do firms differ much? - CiteSeerX

Do Firms Differ Much? Author(s): Dean Amel and Luke Froeb Source: The Journal of Industrial Economics, Vol. 39, No. 3 (Mar., 1991), pp. 323-331 Published by: Wiley Stable URL: http://www.jstor.org/stable/2098523 Accessed: 27-06-2016 04:21 UTC Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://about.jstor.org/terms

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].

Wiley is collaborating with JSTOR to digitize, preserve and extend access to The Journal of Industrial Economics

This content downloaded from 128.42.202.150 on Mon, 27 Jun 2016 04:21:29 UTC All use subject to http://about.jstor.org/terms

THE JOURNAL OF INDUSTRIAL ECONOMICS 0022-1821 $2.00 Volume

XXXIX

March

1991

No.

3

DO FIRMS DIFFER MUCH?* DEAN AMEL AND LUKE FROEB With firm profitability data for a cross-section of geographic markets, it is possible to determine the relative importance of firm and market effects on profitability. Analysis of variance from a panel of multibank holding companies in Texas suggests that firm effects are more important than market effects in determining profitability, and that the magnitudes of the effects vary over time.

I. INTRODUCTION

IN A 1985 article, Schmalensee takes a new approach to analysis of the structure-conduct-performance paradigm. Schmalensee chooses a purely descriptive approach to distinguish among the "classical" tradition of Bain

[1956], which takes markets as the basic unit of analysis, with a particular focus on market concentration; the "revisionist" views of Demsetz [19731 and Peltzman [1977], who view the observed relation between profitability and

concentration as reflecting underlying inter-firm profitability differences; and the "managerial" view, that profitability is determined by firm-wide management practices, but not necessarily by differences in market share. This descriptive approach has two advantages over a structural analysis.

A descriptive analysis avoids imposition of the troublesome maintained hypotheses inherent in structural models. Further, as Scott and Pascoe [1986] point out, the explanatory power of structural models is generally

only a small fraction of that of descriptive models.

Schmalensee uses FTC Line of Business data, where firm profitability data

are broken down by line of business, to calculate the relative importance of firm and market effects on profitability. While a descriptive approach cannot

shed any light on structural parameters, it can yield useful insights into the structure-conduct-performance controversy. In particular, if firm effects are economically unimportant (as Schmalensee concludes), then managerial

effects are not a substantive cause of differences in profitability. However, as pointed out by Shepherd [1972] and Harris [1988], the presence of significant firm effects does not contradict the classical hypothesis. The purpose of this paper is to investigate the robustness of Schmalensee's

results with respect to a different data set, where firm profitability is broken

* The authors thank Steve Bumbaugh for excellent research assistance. Tim Brennan, Timothy Hannan, Nellie Liang, Stephen Rhoades and anonymous referees made useful comments on earlier drafts. The views of the authors do not necessarily reflect the views of their respective institutions.

323


324 DEAN AMEL AND LUKE FROEB

down by geographic market rather than by line of business. Such a re-

examination is appropriate because Schmalensee's results contradict findings of earlier studies and results derived by Scott and Pascoe from an expanded sample of FTC lines of business. The data set is a panel of multimarket banking firms in Texas over the period 1982-87 for which market-specific

profit data are available. The use of geographic markets within a well-defined industry may yield better approximations to what most economists think of as markets than use of a cross-section of Standard Industrial Classification

(SIC) industries.' We find that firm effects are more important than market effects in

explaining variation in profitability. The explanatory power of the firm effects varies over the sample period as economic conditions in the industry change.

In addition, market share and market concentration have little, if any, explanatory power. The results provide support for the hypothesis that firm-wide managerial practices are important determinants of profitability, but do not provide evidence supporting the hypotheses that market share or market concentration are important determinants of performance.

II. BANKING FIRMS AND BANKING MARKETS

Banking markets provide more precise, consistent and economically meaningful measures of economic integration than are available for the industrial sector. The drawbacks of defining economic markets by SIC codes

are well known (e.g. Werden [1988]). Studies using data aggregated by SIC code are vulnerable to criticism that the aggregation is either masking

important relationships or creating spurious ones. In addition, FTC data are available for only four years and are now somewhat dated. Benston [1985] recommends a course for future research: "detailed company and industry

studies, which require knowledge of the specifics and dynamics of events and institutions more than of econometric techniques are required" (p. 65). We follow his recommendation with a study of the Texas banking industry. By

using cross-sectional data on local geographic markets within one industry, and by covering six years during which the industry faced rapidly changing economic conditions, this study attempts to avoid some of the shortcomings associated with the use of SIC data.

