The Empirical Economics Letters, 5(6): (November 2006)
ISSN 1681 8997
Alternative Concepts of Competition and the Greek Manufacturing Persefoni Tsaliki * Department of Economics, Aristotle University of Thessaloniki 54124 Thessaloniki, Greece Email:
[email protected]
Lefteris Tsoulfidis Department of Economics, University of Macedonia 156 Egnatia Street, P.O. Box 1591, Thessaloniki, Greece Email:
[email protected] Abstract: This paper presents the essential characteristics of the classical and neoclassical theories of competition and using data from Greek manufacturing industries empirically tests their fundamental propositions. First, to what extent does the degree of concentration relate to profitability across industries and second to what extent does the proposition of the long-run equalization of interindustry profit rates hold. The results of the analysis lend support to the classical propositions of free competition.
Keywords: Competition, concentration, incremental rate of return, regulating capital JEL Classification: B10, L11, L25, L60 1.
Introduction
Classical economists viewed competition as the mechanism through which economic phenomena become independent of “people’s will” and give rise to regularities amenable to abstract theorization (e.g., J.S. Mill, 1848, p.147). In this approach, competition is regarded as a process of rivalry among firms in their persistent struggle for survival which is associated with firms’ continuous efforts to innovate and reduce the cost of production in order to expand their market share at the expense of their rivals. By the mid-1870s, this dynamic notion of competition was gradually replaced by the neoclassical static notion of competition in which the number of firms in the market is the decisive feature of the degree *
We thank Theologos Dergiades, Aris Papagergiou and Dimitris Paitaridis for their helpful comments.
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of competition. The fewer the number of firms the lower the degree of competition and, thus, the higher the profitability of the firms that comprise the industry. The purpose of this paper is to test the fundamental tenets of these two alternative theories using data from the Greek manufacturing industries. The remainder of the paper is organized as follows: Section 2 highlights the most important features of the alternative conceptions of competition. Section 3 investigates the extent to which the degree of concentration in Greece changed over time and also subjects to empirical testing the hypothesis whether or not profits are directly related to the degree of concentration. Section 4 discusses the extent to which there is a long-run equalization of profit rates. Finally, Section 5 concludes and makes some remarks about the direction of future research efforts. 2. Static and Dynamic Conceptions of Competition The static notion of competition is mainly associated with neoclassical economics, which is taught in the standard microeconomic theory. According to this approach, competition is viewed as a state of equilibrium, where perfectly informed agents producing a product exactly like their “rivals” operate in a market with no entry or exit barriers. In such an environment, each agent in and of itself cannot affect the market outcome and simply reacts to parametrically given prices. The number of participants in an industry defines the degree of competition and when the number of firms is sufficiently large one expects a uniform profitability within and across industries. By contrast, as the number of participants dwindles, phenomena such as oligopolistic or monopolistic behaviour arise which lead to differential profitability between firms within the industry but also between industries. One of the fundamental propositions in standard microeconomic theory is that the existence of profits over and above the average is attributed to market imperfections and to the degree of monopoly of firms. In such non-competitive equilibrium, some prices remain higher than their marginal cost and society underutilizes its resources. Within the neoclassical approach to competition there are two major lines of research. The first, the “imperfectionist”, is associated with people from Harvard University like Bain and J.K. Galbraith, who argue that actual competition deviates from perfect competition, something that makes the government’s corrective role of markets’ imperfections imperative. The antimonopoly legislation that has been instituted in the USA and has been adopted to a great extent in European countries is rooted into this “imperfectionist”
