominal capital productivity growth is the Lerner Index
defined as the ratio of the difference between price and marginal cost and
price.
A brief description of the methodology is as follows:
Δ y t = β Δxt
+ ε t
(1)
where
Δy =
n
Δq+
Δp
−α
Δl+
Δw
−δ
Δn
+ Δp
− 1 −α
−δ
Δk
+ Δr
(2)
t
( ) ( ) ( ) ( )( )
( Δq+
Δp)
−(
Δk
+ r)
Δ x= Δ
(3)
Where q and p are the logarithm of gross output and its respective price, α
is the labour share in total output, l and w are the logarithm of total
employment and the wage rate respectively, δ is the share of intermediate
output in total output, n and p n are the logarithm of intermediate inputs and
their prices respectively and k and r are the logarithm of capital and its rental
price. In turn the rental price (r) is calculated as:
exp ( i − π ) + ) pt
r = ξ
where i is the long-term nominal interest rate, t p exp
is inflation in year t, π
is the expected inflation estimated by taking a linear trend and ξ is the rate
of depreciation set at 5 per cent. A measure of capital stock for Malta is not
available. To overcome this problem the change in capital stock ( Δ k)
is
estimated by assuming that the capital intensity ratio (that is capital stock
over GDP) in 1995 is 2 and thereafter, it is calculated by applying the
standard formula for capital formation: Δk t = I t − δk t−1where
I is gross
fixed capital formation.
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Mario Borg
Δ can be interpreted as the nominal Solow
residual and the explanatory variable is the growth rate of the nominal
output/capital ratio. The appealing feature of equation (1) is that the
productivity term vanishes and a direct estimation of β can be carried out by
the OLS method. Another advantage of this method is that the price and
volume variables can be grouped together and only nominal variables
appear in the equation. On the other hand, it is worth noting that equation
(1) provides an unbiased estimate of β only in the presence of constant
returns to scale. Consequently equation (1) allows estimating the Lerner
Index and the mark-up as:
The dependent variable ( y)
Mark-up = ( 1−β)
24
1
Mark-up ratios measure the degree of competition in a sector. A mark-up
ratio larger than 1 implies that prices are larger than marginal cost and
therefore may be evidence of market power in an economy or sector.
Results
Different sources of data were used for the estimation of mark-up. Most of
the data is from the EU Klems database, Ameco database, and OECD STAN
database. In all 22 European States were covered. Data for 7 EU Member
States were missing and these were not considered. 1 The time period
covered was from 1990-2006 for most economies, with some being restricted
to from 1994 to 2005 due to data constraints.
The results are presented in two parts. The first part presents the estimates
for Malta and a number of other countries. The second part outlines some
stylish observations obtained from the analysis.
Cross-Country Comparisons
For comparative purposes, the mark-up for 22 economies was estimated
using equation (4). Figure 1 illustrates the estimated mark-up, together with
1 The 7 EU Memberstates which were not considered were Bulgaria, Greece, Hungary,
Ireland, Romania, Spain, and Slovenia while Switzerland and Norway were included in
the analysis as non-EU.
(4)

Measuring Market Competition in the EU: The Mark-up Approach
a 5 per cent confidence interval for each country. The estimated mark-ups
range from a high of around 1.46 (Cyprus) to low of 1.22 (Switzerland). It can
be noted that most of the estimated values are around the values of 1.25 to
1.35. The estimated value for Malta was 1.32 with a 5% interval of 1.28 to 1.34.
Such a value is relatively high, ranking the sixth highest among the countries
analysed. Only Cyprus, Lithuania, Italy, Latvia, and Poland had higher
scores.
Looking at estimates for the whole economy can conceal the possible level
of competition within sectors as scores for different sectors in an economy
can cancel each other. Hence, useful insight can be obtained by digging
further down and calculating mark-up levels at more disaggregated levels.
Figure 2 presents the mark-up ratiosfor the 15 main economy activities.
Figure 2 also serves to summaries information with regards the median,
minimum and maximum values for each economy at each sector.
As can be noted, the mark-up for Malta is relatively high for four out of the
fifteen sectors under consideration. Particularly high mark-ups are noted
for the Financial Intermediation sector, the Real Estate and Renting sector,
the Wholesale and Retail sector, and the Other Community Services.
Figure 1
Cross Country Comparisons of Mark-up Estimates
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Mario Borg
26
Figure 2
Mark-up Across Economic Activities
It is noteworthy that these particular sectors are important sources of
intermediate inputs in other sectors of the economy. This might have
significant ‘knock-down effects’ on the economy.
A more in depth analysis of the mark-ups presents some interesting findings.
Sectors which exhibit relatively high mark-ups are agriculture, fishing,
publishing and printing, manufacturing of furniture, sales and maintenance
of vehicles and auto parts, hotel and restaurant services, and real estate. On
the other hand, low mark-ups are associated with most of the manufacturing
activities, especially those export oriented. The high estimates for some of
the sectors might be surprising, but it must be kept in mind that the period
under consideration relates to the 1995 to 2005 period, and thus recent
reforms and liberalisation measures are not fully captured.
Some Stylised Observations
This section will outline some stylised results that emerged from the
sanalysis so far. Unsurprisingly, the results reject the hypothesis of perfect