Data from a number of consumer and business surveys suggest that the markets for at least some banking services are local in nature. While large

businesses typically have access to regional or national markets for credit, smaller businesses are generally limited to local credit markets. In addition, the markets for many consumer banking products are restricted to local areas

l Studies using banking data generally find a significant positive relationship between profitability and market concentration similar to that found in manufacturing industries. See Gilbert [1984] and Rhoades [1982] for surveys.


DO

FIRMS

DIFFER

MUCH?

325

(King [1982], Whitehead [1982]). Federal bank regulators and the Department of Justice, in antitrust analyses of bank mergers and acquisitions, define banking markets as local geographic areas. Following common practice in cross-sectional studies, we estimate urban Texas geographic banking markets by Metropolitan Statistical Areas.2

The courts have traditionally defined the product market for banking to be

the cluster of banking services.3 Such a definition limits the firms in the market to commercial banks. However, deregulatory legislation in 1980 and 1982 and recent technological developments have caused many to question

this traditional product market definition. In particular, thrift institutions, which now have virtually the same legal powers as banks, are often thought to compete in the same markets as banks, and antitrust authorities typically give thrifts some weight in analyses of banking mergers. Nevertheless, the activities of banks and thrifts still differ substantially. Most thrifts have not become aggressive suppliers of products, such as commercial loans, that they were prohibited from supplying before 1980, and, compared to banks, thrift balance sheets show a larger focus on mortgages and real estate investments. Consequently, the sample is restricted to commercial banks. Banks are required to report their profits annually to bank regulators.

Some states, including Texas, have restrictive branching laws that prohibit

multimarket branching, so that each bank is limited to operating in a single market.4 However, to circumvent branching restrictions, banking

organizations form multibank holding companies (MBHCs) that own all of the stock of a number of banks.

While each bank within a MBHC is legally a separate firm, we consider the MBHC to be the firm in this paper. One would expect all banks in an MBHC

to be run so as to maximize their joint profits because of their common

ownership. Cornyn, et al. [1986] and Flannery [1986] review empirical evidence suggesting that market participants view the MBHC, not the individual banks, as the firm. Bank regulators and financial analysts treat MBHCs as firms for most purposes. In this paper, however, we utilize data on individual bank subsidiaries of MBHCs so that we can observe marketspecific performance of MBHCs.

The yearly samples were developed to yield data for bank subsidiaries of all MBHCs operating in two or more of the 27 urban banking markets in

2 Primary Metropolitan Statistical Areas are used within Consolidated Metropolitan Statistical Areas. Thus, Dallas and Fort Worth are treated as separate banking markets, as are Houston, Galveston and Brazoria.

3 US v. Philadelphia National Bank, 374 US 321 [1963]; US v. Connecticut National Bank, 418 US 656 [1974].

'The Texas state constitution prohibited branching until 1987, when a constitutional amendment took effect allowing branching within a county. Since local markets are defined as Metropolitan Statistical Areas (MSAs), and MSAs are composed of counties, branching between markets is still prohibited.


326 DEAN AMEL AND LUKE FROEB TABLE I DATA DESCRIPTION

MEANS, (STANDARD DEVIATIONS), [MINIMAL], AND {MAXIMA}

Variable 1982 1983 1984 1985 1986 1987 Profit rate 1.15 0.54 0.46 0.28 -0.70 -1.40

(0.44) (0.32) (0.43) (2.03) (2.49) (2.96) [-0.49] [-0.80] [-2.74] [-15.20] [-21.31] [-16.95]

{2.32} {1.95} {1.09} {2.12} {1.63} {1.40}

Concentration 1549 1500 1384 1377 1371 1493 (738) (628) (554) (553) (593) (586)

[831] [814] [788] [767] [734] [734] {5270} {3880} {3632} {3634} {3604} {3651}

Market share 11.6 11.1 10.9 10.6 10.4 10.7 (9.9) (9.9) (10.3) (10.1) (9.9) (10.6)

[0.1] [0.0] [0.0] [0.0] [0.0] [0.0]

{52.4} {51.9} {50.6} {47.6} {47.8} {45.7} No. of obs. 107 133 144 153 157 156 No. offirms 18 23 26 30 31 33 No. of markets 26 26 26 27 27 27

Texas.5 If an MBHC controls two or more bank subsidiaries within the same market, the deposit and profit data for those banks are consolidated into one observation for that market by summing bank balance sheets. Because of this

within-market summing, in each year the number of observations on an MBHC is equal to the number of markets in which its subsidiary banks operate. The number of MBHCs in the sample rises from 18 in 1982 to 33 in