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approach. The second line of research, the “perfectionist”, is associated with the University of Chicago and its main representatives are Stigler and Harberger who claim that the distinction between perfect and imperfect competition is theoretically absolutely valid; nevertheless, the empirical evidence shows that the actual deviations are minimal and for practical purposes can be ignored. Consequently, government intervention cannot really achieve situations much different from those that arise spontaneously from the free operation of the market. 1 The dynamic notion of competition is found in the writings of classical economists, Adam Smith (1776), David Ricardo (1817) and John Stuart Mill (1848), who theorized competition as a process characterized by the free mobility of capital and labour, which taken in the long-run leads to the equalization of profit rates across industries. 2 For classical economists, the mechanism mainly responsible for the elimination of interindustry profit rate differentials is the inflow or outflow of capital and not necessarily the entry or exit of firms. Capital flows in and out of industries in its relentless effort to take advantage of profit opportunities. This process of capital flows by no means implies that overtime there is equality of profit rates between industries, but that the equalization is only tendential and the equality is established on an average and after the passage of long time. At any moment in time one can only observe differences, small or large, between an industry’s profit rate and the economy’s average. Figuratively speaking although both conceptions of competition would argue for the equalization of profit rates between industries, the neoclassical one would conceive such an equalization to take place in a short period of time, whereby an industry’s profit rate initial differences (positive or negative) from the average will die out and consequently one could soon expect the converging of this industry’s profit rate to the economy’s average. By contrast, in the classical conception of competition there is no convergence, but persistent 1
It is interesting to note that the promarket conclusions of this approach are reached using time series data spanning over a long period of time. However, such an approach is in deviation to the neoclassical concept of competition, which is in essence static and it is oriented to the study of market forms and not to changes over time. 2 The classical notion of competition as a process of rivalry between firms can also be found in the works of Joseph Schumpeter (1942) and the modern Austrian economists (Kirzner, 1987). In both approaches, the entrepreneur is a pivotal figure, who assumes the risk and uncertainty that are inherently built into the system in which individuals grope toward equilibrium.
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fluctuations of industries’ profit rates around the economy’s average; hence, the profit rate of any particular industry will be different from the average; however, over a long period of time these deviations cancel each other out and their sum is expected to be not different from zero. 3. Concentration and Profitability in Greek Manufacturing Industrial organization studies for the Greek economy, in general, and for its manufacturing sector, in particular, are rare; those few studies usually measure concentration ratios at the 2-digit industry aggregation level. 3 In the present study, we employ data that refer to 3digit industry level providing a classification of 91 industries from three consecutive manufacturing censuses (years 1978, 1984 and 1988). The concentration ratios of the industries refer to the employment base4 and as a proxy for profitability we use the share of gross profits to total sales of large-scale industry. 5 The regressions between the so-estimated profit margins on sales (PMS) against the concentration ratio of the top four firms in the industry (CR) did not display a statistically significant relationship. In fact, the coefficient of determination was found to be indistinguishable from zero and the coefficient of the independent variable not statistically significant. The simple regressions with the Herfindahl Index (ΗI) as an index for concentration ratio provided similar results with that of the CR for the two years of our analysis. Similarly, in non-linear regressions the results are negative for the neoclassical theory of competition. 6 Hence, the correlation of profitability with the degree of concentration is too weak and does not lend support to the view that the concentrated industries necessarily display higher profitability as a result of their monopoly power. In
3
For example, Droucopoulos, 1979; Pakos, 1982; Antonakis, 1986; Droucopoulos, 1991; Tsaliki and Tsoulfidis, 1998 and Kaskarelis and Tsoulfidis, 1999.
4
We measure the employment of the top four firms of each of the 91 large-scale industries, that is, the firms that operate in these industries employ at least ten workers, as a percentage of the total employment in the industry. 5
Data on profits and sales for the year 1978 are not available; thus our analysis is essentially restricted to the years 1984 and 1988. Nevertheless, we mention the concentration index of the year 1978 to show that the changes in the degree of concentration are slow.
6
As mentioned, we cannot test the hypothesis of the degree of concentration (CR or HI) against profitability for the year 1978 because of the lack of published data on sales and profits.
