the effect of reductions in concentration on income distribution

The Effect of Reductions in Concentration on Income DistributionAuthor(s): Irene PowellSource: The Review of Economics and Statistics, Vol. 69, No. 1 (Feb., 1987), pp. 75-82Published by: The MIT PressStable URL: http://www.jstor.org/stable/1937903 .

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THE EFFECT OF REDUCTIONS IN CONCENTRATION ON INCOME DISTRIBUTION

Irene Powell*

Abstract-The simulation model of this study indicates that a decline in above-normal profits associated with concentration will cause a redistribution of income from the highest of six income classes to low and middle income classes. The magnitude of gains and losses ranges from 0.2% to 0.9% of income for reductions in four-firm concentration ratios to 50% in all manufacturing industries. The methodology uses consumer expenditure data and input-output information to estimate the impact on payments made to capital and uses income tax data on income sources by income class to estimate the impact on income received from capital ownership. Estimates of the change in profits resulting from a change in concentration are based on a published concentration-profits regression.

I. Introduction

M UCH of the research on performance effects of monopoly power has focused on

efficiency effects and has found that the misallo- cation of resources resulting from market power is not large (Harberger (1954), Scherer (1980)). Eco- nomic efficiency, however, is not the sole criterion by which we need to evaluate the social impact of industrial concentration. Economists, and to an even greater extent public policy makers, are also concerned with equity. Therefore, an important issue involved in determining the possible impact of monopoly power on social welfare is its effect upon the relative distribution of income. Only Comanor and Smiley (1975), Lankford and Stewart (1980) and McElroy, Siegfried and Sweeney (1982), have considered the distributional impact of monopoly power.

It is the purpose of this study to determine whether there is any validity to the belief that antitrust action can substantially alter the distribution of income. This study simulates the impact of a reduction of concentration in the manufacturing sector on the distribution of income among various income classes. Economists have posited and estimated relationships between concentration and a number of other variables which can be

expected to influence above-normal profits. This study estimates the distributional impact of a reduction in concentration using the most conventional of these effects; the direct effect of a change in concentration on above-normal profits, holding other variables constant.' Even this direct effect of concentration on profits is controversial, particu- larly because some would argue that profits which reflect better products or better management and/or lower costs are wrongly attributed to market power. This study, however, accepts the effect of concentration on profits as valid (and as estimated in past studies), and determines the distributional effect of a decrease in concentration using published estimates of its magnitude.

The simulation is carried out for the year 1963, a year in which the effect of concentration on profits should have been relatively strong. Price changes by firms in concentrated industries appear to be less rapid than price changes by firms in unconcentrated industries during periods of unanticipated inflation. Even the conventional effects of concentration are weak during these periods. For this reason, the distributional impact of reducing concentration estimated for 1963, a period of stable inflation, represents an upper-bound on the effects of a reduction in concentration.

II. Methodology

Any reduction in excess profits associated with concentration would affect the distribution of income by reducing the profits that each income class pays out in consumer expe-nditures (the expenditure side) and by reducing the profits each class receives in income (the sources-of-income side). For any particular income class, the net distributional effect due to a change in profits would equal the change in expenditures minus the decrease in profit income received. Let D be a J x 1 vector (where J is the number of income classes), representing the net distributional effect

Copyright ?D 1987 [ 75 ]

Received for publication December 5, 1985. Revision accepted for publication May 21, 1986.

* Mount Holyoke College. I would like to thank Leonard Weiss, Mark Montgomery,

John Siegfried, Walter Nicholson, Martin David, William G. Shepherd, Richard Rodgers, and two anonymous referees for helpful comments.

1 A more complete analysis is undertaken in Powell (1985) which also allows that a change in concentration will affect above-normal wages. These results are summarized in footnote 9.



76 THE REVIEW OF ECONOMICS AND STATISTICS

due to a change in profits, with element dj being the net change in purchasing power as a proportion of income for the j th income class. Let E be a J x 1 vector representing the change in expenditures as a proportion of income for each income class; and let S be a J x 1 vector giving the change in income received from capital for each income class as a proportion of income. Then D = E-S.

