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Final Year Project
A STUDY ON PROFITABILITY- CONCENTRATION
RELATIONSHIP IN PAKISTAN MANUFACTURING INDUSTRY
FAIZAN HANIFBB-3-05-3014
SUPERVISED BYMr. IMTIAZ ASKARI
KARACHI INSTITUTE OF ECONOMICS AND TECHNOLOGY
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ACKNOWLEDGEMENT
I am thankful to my Project supervisor Mr. Imtiaz Askari, whose guidance,
support and experience benefited me in the completion of this project. I am
grateful to my supervisor for providing me such a practical oriented chance to
understand the theory of profitability. He provided me information and support
which has led me towards the completion of this project.
Last but not the least; I would render great thanks to my parents and friends who
had directly cooperated with me throughout the period of my research.
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TABLE OF CONTENTS
1. Introduction
2. Literature Review
3. Variables
4. Model
5. Methodology
6. Result
7. Conclusion
8. Recommendation
Appendix:
A-1 Data A-2 Reference
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INTRODUCTION
I probed and elucidate a study on profitability- concentration relationship in
Pakistan manufacturing industry. This study includes 3 Industries i.e Cement,
Textile and Sugar. The study uses a Multiple Regression Technique. The
theoretical framework is developed on the basis of literature survey that was
inclusive of all the required dependent and independent variables necessary for
the study.
This study tests two competing hypotheses concerning the link between market
concentration and profitability: the structuralist view that concentration facilitates
the exercise of market power, and the Demsetz-led counter-argument that
concentration and profitability jointly stem from the superior efficiency of large
firms in such markets. The test is based on the application of multiple regression
analysis for a cross-section of 3 Pakistans manufacturing industries for 2001-
2006. Separate regressions are run on two different groupings of firms: the
number one firms and the rest, these groupings being chosen to represent
strategic groups.
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LITERATURE REVIEW
There is strong evidence that the market share of an entity has a U-shaped
relationship with profitability. The paradigm postulates that market characteristics
(e.g. concentration and barriers to entry) will have an influence on the conduct of
firms, which in turn will influence the performance of firms within that market.
Performance is determined by the conduct of firms, which in turn is determined
by the structural characteristics of the market. These structural characteristics
relate to concentration and barriers to entry. The theory dictates that higher
levels of concentration and higher barriers to entry are expected to be associated
with higher profitability. [SIMON FEENY]
Firms which make up the market structure exhibit peculiar behavior which is
determined in shape of features like market share, their concentration in a
geographic region, industry growth, how much they spend on research and
development, advertisement, and their size in the pertinent industry. Firms
having good such feature are in better position to take advantage by
implementing their strategies for profit making. [PANT]
There are series of measure that show how profitable a firm is such as Gross
Margin, Operating Margin and Berry ratio. Gross income reflects in parts the
value added by a company, Operating income is a measure of the reward that a
company earns for its functions. Berry ratio to measure a firms profitability.
[LEAHY]
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Market share shows the extent of a firms control over the market and it indicates
its position in the market. Market share is defined as the sales of the company
divided by the sales of the industry then multiply this ratio by 100 to get market
share in percentages. A positive relationship has been reported between market
share and rate of return in a number of empirical studies. [GALE]
There is a huge literature overseas, particularly in the United States (US), which
tests the hypothesis that the elevation of price above costs will tend to be greater
in concentrated markets.1
since prices and costs are generally difficult to observe
and compare, many studies make use of the price-cost margin (PCM). Any
factors which are associated with market concentration, and which lead to higher
prices and/or lower costs, will result in a positive association between
concentration and the PCM (Clark, Davies and Waterson, 1984).
This view was later challenged by Demsetz (1973, 1974) and his supporters, who
argued that some industries become concentrated because of the superior
efficiency of large firms. By gaining economies of scale or other advantage
certain firms grow large, causing the market to become concentrated, and earn
high profits, which leads the industry average profitability to be higher.2Hence
efficiency provides the link between market concentration and elevation of price
above costs. This view implies that rising concentration should be associated
with a growing disparity in the profitability of large and small firms, in contrast to
the market power hypothesis, under which higher prices should benefit all firms
equally (since both large and small firms are assumed to be equally efficient).
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The competing hypotheses of market power and efficiency as determinants of
inter-industry variations in PCMs have been tested in several studies (e.g.,
Demsetz, 1973; Allen, 1983; Chapple and Cottle, 1985; and Martin, 1988). The
usual approach is to include among the independent variables measures of
market concentration and large firm relative efficiency in cross-section analysis.