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Figure 1 we plot the profit margins on sales against the CR and the HI for the years 1984 and 1988. Figure 1: Concentration Indexes (CR & HI) and the Profits to Sales Ratio, 1984 and 1988 0,4
PMS 84
0,3
0,2
0,1
0 0
0,2
0,4
0,6
0,8
1
1,2
0,4
0,5
0,6
CR4 0,4
PMS 84
0,3
0,2
0,1
0 0
0,1
0,2
0,3 HI
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Figure 1 continued 0,5
PMS 88
0,4
0,3
0,2
0,1
0 0
0,2
0,4
0,6
0,8
1
1,2
0,4
0,5
0,6
CR4 0,5
PMS 88
0,4
0,3
0,2
0,1
0 0
0,1
0,2
0,3 HHI
An inspection of the graphs above reveals that in the period between the years 1984 and 1988 there is not any fundamental change in the structure of the Greek manufacturing. 7 Furthermore, the concentration index of the top four firms for the three years does not reveal any significant change, as this can be judged from the summary statistics that we site in Table 1. The results are similar for the HI. 7
Unfortunately, there are no more recent manufacturing censuses and so we cannot examine changes in the recent years. However, to the extent that we know the literature Droucopoulos and Papadogonas (2000) examining unpublished data of the year 1992 also find that the concentration indexes pretty much remain the same over the years.
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Table 1: Summary Statistics of Concentration Indexes in Greek Manufacturing CR78
CR84
CR88
HI78
HI84
HI88
Mean
0.451
0.435
0.423
0.101
0.096
0.089
Median
0.452
0.404
0.398
0.075
0.065
0.069
Maximum
1.000
0.965
0.972
0.530
0.508
0.540
Minimum
0.040
0.049
0.045
0.002
0.002
0.002
Standard deviation
0.242
0.230
0.229
0.101
0.098
0.088
Coefficient of variation
0.536
0.528
0.542
0.998
1.015
0.981
Note: Number of observations is 91.
In Table 2 below, the lower triangle presents the Pearson correlation coefficients of the variables at hand along with their statistical significance as this can be judged by their probability values shown in parenthesis, for the years 1984 and 1988. The upper triangle of Table 2 displays estimates of the Spearman’s rank correlation coefficients whose advantage over the Pearson’s correlation coefficients is that they account for possible nonlinear relations. The probabilities shown in the parentheses indicate statistically insignificant correlations between profit margin on sales and concentration ratios, with the exception of the Spearman’s rank correlation coefficient between the variables PMS88 and HI88+++ and between PMS88 and CR88 which are statistically marginally significant at the 5% and the 10% level of significance (p-values: 0.05 and 0.07, respectively). Table 2: Pearson’s and Spearman’s Rank Correlation Coefficients
CR84 CR88 HH84 HH88 PMS84 PMS88
CR84
CR88
HH84
HH88
PMS84
PMS88
-
0.932 (0.00)
0.978 (0.00) 0.915 (0.00)
0.900 (0.00) 0.978 (0.00) 0.894 (0.00)
0.108 (0.30) 0.180 (0.08) 0.105 (0.32) 0.207 (0.04)
0.147 (0.16) 0.190 (0.07) 0.144 (0.17) 0.204 (0.05) -0.004 (0.99)
0.928 (0.00) 0.886 (0.00) 0.796 (0.00) 0.052 (0.62) 0.142 (0.17)
0.792 (0.00) 0.871 (0.00) 0.132 (0.21) 0.163 (0.12)
0.801 (0.00) 0.037 (0.73) 0.145 (0.17)
0.188 (0.07) 0.112 (0.29)
-0,041 (0.70)
-
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The results of the year 1984 are definitely negative for the hypothesis that the number of participants in an industry affects the profitability, whereas the results for 1988 lend some support to the neoclassical hypothesis. In order to derive more conclusive results we tested two additional econometric specifications. In the first specification we formed a two-period panel provided that the industries are the same in the two census years (1984 and 1988). The regression results of PMS against CR and the HI applying the hetroscedasticity robust White’s estimating method with the t-statistics in parentheses are displayed below: PMS = 0.18567 + 0.02807 CR (20.08) (1.46)
R2=0.09%
PMS = 0.19359 + 0.04439 HI (31.06) (1.03)
R2=0.04%
Clearly, the statistical evidence does not lend support to the neoclassical hypothesis, the tstatistics in parenthesis are of low values and the R2 is near zero. In the second econometric specification we took the first difference of the variables at hand. More specifically, we run regressions of the differences of ΔPMS =PMS88-PMS84 against ΔCR=CR88-CR84 and ΔHI=HI88-HI84. The results of the regressions correcting for the possible presence of heteroscedasticity using White’s method with the t-statistics in parentheses are displayed below: ΔPMS = 0.0217 - 0.11809 ΔCR (2.16) (0.91)
R2=1.2 %
ΔPMS = 0.0211 - 0.3170 ΔHI (2.19) (1.64)
R2=0.04%
There is no doubt that the results of this specification are categorically against the hypothesis of a positive relationship between profitability measured by PMS and the degree of concentration measured either by CR or the HI. 4. Equalization of Profit Rates The empirical analysis so far has been static, since we examined to what extent profit margins on sales are positively correlated with the concentration indexes. The results overall show that there is no statistically significant relation. The next step is to test the