A. Estimating the Change in Profits Due to a Decrease in Concentration

Predicted excess profits associated with concentration are calculated using one of the many concentration-profits relationships already estimated for manufacturing industries for 1963. The regression selected, estimated by Weiss (1974), was chosen because Weiss' specification is typical of those in the concentration-profits literature and because it used data for 1963. The measure of profits used is the price-cost margin (PCM), or the margin of price over average materials and labor costs, as a percentage of price. The portion of this markup which can be attributed to concentration is the measure of the change in excess profits used in all estimation reported in this study. The variables and notation used are described in the appendix, which is available from the author on request.

The results of the Weiss regression are as fol- lows:

PCMi = O.0005(CR4i) + 0.000008(CR4i * CDi)

M

+ E xm gm m=1

where CR4 is the 4-firm concentration ratio, CD is consumer demand as a proportion of total demand, and the M other independent variables and coefficients are as reported in the appendix.

Letting RCR4 be the level to which the four-firm concentration ratio will be reduced by antitrust action, we can predict the change in the price-cost margin for industry i as

ri=APCM, = (0.0005 + 0.000008 * CDJ) X(CR4i - RCR4),

if CR4i > RCR4,

= 0 otherwise

(no antitrust action if CR4 < RCR4).2

This study simulates a reduction to three alternative four-firm concentration ratios; 0%, 40% and 50%. A 0% cutoff is not a realistic goal for antitrust policy. It is of interest here, however, because the specification of the Weiss regression implies that the competitive CR4 is 0%. Also, this extreme reduction will provide an upper bound estimate of the potential impact of antitrust. However, because it is unlikely that concentration would be reduced to 0%, for policy purposes it is helpful to look at a reduction of concentration to higher levels as well.3

B. The Expenditure Side

The next step is to use the estimates of excess profits found in section A to simulate E, the vector of changes in the distribution of payments by income class for the J income classes. The methodology is that used by McElroy, Siegfried and Sweeney (1982) in estimating the distributional effect of changes in product prices. Let A be the N x N Total Requirements matrix for the N industries in the U.S. economy where aik shows the number of dollar's worth of good i required to produce one dollar's worth of good k. Let C be the N x J matrix of consumer expenditures on each of the N goods by each of the J income classes. (Thus, c,j is the proportion of the jth income class's income spent on good i.)4

2 The concentration ratios used to estimate R were taken from the Census of Manufactures for 1963 for four-digit SIC industries.

3A concentration-profits regression which estimated the change in profits from a discontinuous regression using a critical four-firm concentration ratio of 50% (Rhoades and Cleaver (1973)) was also used in Powell (1985). These results are available from the author on request.

4 The data for the matrix C are taken from the Survey of Consumer Expenditures for 1960-1961, found for detailed product classifications in Expenditure Patterns of the American Family (Linden (1965)). This survey groups consumers into various income classes which were chosen to correspond to classifications available for other data used for this study. The approximately 3000 detailed products were reclassified to correspond to the Input-Output industry classifications. Also, the 399 4-digit SIC manufacturing industries were aggregated (using a value-of-shipments weighted average) into the 284 Input- Output manufacturing industries.



INCOME DISTRIBUTION 77

McElroy, Siegfried and Sweeney show that

el: e1 e2 J r, ... rN

eJ lirN

all a .2 . alNI Cc a2 *

XI

I . . I I . . I

aN1 aN2 a NN :CN1 .. * *

"A" "c"

where R is the vector of the percentage changes in rents caused by reducing concentration in each of the N industries, as estimated in section A above.

Each element of E is valued as the average change in payments for each income class as a proportion of average household income for that class.

The methodology described above implicitly re- quires the following assumptions:

1. Fixed coefficients technology and constant returns to scale in production.

2. Homogeneous products within each industry.

3. Fully employed and perfectly-elastically sup- plied factors.

4. The distribution of consumption expenditures for each income class across the N goods is invariant with respect to the change in rents.