1987 while the number of observations on MBHC bank subsidiaries rises from 107 to 156. The increases are due primarily to mergers and acquisitions

by one-market banking organizations that increase the number of multimarket MBHCs and to acquisitions of banks by existing MBHCs. The data are summarized in Table I for each of the six years in the sample.6 Profits are measured by the ratio of net income after taxes to assets.7 Use of the ratio of net income after taxes and securities gains and losses to assets as

an alternative profit measure yielded very similar results, which are not reported. Market concentration, as measured by the Herfindahl Index, and 5:Texarkana banks are excluded from the sample because part of the Texarkana market is in Arkansas. Texarkana banks face different branching restrictions and competitive conditions than banks in other Texas metropolitan areas.

6 The number of markets covered rises from 26 over 1982-84 to 27 over 1985-87 because the Laredo market contains no banks owned by multimarket MBHCs prior to 1985. 7Intra-MBHC transfers could bias the profitability figures for individual banks within a MBHC. However, this bias is controlled by regulations that require all such transfers to be at fair market values. Transfers among banks designed to aid failing affiliates are supposed to come

through bank dividends paid to the parent holding company, then transferred to the failing bank subsidiary. Such dividends and transfers do not affect the profitability data of individual banks. Similarly, purchase premia paid for acquisitions of banks would come from dividends paid to the holding company parent and would not affect the profitability of banking subsidiaries.


DO FIRMS DIFFER MUCH? 327

market share are computed using the total assets of all banks operating in a market.

III. ANALYSIS OF VARIANCE IN PROFITABILITY

Multimarket data are particularly suited to analyzing the relationship between market structure and performance. With such data, it is possible to decompose variance in profitability into two orthogonal parts: betweenmarket variation and within-market variation over firms. The classical

approach predicts large between-market variation, and uses market concentration, along with other industry-level variables, as a proxy for the

market effects, while the revisionist approach predicts large within-market variation, and uses market share as a proxy for firm effects within a market.

The managerial view has implications for a different variance decomposition: between-firm variation and within-firm variation over markets. This view holds that management at the firm level is the most important

TABLE II

ANALYSIS OF VARIANCE OF PROFITABILITY

ADJUSTED R-SQUARED MEASURESa (MARGINAL SIGNIFICANCE LEVELS IN PARENTHESES)

Effect 1982 1983 1984 1982-84b 1985 1986 1987 YEAR

35.1**

(0.00) FIRM 3.5 25.3** 0.9 6.7** 80.7** 41.5** 48.0**

SHARE MKT

(0.26) (0.00) (0.41) (0.00) (0.00) (0.00) (0.00) 0.4 0.9 0.3 1.7 0.1 2.7*

0.0

(0.94) (0.23) (0.14) (0.02) (0.06) (0.27) (0.02)

14.1*

HERF

4.4

6.6

3.0*

0.0

7.1

10.9*

(0.04) (0.22) (0.12) (0.02) (0.67) (0.09) (0.02) 0.0 0.3 2.1* 0.3 0.0 0.0 3.5*

(0.83) (0.45) (0.05) (0.10) (0.71) (0.55) (0.01) FIRM+MKT 15.4 31.0** 7.0 9.6** 84.0** 51.7** 60.1** (0.08) (0.00) (0.21) (0.00) (0.00) (0.00) (0.00) FIRM + HERF 2.4 25.9** 2.0 6.9** 80.6** 41.1** 49.7**

(0.32) (0.00) (0.34) (0.00) (0.00) (0.00) (0.00) SHARE+MKT 16.7* 5.7 5.9 3.5** 0.4 7.0 11.0* SHARE

+

(0.02) (0.17) (0.14) (0.00) (0.44) (0.10) (0.03) HERF 0.0 0.0 1.6 0.3 1.5 0.0 4.0*

(0.98) (0.45) (0.12) (0.16) (0.12) (0.55) (0.02) FIRM/MKTC 1.3 26.6** 0.4 3.9** 84.0** 44.6** 49.2** (0.39) (0.00) (0.45) (0.00) (0.00) (0.00) (0.00) MKT/FIRM0 11.9 5.7 6.1 0.2* 3.3** 10.2** 12.1*

(0.10) (0.15) (0.21) (0.01) (0.01) (0.00) (0.00) aNegative values of the adjusted R-squared measure are set equal to zero. * denotes significance at the five-percent level, and ** denotes significance at the one-percent level.

bThe adjusted R-squared measures are calculated conditioned on the year effects; i.e. the adjusted