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long run tendential equalization of profit rates in Greek manufacturing industries. For this purpose and also due to the lack of data for 3-digit industries we restrict ourselves to 2-digit industries of the Greek manufacturing. The hypothesis of equalization of profit rates has been tested so far in terms of the average profitability of each industry against the economy’s average. 8 To our view, however, an industry’s average profitability is not necessarily the appropriate index of profitability that attracts the investment flows. The idea is that the average rate of profit estimates the profitability of all the firms that comprise the industry; firms that use advanced technology and have excellent location and firms whose technology is old and obsolete. However, the bulk of investment flows is not directed neither to the old type of capitals because of low profitability nor to the very new capitals because they are usually associated with too much risk and employ new, non tested and not easily reproducible technologies (because of patents, better location, etc). 9 Turning to manufacturing, the regulating conditions of each industry may not necessarily coincide with the average conditions but are rather determined by the type of capital where expansion or contraction of accumulation takes place. This concept is similar to what business people call the capital, which embodies “the best generally available method of production”, and is often called “the best-practice method of production”. This should not lead to the conclusion that all firms adopt this method of production immediately, since firms operate fixed capitals of different vintages and managers have different expectations about the direction of demand and profitability. Consequently, firms do not easily switch from one method of production to another. However, new capitals are expected to enter into that method of production, which can be easily duplicated and, furthermore, the expected rate of profit is attractive enough. The production method which is targeted by the new entrants is usually the most recent in the industry and not the older or the most profitable. The older methods of production, ceteris paribus, will have a rate of profit lower 8
See Muller (1990) for a number of studies about different countries and Lianos and Droucopoulos (1993) for the Greek economy. These studies usually find that the deviations of profit rates from the average persist, a result that leads to the idea of the presence of monopolistic elements. 9
Classical economists seem that they were aware of these limitations in the flows of capital. The best example is the case in agriculture, where the most fertile lands are already cultivated and they are not available to new entrants who can only enter into a worse type of land that secures the normal rate of profit and in this sense is the “best” available. Ricardo (1817, p. 73) analyzed the details of this concept in agriculture and mining and made some efforts for generalization.
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than the industry’s average, whereas the most profitable methods of production may not be easily reproducible or their reproduction might be associated with high risk, which new entrants usually do not wish to undertake. According to classicals, over a long period of time there is a tendency for the rate of profit to equalize among regulating capitals between industries. The profit rates of the regulating capitals across industries are those that are expected to be equalized. The rate of profit earned on regulating capital is, therefore, the measure of return on new investment and determines the rhythm of capital accumulation in industries. If two regulating capitals have different rates of profit, the investment will flow differentially and will not just stop flowing in the industry with the lower rate of profit because of uncertainty and differences in expectations. Consequently, at any given moment in time, the rates of profit between regulating capitals across industries are not equal and only in the long run there is a tendential equalization of the regulating rates of profit to an average. The problem with the concept of regulating capital is its quantification in real economies. In principle, one can distinguish these conditions by observing an industry over time and collecting data for a group of firms with certain characteristics that persist over time. Stigler’s “survivor technique” might be an example that would guide such a research for the identification of the regulating capital of an industry each year spanning a sufficiently long period of time. Clearly, such a procedure requires data which are hard to come by for a few industries and a few years, and such efforts would be extremely difficult to carry out for a long run analysis and many industries. One way out is Shaikh’s (1995) idea according to which although we may not know the regulating capital of each industry, however, we can estimate the profitability of these capitals through the concept of “incremental rate of return on capital” (henceforth IROR). 10 His rationale is as follows: investment flows are conditioned more by the short-run rate of return which is expressed in the concept of IROR than by the rate of profit over the lifetime of the investment. Hence, he distinguishes between current profits (Πt) that accrue to a firm as the sum of profits from the most recent investment (ρIt–1) and profits that accrue to a firm from all previous investments (Π*) which is equivalent to saying, the current profits in the absence of new investment. Consequently, we write: Πt = ρIt–1 + Π* 10
In fact, the concept of IROR is used in the literature of corporate finance to assess the profitability of firms and forms one of the “fundamentals” that investors must consider in their decisions.