C. The Sources of Income Side

The next step is to estimate the vector of changes in income received by the various income classes, S. Because data on stock ownership by industry by income class are unavailable, it is assumed that the percentage of each individual industry's stock held by an income class is equal to the percentage of all stock held by that class. This assumption may introduce some errors if, for example, the rich own proportionately more stock in concentrated industries than other classes. However, Blume, Crockett and Friend (1974) observed that

industry stock holdings were relatively uniform across income groups.

The estimate of the decrease in income received from capital for each income class j resulting from a decrease in concentration, sj, is calculated as

sj = (RET)/jRETJ)(TOTAL R)/yj

where

RETj total returns to stock received by the jh income class;

y- total income received by the jth income class (found in Current Population Reports);

TOTAL R the total reduction in profit or excess returns to capital = X(ri x value of shipments in industry i), where ri was estimated in section A above.

Total returns for class j, RET) must equal the sum of dividends plus realized and unrealized capital gains.

RETJ = dvj + rgj + ugj;

where ugj is unrealized gains for the j th income class, dvj is dividends, and rgj is realized capital gains.

To discover the proportion of total returns received by the j th class we first assume that the ratio of realized capital gains to total capital gains is constant across income classes. We call this ratio q. That is,

q = rgl/(rgj + ugj)

= rg/(rg + ug) for allj.5

Given this assumption, it must be true that

RETj = dvj + rgj(1/q).

There have been various estimates made of q, the proportion of total accrued gains that are realized (McClung (1966), Bailey (1968), and David (1968)). These estimates range from approximately 0.20 to 0.40. Therefore, the current study uses an estimate for q of 0.30.

s It is likely that higher income households will choose to earn relatively more of their stock earnings in the form of unrealized capital gains for tax avoidance purposes. In this case, making this assumption will tend to understate the degree of inequality in redistribution.




Data on income earned from stock ownership from dividends and realized capital gains (estimates of dvj and rgj) were selected from data compiled by the Internal Revenue Service in Sta- tistics of Income: Individual Income Tax Returns.6 There are certain problems with the IRS data, attributable to underreporting of income, the tax- exempt status of some forms of income and the tendency of wealthy families to distribute income among separately-filing family members. Work by Blume, Crockett, and Friend (1974) attempted to correct for these problems. Their results indicate that the higher income groups own a greater proportion of stock value than the IRS data indicate and thus suggest that using IRS data will cause the estimate of redistribution made here to be slightly biased downward.

A complication in estimating S arises from the fact that the estimate of the total reduction in profits is derived from the price-cost margin measured before corporate income tax is deducted. While this problem is not relevant to estimating the distributional impact on the expenditure side, it does present a problem in estimating the impact on what each income class receives from ownership of capital. Therefore, to find the distributional effect of decreasing capital income the above measurement is multiplied by the quantity: (one minus the average corporate tax rate in manufacturing). The average corporate tax rate used, 0.3940, was calculated by Siegfried (1974) as the effective average corporate tax rate for mining and manufacturing for 1963.7

III. Simulation Results

Results of the simulated distributional effect of decreasing profits associated with concentration are given in table 1. The results for the change in expenditures, E, are found in the first three columns. The greatest reduction in excess payments as a percentage of household income is enjoyed by the $3000-$4999 and $5000-$7499 income groups. For example, when concentration is reduced to CR4 = 40%, the reduction of excess payments to capital is approximately 0.71%-0.75% of income for those two groups, compared to 0.35% of income for the over $15,000 class. The pattem is similar when concentration ratios are lowered to zero and 50%. In general, while the expenditure reductions reported in table 1 are modest even for the extreme case of lowering concentration to zero, they are not insignificant and are felt most heavily by the five lowest income classes.

Why do the five lowest income classes gain the most in terms of lower excess payments to capital while the rich gain the least? Clearly, one contrib- uting factor is that expenditures form a lower proportion of the incomes of wealthier households than for lower income households. The burden of excess payments as a percentage of income should, therefore, fall most heavily on those with lower incomes. However, it is also possible that wealthier families purchase relatively more from less concentrated industries.

