How Much Does Industry Matter? TORIo Richard P Rumelt Strategic Management Journal, Vol 12, No. 3(Mar, 1991), 167-185 Stable url: http://linksjstor.org/sici?sici=0143-2095%28199103%0291293a3%03c167%03ahmdim%3e2.0.c0%03b2-v Strategic Management Journal is currently published by John wiley sons Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.htmlJstOr'sTermsandConditionsofUseprovidesinpartthatunlessyou have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://wwwjstor.org/journals/jwiley.html Each copy of any part of a jSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission jStOR is an independent not-for-profit organization dedicated to creating and preserving a digital archive of scholarly journals. For more information regarding JSTOR, please contact support@jstor. org http://wwwjstor.org Wed nov204:10:19200
Strategic Management Journal, Vol. 12, 167-185(1991) HOW MUCH DOES INDUSTRY MATTER? RICHARD P RUMELT Anderson Graduate School of Management, University of California, Los Angeles, This study partitions the total variance in rate of return ar TC Line of Business reporting units into industry factors(whatever their nature) tors, factors assoc with the corporate parent, and business-specific factors Schmalensee (1985 reported that industry factors were the strongest, corporate and market share effects being extremely weak, this study distinguishes between stable and fiuctuating effects and reaches markedly different conclusions. The data reveal negligible corporate effects, small stable industry effects, and very large stable business-unit effects. These results imply that the mose portant sources of economic rents are business-specific; industry membership is a much less important source and corporate parentage is quite unimportant Because competition acts to direct resources the total variance of rates of return on assets in towards uses offering the highest returns, persist- the 1975 LB data into industry, corporate, and ently unequal returns mark the presence of either market-share components. He reported that:(1) natural or contrived impediments to resource corporate effects did not exist;(2) market-share flows. The study of such impediments is a effects accounted for a negligible fraction of the principal concern of industrial organization eco- variance in business-unit rates of return; ( 3) nomics and the dominant unit of analysis in industry effects accounted for 20 percent of the that field has been the industry. The implicit variance in business-unit returns; (4) industry sumption has been that the most important effects accounted for at least 75 percent of the arket imperfections arise out of the collective variance in industry returns. He concluded circumstances and behavior of firms. However, " the finding that industry effects are important the field of business strategy offers a contrary supports the classical focus on industry-level view: it holds that the most important impedi- analysis as against the revisionist tendency to ments are not the common property of collections downplay industry differences"(1985: 349) of firms, but arise instead from the unique Schmalensee's study was innovative and techni endowments and actions of individual corpo- cally sophisticated. Nevertheless, there are diffi- rations or business-units. If this is true. the ulties with it traceable to the use of a single industry may not be the most useful unit of year of data. In this article I perform a new analysis. Consequently, there should be consider variance co nents analysis of the FTC LB able interest in the relative sizes of inter-industry data that corrects this weakness. I analyze the nd intra- industry dispersions in long-term profit four years(1974-1977)of data available and Despite these arguments for this issue's sali- ence, surprisingly little work addressed it until 'Industry and ffects are (unobserved)com Schmalensee's(1985 )estimation of the variance moenmbesrsh returns that are associate omponents of profit rates in the FTC Line of industry return'is the calculated average return of the Business(LB)data. Schmalensee decomposed business-units in that industry 0143-2095/91/030167-190950 Received 16 February 1990 c 1991 by John Wiley Sons, Ltd Revised 28 December /990
168 R. P. Rumelt include components for overall bu cycle profitability is unrelated to ffects, stable and transient industry effects, as effects. While industry differences matter, they well as stable and transient business-unit effects. 2 are clearly not all that matters. If this intra- Like Schmalensee, I find that corporate effects industry variance is due to transient disequilib are negligible. However, I draw dramatically rium phenomena, then the 'classical focus on different conclusions about the importance of industry'would still be a contender; although it industry effects, the existence and importance of explains only 8 percent of the variance, it would business-level effects, and the validity of industry- be the only stable pattern in the data. But, if a level analysis large portion of the intra-industry variance is due The me raightforward ble differeng analysis is to start with what Schmalensee's results industries, then the 'classical focus on industry' left undecided. The first major incertitude is that, may be misplaced although 20 perce usiness-unit returns explained by industry effects, we do not know In this study, I find that the majority of this industry effects rather than to transient phena a how much of this 20 percent is due to sta residual variance is due to stable long-term diferences among business-units rather than ena. For example, in 1975 the return on assets to transient phenomena. Using Schmalensee's of the passenger automobile industry was 6.9 sample, I find that stable business-unit effects percent and that of the corn wet milling industry account for 46 percent of t e variance. Indeed was 35 percent. But this difference was far from the stable business-unit effects are six times able: in the following year the industries more important than stable industry effects in virtually reversed positions, auto's return rising explaining the dispersion of returns. Busines to 22. 