This view implies that rising concentration should be associated with a growing
disparity in the profitability of large and small firms, in contrast to the market
power hypothesis, under which higher prices should benefit all firms equally
(since both large and small firms are assumed to be equally efficient).
Industries are composed of groups of firms, each group following similar
strategies, and each being insulated to some degree from new entrants and firms
in other groups by a generalized from of entry barriers called mobility barriers.
These barriers prevent the strategies of successful firms from being imitated by
outsiders, thereby preserving their higher profits. The profitability of firms in a
strategic group depends on three factors: industry-wide market features which
influence the profits of all firms; the amount of protection offered by entry
barriers; and the amount of rivalry (or lack of it) with other groups.
Variations in PCMs between industries appear to arise both from relative
efficiency and market power effects. Leading firms earn higher profits partly
because of greater efficiency. In Demsetzs view, such efficiency reflects not
only economies of scale, but generally any superiority in performance which
enables firms to grow at the expense of rivals.
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However, unless protected by patent, copyright or trademark, Demsetz argues
that these efficiency advantages will soon be replicated by rivals, subject to
delays arising from imperfect information and other market frictions.
Market power effects are associated both with the market shares of leading firms,
and with group interactions, such that market power enjoyed by one group may
spread through spillover effects to others within the industry. Leading firms seem
to enjoy higher profits when their market share is high, and when the presence of
high mobility barriers appears to blunt rivalry both from new entrants and
between groups, allowing them to price independently.
It was found that the price-cost margins of leading firms are larger when: own
market share is larger, number two firms market share is smaller, other strategic
groups within the industry have higher margins, own relative efficiency is high,
and plant scale economies are large in relation to market size. The first three
factors support market power explanations of the profitability-concentration
relationship; the last two factors imply that market concentration and profitability
are jointly related to the superior efficiency of large firms. [MICHAEL PICKFORD
AND MARCUS WAI]
Movements in profit margins or price cost mark-ups are an important component
of changes in prices. In recent years profit margins have undoubtedly accounted
for a significant part of the increase in prices perhaps as a much as a third.
Given this, the behavior of mark-ups over the business cycle is of interest to
anyone concerned with the behavior of prices in the short to medium run. It is
also of interest because of the potential implications for the real economy. A
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number of recent macroeconomic models identify counter-cyclical movements in
the mark-up as a simple transmission mechanism by which changes in nominal
demand can lead to pro-cyclical movements in employment in the absence of
nominal rigidities.
There are two main results. First, average mark-ups are significantly greater
than one in all but a few manufacturing industries, and profit margins are
positively associated with both firm market share and industrial concentration,
and display a significant degree of persistence.
Second, mark-ups are found to be pro-cyclical, and the pro-cyclicality exhibited
by firm profit margins is found to only partly reflect movements in the standard
determinants of margins. Once the latter are controlled for, profit margins still
display a pro-cyclical pattern. This finding suggests that price pressures increase
during recovery periods and decrease during recessions. It also raises doubts
about macroeconomic models that assume that demand shocks may affect
employment via counter-cyclical mark-ups. [ IAN SMALL]
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VARIABLES
The industry sample consisted of 3 industries i.e Cement, Textile and Sugar.
Demsetz (1973) was the first to consider the determinants of profitability for
different size classes of firms in each industry. Chapple and Cottle (1985)
extended his approach by placing it within the mainstream market structure-
conduct-performance paradigm, where industry PCMs are a function of market
concentration and various other structure and conduct variables. To incorporate
relative efficiency they split each industry into two groups.
The dependent variable is the price-cost margin (PCM). We measured it as the
gross return on sales:
PCMij= SALESij - COST OF SALESij
SALESij
Where i denotes the industry and j the firm group.
The independent variables can be divided into two groups, the first designed to
control for industry- wide differences between industries, and the second relating
to differences between groups.
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The following control variable was used:
Market growth (MGR): even competitive industries can earn supernormal profits
when in disequilibrium states. Hence MGR, measured as the percentage change
in turnover between 2001- 2006, was included to control for variations in industry
profitability induced by disequilibrium. For example, rapid growth, by causing
demand to surge ahead of investment in additional capacity, might lead to
abnormally high profit rates. This variable helps to correct, in a crude way, for
the use of cross-section data to estimate long-run relationships. Other sources
of deviations from long-run equilibrium will be captured by the error term.
Other factors likely to cause PCMs to vary between industries could not be
controlled for because of lack of data and other difficulties. These were: price
elasticity of demand and risk (both positively associated with PCMs), and rent-
seeking and X-inefficiency (where high values should raise costs and reduce
PCMs). Also, US studies usually find a stronger profitability-concentration
relationship for consumer goods industries compared to producer goods
industries, apparently reflecting the greater scope for product differentiation with
the former (Collins and Preston, 1969). However, this effect might be captured
by the ASR variable, since differentiation is linked to advertising, which typically
is higher in consumer goods industries.