To gain some insight into this issue, the distribution of monopoly payments as a proportion of average total expenditures for each income class was calculated. The lowest income class pays the lowest percentage of total expenditures as monopoly profits (for example, about 0.35% of expenditures for an RCR4 of 50%). The highest percentage is paid by the middle income classes (the $3000-$4999 class pays O.54% for RCR4 =

50%) while the richest group pays only slightly less (0.5% for RCR4 = 50%). We conclude, then, that the highest income class enjoys the smallest reduction in payments primarily because those payments are low as a proportion of its income. However, the poor do seem to make more of their purchases from unconcentrated industries.

The pattern of expenditures and monopoly payments to industries is made clearer by looking at the matrix of monopoly payments by each income class in each two-digit industry, presented in table

6 This estimate uses data from individual tax returns to estimate the proportion of returns earned by each income class. However, part of stock value is owned by institutions such as pension funds. Thus, this estimate assumes that pension ownership is distributed in the same way as individual stock ownership. The author made an alternative estimate of si which used information on pension income by income class to distribute that portion of the change in returns accruing to institutions, about 14% of stock value. These estimates are available from the author on request and are discussed in footnote 8.

7 Using the average tax rate might produce some error in estimation. For instance, the loss of income may be overstated if those industries with significantly higher than average tax rates also tend systematically to be high profits industries (or vice versa). However, there does not seem to be any systematic trend based on profits in high or low tax industries when Siegfried's (1974) list of high and low tax rate industries is matched to a list of industry profits.




TABLE 1.-THE DISTRIBUTIONAL EFFECT OF A REDUCTION IN INDUSTRY CONCENTRATION BY INCOME CLASS (as a proportion of household income)

Expenditure Side (E) Sources of Income Side (S) Overall Distributional Effect Decrease in Payments Decrease in Excess Income (D = E - S)

to Capital Received from Capital Net Change in Purchasing Power

RCR4 = 0 RCR4 = 40 RCR4 = 50 RCR4 = 0 RCR4 = 40 RCR4 = 50 RCR4 = 0 RCR4 = 40 RCR4 = 50

Under $3,000 .03515 .006861 .004280 .003505 .0008361 .0005276 .031646 .006025 .003752 3,000-4,999 .03227 .007462 .004884 .002937 .0007007 .0004422 .029335 .006761 .004442 5,000-7,499 .02965 .007132 .004724 .003263 .0007784 .0004912 .026386 .006354 .004233 7,500-9,999 .02612 .006372 .004239 .004832 .0011526 .0007274 .021286 .005219 .003512 10,000-14,999 .02315 .005710 .003811 .012757 .0030431 .0019204 .010395 .002667 .001891 15,000 & over .01440 .003534 .002356 .075706 .0180594 .0113968 -.061306 -.014525 -.0090408

2. Three-fifths of the industries in which monopoly payments are highest for the middle income group are industries with high monopoly profits (0.5% of value of shipments or greater). The industries in which monopoly profits are highest for the lowest income group are the food (#20), paper (#26), fabricated metal (#34) and tobacco (#21) industries. Each of these industries, except tobacco, is a low profits industry (0.4% or less of value of shipments).

The "income side" of the effect of decreasing concentration (S) is presented in columns 4-6 of table 1. These estimates indicate that the highest income class would lose significantly more from a decrease in concentration than other groups. For example, the estimated loss of capital income for the $15,000 and over group with a cutoff of 40% is 1.8% of income as compared to 0.3% for the $10,000-14,999 group. This result holds for all three reductions in concentration ratios. With a 0% cutoff the highest estimated loss for the richest income class is 7.57%. The loss of capital income for the four lowest income classes is very low, ranging from 0.044% of income (for the $3000-$4999 income group, RCR4 = 50) to 1.3% of income (for the $10,000-14,999 income class, RCR4 = 0).8

The last three columns of table 1 present the overall change in the income distribution, found by subtracting the income side, S, from the expenditure side, E. These estimates indicate that

the decrease in concenration would increase real income (purchasing power) for the lowest five income classes. The reverse is true for the highest income group, implying a redistribution of income from the richest class to the other classes. The gain in income is the greatest for the lowest three income groups.