Measuring Market Competition in the EU: The Mark-up Approach
competition in the countries under observation. Indeed, across all the main
economic activities in all countries, mark-up ratios are generally statistically
significantly larger than 1. This was widely expected as perfect competition
is rarely observed in reality.
A second result that emerges is that mark-up levels differ considerably
across countries. This observation raises questions regarding the effect of EU
single market. This in part confirms the finding of a study by Badinger (2007)
who found that mark-up ratios have decreased in the manufacturing sector
while they tended to increase in the services sector since 1990s in spite of the
efforts relating to the strengthening of the EU single market.
A third observation that is closely related to the previous results is that
mark-ups are highly heterogeneous across sectors, with industries which
either have particular economic and social characteristics such as agriculture,
fishing, and mining or which are characterised by strong network effects
tending to display higher mark-ups. Such examples are the transport and
communication sectors and the electricity, gas and water sectors.
A related further observation that is noted is that mark-up ratios are on
average higher in services industries than manufacturing industries, and
this seems to hold for all countries under observation. This is not surprising
as manufacturing is likely to be exposed to more international competition
than services. This is illustrated in Figure 3 where the distribution of
manufacturing is skrewed much more to the left than the ratios related to
services. It is also noteworthy that the estimated mark-ups in manufacturing
are relatively concentrated around the median while the estimated mark-up
for the services are more disperse. 2
Factors that Underpin the Level of Market Competition
The analysis can be extended by exploring what factors are likely to
influence the mark-up ratio and hence the level of market competition. A
priori, the smaller the market, the lower the degree of competition as natural
monopolies and oligopolies tend to prevail in small markets. In addition the
2 This can also be confirmed by looking at the mean and median. For services the mean stands
at 1.45 and the median at 1.37 while for the manufacturing sectors the mean is 1.29 and the
median 1.19
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Mario Borg
Frequency
degree of market competition in small economies is hindered due to
invisibility of overhead costs, lack of economies of scale, and limited
administrative capacity of the regulator.
It can be argued that advanced economies are more likely to have highly
competitive market structures. This is built on the premise that more
developed and economically advanced countries tend to be more averse to
monopolistic structures. However, there might be a problem of causation
since it is not clear whether economic development impacts on market
structure or vice-versa.
Another factor that is likely to impact on the level of mark-up is the degree
of economic openness. This follows from the premise that the impact of
international competition will lead domestic firms to operate nearer to their
marginal cost curves as in the absence of such pricing strategies the firms
will lose their market share.
Thus more formally, the relationship between mark-up and the variables
mentioned can be modelled as follows:
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6.0
5.0
4.0
3.0
2.0
1.0
0.0
Figure 3
Dispersion and Distribution of Mark-up
1.0 1.0 1.1 1.1 1.2 1.2 1.3 1.3 1.4 1.4 1.5 1.5 1.6 1.6 1.7 1.7 1.8 1.8 1.9 1.9 2.0 2.0 2.1 2.1 2.2 2.2
Markup
All Sectors (right axis)
Services (Exl. Public Adm, Education, Health, & Other Community)
Manufacturing (exl Agriculture, Fishing, Quarying & Mining)
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0

Measuring Market Competition in the EU: The Mark-up Approach
Mark-up = α + δ1S
+ δ 2D
+ δ 3O
+ ε 1
(5)
Where:
O = Openness and is defined as the average of export and imports as a ratio to GDP;
S = Size measured by the log of GDP;
O = Level of development as measured by GDP per capita.
Estimation of the coefficient can be made by OLS. The results are shown in
Table 1, where the numbers in parenthesis are standard errors.
Table 1
Regression Results
Mark-up = 1.56 -0.02 S -0.04 D -0.17 O
2
R = 0.
48
(0.0076) (0.0248) (0.0770)
n = 20
δ1
< 0; δ 2 < 0;
δ 3 < 0
Table 1 confirms the hypothesis that the level of mark-up in an economy is
negatively related to the size of the economy, to the level of development,
and to the degree of openness of the economy.
Methodology Issues and Limitations
This section briefly highlights limitations associated with the computation
of mark-up using the methodology described in this paper. First, the
estimates are obtained assuming constant returns to scale. This assumption
is debatable especially in small internal market like Malta’s. Secondly, the
different sectors’ output is measured at base price, i.e. including subsidies.
This can lead to higher mark-up values. Thirdly, the lack of data in connection
with capital stock in Malta and a number of other economies can also impair
the accuracy of the estimates.
One must keep in mind that the estimates are backward looking and can be
taken as an average of the period covering 1995 to 2005. This means that
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Mario Borg
recent reforms are completely ignored. This weakness can be particularly
relevant for specific sectors of the economy.
Conclusion
The paper explored the level of competition in a number of European
countries including Malta. The mark-up for Malta was estimated to be 1.32
which is relatively high compared with the economies under observations,
in particular in four out of the fifteen economic sectors, namely Financial
Intermediation, the Real Estate and Renting, and the Wholesale and Retail
sector.
From the analysis it also emerged that mark-ups differ considerable across
sectors with mark-ups being higher within services than in the manufacturing
sectors, which is consistent with the idea that certain services are more
sheltered from international competition than are manufactured goods.
This paper also found that the level of market competition as measured by
the mark-up is positively related to openness while it is negatively related
to the size of the economy and the level of development.
References
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(2005) “Competition and Innovation: An Inverted-U Relationship,”
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AHN, S. (2002) “Competition, Innovation and Productivity Growth: a
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Department.
BADINGER, H., (2007) ”Has the EU’s Single Market Programme Fostered
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GRIFFITH, R., and HARRISON, R., (2004) “The Link Between Product
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HALL, R.E. (1988) ‘The Relation Between Price and Marginal Cost in U.S.
Industry,” Journal of Political Economy, Vol. 96 (5): 921-947.
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Measuring Market Competition in the EU: The Mark-up Approach
MARTINS, J.O., SCARPETTA, S. and PILAT, D. (1996) “Mark-up Ratios in
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