R-squared measures are the increase in adjusted R-squared above the adjusted R-squared of the year effects. 'The conditional notation means that the firm adjusted R-squared measures and the marginal significance levels are calculated conditional on the market effects, and vice versa for market and firm.



determinant of profitability, independent of the markets in which a firm operates. The managerial approach predicts large between-firm variation and small within-firm variation across markets.8

Table II presents tests of the predictions of these three hypotheses. Each row of the table presents a fixed-effects model specification, and the columns give the samples over which each model is estimated. All of the samples cover single years except for 1982-84, which is the only period over which a Chow

stability test is accepted, conditional on year effects. The entries in the table are adjusted R-squared measures, with the marginal significance level of the effects listed in parentheses below the measures. Adjusted R-squared measures are used because we are comparing the explanatory power of models with

different numbers of regressors. For the aggregated sample, 1982-84, table entries are, the increase in adjusted R-squared over the adjusted R-squared of the year effects; likewise, the significance tests are performed conditional on the year effects.

The variance decomposition suggested by the classical view can be seen by examining the MKT effects in the fourth row. The adjusted R-squared of the

market effects (i.e. of a set of market dummy variables), measures the amount of between-market variation in the sample. The residual is within-market variation. In only two of the seven years are market effects significant, in 1982 and 1987, explaining 14 percent and 11 percent of the variation in profitability.

For the aggregate 1982-84, market effects are also significant, explaining about 3 percent of the variation above that explained by year effects alone. The residual within-market variation is much larger than the betweenmarket variation, lending some support to the revisionist critique of the classical view.9

However, support for the revisionist view is ambiguous. The market share variable does not pick up much of the residual within-market variation. This can be seen by examining the third row, denoted SHARE. The market share

variable is insignificant in all but the year 1987, where it explains only 2.7 percent of the adjusted variation. The effects of market share can

also be calculated conditional on the market effects. Looking at the two SHARE + MK T it is possible to calculate the additional explanatory power

of market share by comparing it to the MKTrow above. At most, in 1982, market share adds 2.6 percent to the explanatory power of the market effects.

Likewise, market concentration is significant in only two of the seven years, 8 Firm effects will capture any differences in profits due to differences in firm behavior. In particular, the effects of differences in portfolio composition, which reflect differences in managerial philosophy, will be captured by firm-specific dummy variables. 9 In some ways this is a more stringent test of the classical hypothesis than interindustry studies using manufacturing data. Structural variables other than market concentration, such as entry barriers, do not vary as substantially across markets within an industry as they do in interindustry studies. However, as noted in the first footnote, market concentration and profitability have been found to have a significant positive correlation in many studies of the banking industry.


DO

FIRMS

DIFFER

MUCH?

329

1984 and 1987, and explains only 2.1 and 3.5 percent of the variation in these two years. Conditioning on firm effects, as calculated by comparing the FIRM + HERF row to the FIRM row, does not add to the explanatory

power of concentration.'0 Turning to the second variance decomposition, that suggested by the

managerial view of the firm and given in the FIRM row of Table II, we see

that firm effects (i.e. a set of firm dummy variables) are relatively large and

significant in four of six years." Firm effects are also significant for the period 1982-84. In the latter years of the sample, 1985, 1986 and 1987, the between-firm variation becomes very large. During 1986 and 1987, many Texas banks lost a great deal of money, as can be seen by examining the

average profitability rates listed in Table I. Profit rates fell throughout the sample period, from a high in 1982 of 1.15 percent, to a low of - 1.40 percent in 1987.12

In the last two rows of Table II, we attempt to measure the relative

importance of firm and market effects. Since the models are not nested,13 statistical hypothesis tests cannot speak directly to this issue, although they

can provide some evidence. The two rows, FIRM/MKT and MKT/FIRM, have entries calculated conditional on the market and firm effects. Specifically,

the increase in adjusted R-squared is measured and the hypothesis tests are calculated for the additional explanatory power of the effect over and above the explanatory power of the conditioned effect. These two rows clear up any ambiguity about the relative importance of firm and market effects that could be caused by a correlation between the effects. Conditionally and unconditionally, firm effects are more important than market effects in 1983 and in the last three years of the sample. In 1982 and

1984, the market effects are larger than the firm effects, but not for the

1982-84 aggregate. Measuring the firm effects conditional on the market effects, and vice versa does not affect either the statistical significance or the size of the effects.

IV. CONCLUSIONS

We find support for the following four empirical propositions: (i) During the recession in the Texas banking industry, firm effects are large and significant. '0 Results of the market share and market concentration variables are consistent with those of Scott and Pascoe [1986].