The important point made in table 1, however, is that the magnitude of the redistribution is relatively low for reductions in concentration to a CR4 of 40% or 50%. For example, for an RCR4 of 50%, the gain in income for the five lowest income groups ranges from 0.19% to 0.44% of income. The decline in income for the highest income class is 0.90% of income. It is not surprising that a much higher potential redistribution occurs with a decline in concentration to zero. Here the decline as a percentage of income is 6.13% for the highest income class; the greatest gain in income is 3.2% for the lowest income class.9

IV. Conclusions

The simulation model presented in this study found that a reduction in above-normal profits associated with concentration would cause a redistribution of income from the highest income class

8 When pension income data are used to distribute the change in income received from stock ownership of institutions, the richest group is not hurt quite so much (losing 1.05% of income with an RCR4 of 50%, for instance) and the lowest three groups are hurt a little more (the bottom group loses 0.11% of income).

I The distributional effect of a decrease in excess returns to labor resulting from a decrease in concentration was estimated using a concentration-wage regression estimated by Haworth and Reuther (1978) to predict the change in labor costs and Current Population Survey data for sources side estimation. The results, summarized briefly, indicate that such a decrease in excess labor costs would redistribute income from low and middle income groups to the richest group, with the greatest loss for the middle groups. The magnitude of the redistribution is very low, from 0.01 to 0.07% of income for a decrease in concentration to 40%.



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to the low and middle income classes. The highest income class would suffer a loss of income if concentration were lowered. The lowest five income groups would enjoy an increase in purchasing power as a result of the decease in concentration. The greatest gain in purchasing power would be enjoyed by households in the $3000-$4999 income class. The results of this study indicate that while there may be a lessening of income inequality from government action which would decrease concentration; the magnitude of the effect is small for the more realistic reductions in concentration to 40% or 50%.

Before considering the implications of the above simulation for the conduct of U.S. antitrust policy, it is important to bear in mind some caveats about the limitations of this study. First, factor substitu- tions and changes in the distribution of consumption expenditures, assumed away in the current study, would undoubtedly occur over time as pro- ducers and consumers had time to adjust to the policy actions. It is difficult to conclude whether making partial equilibrium calculations will bias the current results up or down. Whalley (1975) and Friedland (1978) compare general equilibrium estimates to partial equilibrium estimates of welfare changes as a result of a tax change (Whalley), and a change in monopoly pricing (Friedland), and find that general equilibrium calculations usually yield smaller estimates of the welfare changes. It is not clear, however, whether their results imply that general equilibrium estimates of the income distribution among income classes would be smaller in magnitude than partial equilibrium as well.

Second, as stated above, we expect these results to represent a high estimate of the distributional effect of changing concentration. It is likely that it would be lower, and possibly undetectable, for years of severe, unanticipated inflation such as 1973-1974 and 1979-1980.

Third, if the profits attributed to monopoly power are returns to greater efficiency, as some economists assert, then the decrease in concentration simulated here could eliminate efficient firms and instead lead to higher effective prices and costs. Then, the distributional effect measured here would overstate the effect on lowered prices and lower consumer expenditures.