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If we subtract profits of the past periods from both sides of the above equation we get: Πt – Πt–1= ρΙ t–1 + (Π* – Π t–1) or ΔΠ t = ρΙ t–1 + (Π* – Πt–1) The term in parenthesis is expected to be very small in comparison to the term ρΙt–1 and for practical purposes it can be ignored. The justification is the view that the shorter the evaluation horizon, the closer the current profit will be on carried-over vintages Π* to the last period's profit on the same capital goods (Πt–1). Moreover, since uncertainty and ignorance increase with the passage of time, it is reasonable to assume that the short-run (up to a year) is the relevant time horizon. After all, current profits are fraught with many ephemeral factors, and we know that abnormally high or low profits direct investment accordingly, which in turn gives rise to new uncertainty and thus profits or losses, and so forth. With these considerations in mind it is reasonable to assume that expectations about future returns to investment are nearsighted, that is, expectations depend on the short run rate of return. Consequently, the current rate of return on new investment will be: ρ t = ΔΠ t / I t–1 that is, the change in profits of each industry divided by the investment in the previous period. The above configuration provides a practical way to identify the profitability in the case that we do not have data on the best practice technique and the group of firms that utilize it over the years. Consequently, the motion of the IROR determines whether or not there is a tendential equalization of profit rates for the regulating capitals. Below, we propose a simple test according to which we estimate whether or not the deviation of industry’s IROR from the average differs from zero over the long run. The results are displayed in Table 3. In addition, in Figure 2, we plot the IROR deviations from the average in Greek manufacturing industries data over time. The data span the period between 1962 and 1993. 11 Clearly, the results in Table 3 reject the hypothesis of permanent deviations of industries’ IRORs from zero with only the exception of industry 24. An inspection of the data of industry 24 in Figure 2 revealed that the rejection of the null hypothesis is due mainly to some obvious outliers, that is to say, the exceptionally high IRORs in early 1960s, which when subtracted from the sample gave the expected result. 11
The time period was defined by the availability of data on investment which start in the year 1961, while after the year 1993 the industry classifications changed to such an extent that discourage any idea to expand the data base to more recent years.
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Table 3: Testing the Sample Mean of IROR Industry
t-value
Test Result
Industry
Food
1.23
Fail to reject H0 Rubber
0.26
Fail to reject H0
t-value Test Result
Beverages
1.67
Fail to reject H0 Chemicals
0.42
Fail to reject H0
Tobacco
-0.11
Fail to reject H0 Petroleum/Coal
0.18
Fail to reject H0
Textiles
-0.38
Fail to reject H0 Nonmetallic Minerals
-0.59
Fail to reject H0
Clothing/Footwear
2.23
Reject H0
-0.41
Fail to reject H0
Wood/Cork
1
Fail to reject H0 Metal Products
0.01
Fail to reject H0
Basic Metallic
Furniture
0.96
Fail to reject H0 Machinery
0.44
Fail to reject H0
Paper
0.71
Fail to reject H0 Electrical Supplies
1.51
Fail to reject H0
Printing/Publishing
1.39
Fail to reject H0 Transport. Equipment
0.97
Fail to reject H0
Leather
0.96
Fail to reject H0 Miscel. Manufacturing
-0.82
Fail to reject H0
Rubber
0.26
Fail to reject H0
Note: H0: sample mean = 0 and H1: sample mean ≠ 0. An alternative relatively new test that has not yet been tried in this type of studies and to our view is promising enough is based on the concordance statistics. Concordance statistics indicate whether or not two variables are together in the same phase or not. In a study such as ours, we are more interested in identifying whether or not the two variables (an industry’s IROR and the economy’s average IROR) coexist in the same state for a considerable period of time and not just to identify the strength of their possible correlation. This type of information is obtained by a test based on the non-parametric concordance statistic (Harding and Pagan, 1999), which is designed to determine the proportion of time that the two variables are in the same state. The estimated concordance statistic takes on values between 0 and 1. A positive relationship between the phase in two series implies a degree of concordance usually much higher than 0.5. 12 The idea is that the
12
The
Cij =T
concordance
statistic
(Cij)
is
estimated
from
the
{∑ (S ⋅S )+∑ (1−S )⋅(1−S )} , where T is the sample size, S and S
−1
T
t=1 it,
following
T
j,t
t=1
it,
j,t
it
jt
formula:
are binary variables
taking the value of one, when each of the IROR measures is greater than zero (the threshold level) and zero otherwise. The significance of the concordance statistic is conferred from the a coefficient whose value is obtained by running the following regression: Ε(( S − S ) ⋅ ( S − S ) − a ) = 0 . For further it
it
discussion on the concordance statistic see Hall and McDermott (2004).