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The second groups of independent variables were used to represent each of the
three intra-industry groups:
Market power(CR): market power was measured by sales-based concentration
ratios calculated for each group. CR1 and CR2 are equivalent to the market
shares of those firms; Because group shares sum to one, only two of the three
ratios can be incorporated in the model at one time to avoid multicollinearity.
Group characteristics: the theory of strategic groups suggests that, holding all
else constant, the market power exercised by one group should be greater, the
greater the market power exercised by the other groups in the industry. This
implies, for example, that the market power of the leading firm, measured by
PCM1, should be positively associated with the price-cost margins of the number
two (PCM2). Hence PCM2 is included as determinants of PCM1.
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THE MODEL
The following two models were developed for each industry:
For strategic group 1:
PCM1 = 0 + 1PCM2 + 2CR1 + 3CR2 + 4MGR +
For strategic Group 2:
PCM2 = 0 + 1PCM1 + 2CR1 + 3CR2 + 4MGR +
Where,
PCM1 = Price cost margin of strategic group 1
PCM2 = Price cost margin of strategic group 2
CR1 = Market share or market power of strategic group 1
CR2 = Market share or market power of strategic group 2
MGR = Growth rate of the industry
= Error term, and
0, 1, 2, 3 and 4 are the respective coefficients.
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METHODOLOGY
The study comprised of 3 industries i.e Cement, Textile and Sugar and in each
industry a sample of over 15 companies was taken. Each industry was divided
into two strategic groups. First strategic group comprised of the top 4 to 5 market
leaders and the remaining companies in that industry made up the second
strategic group. Regression was run separately on each strategic group in each
industry respectively.
This study tests two competing hypotheses concerning the link between market
concentration and profitability: the structuralist view that concentration facilitates
the exercise of market power, and the Demsetz-led counter-argument that
concentration and profitability jointly stem from the superior efficiency of large
firms in such markets. The test is based on the application of multiple regression
analysis. Separate regressions are run on three different groupings of firms: the
number one firms and the rest, these groupings being chosen to represent
strategic groups.
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RESULT
The result of each strategic group in every industry is as follows:
CEMENT INDUSTRY
STRATEGIC GROUP 1
After running regression for strategic group 1 we get:
STRATEGIC GROUP 2
After running regression for strategic group 2 we get:
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SUGAR INDUSTRY:
STRATEGIC GROUP 1
After running regression for strategic group 1 we get:
STRATEGIC GROUP 2
After running regression for strategic group 2 we get:
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TEXTILE INDUSTRY
STRATEGIC GROUP 1
After running regression for strategic group 1 we get:
STRATEGIC GROUP 2
After running regression for strategic group 2 we get:
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The adjusted R2s for all three equations are high, indicating that the independent
variables explain over half of the variance in the dependent variables. R2s and
the t-statistic are all highly significant. The F-statistics are also significant and
the probability is also under 10%.
The following diagnostic tests were performed on the equations. The application
of Whites test for heteroscedasticity found that all three accepted the null
hypothesis that the residuals were homoscedastic. The Durbin-Watson (D-W)
Statistic was also used to test for autocorrelation, but the tests were inconclusive
as the findings belong to the quadrant of indecision.
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CONCLUSION
We find that the price-cost margins of leading firms are larger when: own market
share is larger, number two firms market share is smaller, and other strategic
groups within the industry have higher margins, own relative efficiency is high,
and the market is growing as a whole. The first three factors support market
power explanations of the profitability-concentration relationship; the last two
factors imply that market concentration and profitability are jointly related to the
superior efficiency of large firms.
Using group concentration ratios as conventional measures of market power
reveals that the PCMs of number one firms are positively influenced by their own
market shares (CR1), and negatively influenced by the market shares of number
two firms (CR2), both at the one percent level of significance.
Leading firms earn higher profits partly because of greater efficiency. Such
efficiency reflects not only economies of scale, but generally any superiority in
performance which enables firms to grow at the expense of rivals.
The market will then become more concentrated, and the higher profits of the
leading firms will push up the industry average, causing concentration and
profitability to be related.
Market power effects are associated both with the market shares of leading firms,
and with group interactions, such that market power enjoyed by one group may
spread through spillover effects to others within the industry. Leading firms seem
to enjoy higher profits when their market share is high, and when the presences
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of high mobility barriers appear to blunt rivalry both from new entrants and
between groups, allowing them to price independently.
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RECOMMENDATIONS
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APPENDIX 1