" Because of systematic differences in portfolio composition between banks and thrifts, the addition of thrifts to the sample would likely increase the importance of firm effects relative to market effects and would not substantively alter the paper's conclusions.

'2These profit figures are simple averages of all observations in the sample, and are not

weighted by assets.

13 The models are not nested because one consists of a set of firm dummy variables and the

other of a set of market dummy variables.



(ii) Prior to the recession, firm effects and market effects are much smaller, though statistically significant.

(iii) Market share effects are very small.

(iv) Market concentration effects are very small.

In so far as they can be interpreted with respect to the classical, revisionist and managerial hypotheses, the results offer the most support to the managerial view. The observed increase in the variability of firm performance during times of stress is what one would expect if managerial ability is the primary determinant of firm performance. However, data for the earlier, more prosperous part of the sample period do not give as much support to the managerial hypothesis. The classical emphasis on the market as the unit of observation does not find any support in the data, but its alternative, the revisionist critique, finds only partial support.

These results agree more closely with those of Scott and Pascoe than with those of Schmalensee. Further, the results demonstrate the degree to which macroeconomic conditions can affect the structure-performance relationship. Finally, the paper indicates that industry-specific panel data are a usable alternative to the somewhat-dated FTC Line of Business data. DEAN

AMEL,

ACCEPTED

MARCH

1990

Federal Reserve Board,

Washington, DC, USA AND LUKE FROEB,

University of Chicago, and US Department of Justice, Washington, DC, USA.

REFERENCES

BAIN, J. S., 1956, Barriers to New Competition, Cambridge: Harvard University Press. BENSTON, G. J., 1985, 'The Validity of Profits-Structure with Particular Reference to the FTC's Line of Business Data', American Economic Review, 75, March, pp. 37-67. CORNYN, A., HANWECK, G., RHOADES, S. and ROSE, J., 1986, 'An Analysis of the Concept of Corporate Separateness in BHC Regulation from an Economic Perspective', in Bank Structure and Competition, Federal Reserve Bank of Chicago, Chicago, pp. 174-212. DEMSETZ, H., 1973, 'Industry Structure, Market Rivalry, and Public Policy', Journal of Law and Economics, 16, April, pp. 1-10. FLANNERY, M. J., 1986, 'Contagious Bank Runs, Financial Structure and Corporate Separateness within a Bank Holding Company', in Bank Structure and Competition, Federal Reserve Bank of Chicago, Chicago, pp. 213-230.


DO FIRMS DIFFER MUCH? 331 GILBERT, R. A., 1984, 'Bank Market Structure and Competition: A Survey', Journal of

Money, Credit and Banking, 16, November, pp. 617-645. GUNTHER, J. W., 1989, 'Texas Banking Conditions: Managerial versus Economic

Factors', Financial Industry Studies (Federal Reserve Bank of Dallas), October. HARRIS, F., 1988, 'Testable Competing Hypotheses from Structure-Performance

Theory: Efficient Structure Versus Market Power', Journal of Industrial Economics, 36, March, pp. 267-280. KING, B. F., 1982, 'Review of Empirical Literature', Economic Review (Federal Reserve

Bank of Atlanta), April, pp. 35-40. PELTZMAN, S., 1977, 'The Gains and Losses from Industrial Concentration', Journal of

Law and Economics, 20, October, pp. 229-263. RHOADES, S. A., 1982, 'Structure-Performance Studies in Banking: An Updated

Summary and Evaluation', Staff Study 119 (Board of Governors of the Federal Reserve System), August.

SCHMALENSEE, R.. 1985, 'Do Markets Differ Much?' American Economic Review, 75, June, pp. 341-351. SCOTT, J. T. and PASCOE, G., 1986, 'Beyond Firm and Industry Effects on Profitability in Imperfect Markets', Review of Economics and Statistics, 68, May, pp. 284-292. SHEPHERD, W. G., 1972, 'The Elements of Market Structure', Review of Economics and Statistics, 54, February, pp. 25-37. WEISS, L. W., 1974, 'The Concentration-Profits Relationship and Antitrust', in H. J. GOLDSCHMID et al., (eds.), Industrial Concentration and the New Learning, LittleBrown, Boston. WERDEN, G., 1988, 'The Divergence of SIC Industries from Antitrust Markets: Some Evidence from Price Fixing Cases', Economic Letters, 28, pp. 193-200. WHITEHEAD, D. D., 1982, 'The Sixth District Survey of Small Business Credit', Economic Review (Federal Reserve Bank of Atlanta), April, pp. 42-48.