jt
jt
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Figure 2. IROR Deviations from the Average in Greek Manufacturing Industries 0.6
3
4
0.4
2
2 2
1
0.2
0
0.0
1
-2
-0.2
0
-4 0
-1
-0.4
-6
-0.6
-1 65
70
75
80
85
90
-8 65
70
75
IROR20
80
85
90
-2 65
70
IROR21
6
80
85
90
65
70
75
IROR22
1.5
2
1.0
1
0.5
0
0.0
-1
-0.5
-2
4
75
80
85
90
IROR23
4 3 2
2
1 0
0
-1.0
-2 65
70
75
80
85
-1
-3
90
65
70
75
80
85
90
-2 65
70
75
IROR25
IROR24
3
80
85
90
65
6
75
80
85
90
85
90
IROR27
1.0
3
4
2
70
IROR26
2
0.5 2
1
1 0.0
0 0
0 -2 -0.5
-1
-1
-4
-2
-6 65
70
75
80
85
90
-1.0 65
70
75
IROR28
80
85
-2 65
90
70
75
IROR29
15
80
85
90
0.8
70
75
80
IROR31
3
6
0.6
10
65
IROR30
2
0.4
4 1
5
0.2 0.0
0
0
2
-0.2
-1
-0.4
-5
0 -2
-0.6 -10
-0.8 65
70
75
80
85
90
-3
-2 65
70
75
IROR32
80
85
90
65
70
IROR33
75
80
85
65
90
70
75
80
85
90
85
90
IROR35
IROR34
3 2
2
1
1
0
0
-1
-1
-2
-2
3
0
2 -2 1 -4 0
65
70
75
80
IROR36
85
90
-6
-1 -2 65
70
75
80
IROR37
85
90
-8 65
70
75
80
IROR38
85
90
65
70
75
80
IROR39
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expected value of concordance, in the case of two independent and identically distributed series, symmetrically around zero will be 0.5 and so one expects a somewhat higher value of the concordance statistic in order to pass judgment on whether or not the two variables at hand are synchronized and, therefore, are in the same state. The concordance statistics presented in Table 4 below indicate that most of the time the industries’ IRORs and the average IROR coexist in the same state, as this can be judged by the concordance statistics, which in all cases are higher than 0.5. Moreover, in most cases the concordance statistics are of value much higher than 0.5 indicating that the two variables spend much longer time in the same state. The concordance statistics are also associated with probability values which in our case indicate that our estimates are statistically significant more often than not. Table 4: The Concordance Statistic Industry
Concordance Significance Industry
Concordance Significance
Food
0.8064
***
Rubber
0.7419
***
Beverages
0.8387
***
Chemicals
0.8064
***
Tobacco
0.6774
*
Petroleum/Coal
0.6451
*
Textiles
0.8064
***
Nonmetallic Minerals
0.7419
***
Clothing/Footwear
0.7741
***
Basic Metallic
0.6451
***
Wood/Cork
0.7519
**
Metal Products
0.7096
***
Furniture
0.7519
-
Machinery
0.6774
-
Paper
0.6774
**
Electrical Supplies
0.8709
***
Printing/Publishing
0.7096
-
Transport. Equipment
0.5483
-
Leather
0.6451
**
Miscel. Manufacturing
0.6129
-
Note: *** indicates 5% significance level, ** 10%, *15%, and - No significance level.