The magnitude of the redistribution simulated is low enough that these redistributive effects,

TABLE 3.-CHANGE IN PAYMENTS TO CAPITAL (E) RESULTING FROM A DECREASE IN CONCENTRATION TO 40%

FOR SELECTED 3- AND 4-DIGIT INDUSTRIES AND INCOME CLASSES

(as a proportion of household expenditures)

Under $5,000- $15,000 SIC code Industry $3,000 7,499 and over

2043 Cereal preparations .0198 .0132 .0065 205 Bakery products .0109 .0091 .0053 206 Sugar .0103 .0070 .0043

2095 Coffee .0163 .0093 .0053 2111 Cigarettes .0736 .0710 .0348

284 Soap .0293 .0267 .0179 3632 Refrigerators .0134 .0146 .0083 3641 Electric lamps .0066 .0073 .0093 3711 Motor vehicles .0139 .0371 .0382 3861 Photographic .0039 .0069 .0085

equipment

when weighed against the possible costs of antitrust policy to lower concentration, might not justify an increase in such antitrust action. Admin- istrative and enforcement costs of the antitrust action needed to lower concentration ratios to 50% in all manufacturing industries would be enormous.

However, one need not interpret the estimates given here to suggest that antitrust action should be less intense. First, this study looked at excess profits only in manufacturing. Second, just as with deadweight loss reduction, the greatest benefit originates with a relatively small number of industries. For instance, the results in table 3 suggest that deconcentration efforts should be focused on such high profit industries as cereals, bakery products, sugar, coffee, cigarettes, and soaps, where the decrease in payments would be greatest for the low income groups and least for the high income groups.

REFERENCES

Bailey, Martin J., "Capital Gains and Income Taxation," in A. C. Harberger and M. J. Bailey (eds.), Taxation of Income from Capital (Washington, D.C.: Brookings In- stitution, 1968).

Blume, Marshall E., Jean Crockett, and Irwin Friend, "Stock- ownership in the United States: Characteristics and Trends," Survey of Current Business 54 (Nov. 1974), 16-40.

Comanor, William S., and Robert H. Smiley, "Monopoly and the Distribution of Wealth," Quarterly Journal of Eco- nomics 89 (2) (May 1975), 177-194.

David, Martin, Alternative Approaches to Capital Gains Taxa- tion (Washington, D.C.: The Brookings Institution, 1968).




Friedland, Thomas S., "The Estimation of Welfare Gains from Demonopolization," Southern Economic Journal 45 (July 1978), 116-123.

Harberger, Arnold, " Monopoly and Resource Allocation," American Economic Review 44 (May 1954), 77-87.

Haworth, Charles T., and Carol J. Reuther, " Industrial Concentration and Wage Determination," this REVIEW

60 (Feb. 1978), 85-95. Lankford, Ralph H., and John F. Stewart, "A General

Equilibrium Analysis of Monetary Power and the Distribution of Income," in John J. Siegfried (ed.), The Economics of Firm Size, Market Structure and Social Performance (Washington, D.C.: Federal Trade Commission, July 1980).

Linden, F. (ed.), Expenditure Patterns of the American Family, National Industrial Conference Board, 1965.

McClung, Nelson, "The Distribution of Capital Gain on Cor- porate Shares by Holding Time," this REVIEW 48 (Feb. 1966), 40-50.

McElroy, Katherine M., John Siegfried, and George Sweeney,

"The Incidence of Price Changes in the Economy," this REVIEW 64 (May 1982), 191-203.

Powell, Irene, The Effect of Reducing Concentration in U.S. Manufacturing on the Distribution of Income: A Simula- tion, unpublished doctoral dissertation, University of Wisconsin-Madison 1985.

Rhoades, Stephen, and Joe M. Cleaver, "The Nature of the Concentration-Price/Cost Margin Relationship for 352 Manufacturing Industries: 1967," Southern Economic Journal 40 (July 1973), 90-102.

Scherer, F. M., Industrial Market Structure and Economics Performance (Chicago: Rand McNally, 1980).

Siegfried, John, "Effective Average U.S. Corporation Income Tax Rates," National Tax Journal 27 (June 1974).

Weiss, Leonard, "The Concentration-Profits Relationship and Antitrust," in H. Goldschmid, H. M. Mann and J. F. Weston (eds.), Industrial Concentration: The New Learn- ing (Boston: Little, Brown and Co., 1974).

Whalley, John, "How Reliable Is Partial Equilibrium Anal- ysis?" this REVIEW 57 (May 1975), 299-310.



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