5. Conclusions In this article we set out to show that the notion of competition as a dynamic process that has been developed by classical economists, Marx and also Austrian economists is much richer than it is usually thought. In our view, this alternative notion of competition concentrates a number of interesting characteristics that can become the foundation for the development of a more realistic theory of competition. Crucial to this approach is the notion of regulating capital whose general description can be found in Ricardo but its detailed development is in Marx. To our view what is even more essential about the notion
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of regulating capital are its important parallels with the established prudent business practices, whereby the “best practice capital or technique” and its profitability correspond to the regulating capital whose profitability is estimated by the IROR. The empirical analysis showed that there is no statistically sound positive relationship between the concentration ratio and profitability in Greek manufacturing industries, thereby casting doubt to the major proposition of the static notion of competition. Furthermore, the time series statistical analysis showed that the IROR of each of the twenty industries of the Greek manufacturing displayed gravitational behaviour around the economy’s average IROR, which is equivalent to saying that there is a tendential equalization of profit rates for the regulating capitals. A result which is consistent with the dynamic analysis of competition and encourages us to think that the analysis of competition as a process and the associated with it concept of regulating capital constitute a fertile ground for further theoretical and empirical research. References Antonakis, N. (1986) Concentration of Production in Greek Manufacturing: Theoretical and Empirical Analysis, Spoudai, (in Greek). Droucopoulos, V. (1979) Concentration of Capital and Production in our Times (in Greek). Athens: Odyseas. Droucopoulos, V. (1991) The Degree of Concentration in Greek Manufacturing (in Greek). Issues in Political Economy 8, 99-121. Droucopoulos, V. and Lianos, T. (1993) The Persistence of Profits in the Greek Manufacturing, 1963-1988. International Review of Applied Economics, 7, 163-176. Droucopoulos, V. and Papadogonas, Th. (2000) Concentration Indices: Back to the Drawing Board, Ekonomia 4, 55-72. Hall, V. and McDermott, J. (2004) Regional Business Cycles in New Zealand: Do they Exist? What Might Drive Them? ERSA conference papers, European Regional Science Association.
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Harding, D. and Pagan, A. (1999) Knowing the Cycle, mimeo, Melbourne: University of Melbourne. Kaskarelis, I. and Tsoulfidis, L. (1999) Inflation, Demand, Imports Competition and Markups in Greek Manufacturing Industries, Economia Internazionale, pp. 151-171. Kirzner, I. (1987) Competition: Austrian conceptions, in Eatwell, J., Milgate, M. and Newman, P. (eds.) The New Palgrave: A Dictionary of Economics. London: Macmillan. Mill, J.S. (1848) Principles of Political Economy. Fairfield New Jersey: Augustus M. Kelley, 1976. Mueller, D. ed. (1990) The Dynamics of Company Profits, Cambridge: Cambridge University Press. Pakos, Th. (1982) Industrialisation, Structural Change and Policy: The Case of Greece 1958-77. Ph.D. Thesis, The Victoria University of Manchester. Ricardo, D. (1951, [1821]) Principles of Political Economy and Taxation. Cambridge: Cambridge University Press. Schumpeter, J. (1942) Capitalism Socialism and Democracy. New York: Harper and Row Publishers. Shaikh, A. (1995) The Stock Market and the Corporate Sector: A Profit Based Approach. Working Paper, No 146. New York: Jerome Levy Institute. Smith, A. (1776) The Wealth of Nations, New York: The Modern Library, 1976. Stigler, G. (1957) Perfect Competition Historically Contemplated, Journal of Political Economy 65, 1-16. Tsaliki, P. and Tsoulfidis, L. (1998) Alternative Theories of Competition: Evidence from Greek Manufacturing, International Review of Applied Economics 12, 187-204.