1 percent and corn wet millings return units differ from one another within industries falling to 11.5 percent (Federal Trade Con a great deal more than industries differ from mission, 1975, 1976). The presence of industry one another specific fluctuations like these adds to the variance in industry returns observed in any one year. The conceptual conclusions are straightfor Thus, Schmalensee's snapshot estimate of the ward. The classical focus on industry analysis variance of industry effects' is the variance is mistaken because these industries are too among stable industry effects plus the variance heterogeneous to support classical theory. It of annual fluctuations. But the classical focus'is is also mistaken because the most important surely on the stable differences among industries, impediments to the equilibration of long-term ather than on random year-to-year variations in rates of return are not associated with industry, those differences but with the unique endowments, positions, and strategies of individual businesses My analysis of the FtC lb data shows that The empirical warning is equally striking. Most stable industry effects account for only 8 of the observed differences among industry percent of the variance in business-unit returns. returns have nothing to do with long-term Furthermore, only about 40 percent of the industry effects; they are due to the random dispersion in industry returns is due to stable distribution of especially high and low-performing business-units across industries. As will be shown an FtC industry return must be at least 15.21 The second incertitude concerns the variance not percentage points above the mean to warrant a explained by industry effects. Schmalensee noted conclusion(95 percent confidence)that the true (p.350)it ortant to recognize that stable industry effect is positive. Fewer than 80 percent of the variance in business-unit in forty industry returns are high enough to pass 2'Stable'industry effects are the(unobserved )time-invariant BACKGROUND (unobserved) time-invariant components or eets are the Most industrial organization research on business returns that are not due to industry or corporate membership. corporate, and industry profitability tests prop
How Much Does Industry Matter? 169 ositions about the causes of differential perform- Most prior work touching on the issue of locus ance. The primary tradition made industry the has done so tangentially, rough measures of intra- unit of analysis and sought a link between industry di dispersions in return being me industry concentration(and entry barriers) and in passing within a study on a different topic industry profitability (usually measured with Stigler, for example, studying the convergence pooled data).3A second tradition focused on of profit rates over time, used the relative inter-firm differences in performance, seeking proportions of positive-profit and loss corpo explanation first in terms of firm size and later rations to construct rough estimates of intra- in terms of market share. 4 The early reaction industry variances in the rate of return by IRS against the mainline tradition viewed the concen- size class(his estimates unavoidably confound tration-profitability correlation as an artifact inter-period and inter-firm variances). He induced by the deeper share-profitability link. remarked in passing(1963: 48)that these values ly, the stochastic and efficiency views explain were much larger than inter-industry variances both firm profitability and market-share, and thus but drew no implications, Fisher and Hall (1969) concentration, in terms of exogenous differential measured the long-term(1950-1964)dispersion firm efficiencies. 6 in rates of return about industry averages in In contrast to economics, business strategy order to obtain a measure of risk that could be research began with the presumption of hetero- regressed against industry profitability. Although geneity within industries and has only recently they did not remark the fact, they obtained come to grips with the question of how differences estimates that were approximately double their in efficiency are sustained in the face of compe- reported standard deviation in inter-industry rates tition. Thus. the earliest case research informed of return by the ' concept focused on the different McEnally (1976), in an analysis of results roaches ompetition adopted by firms obtained by Conrad and Plotkin(1968) within the same industry. As the field matured, that industries with larger average return tend attention turned towards developing quantitative also to have larger dispersions in long-term inter- measures of this diversity' and, more recently, firm rates of return. His figures"show inter-firm o its explanation in economic terms variances that are two to five times as large as Each of these streams of work presumes inter-industry variances different causal mechanisms and employs differ- As part re-examination of the ent units of analysis. Claims about whether profit- concentration-profitability relationship, Gort and persion reflects collusion, share-based Singamsetti (1976) were apparently the first to market power, or difficult-to-imitate resources explicitly ask whether or not 'the profit rates of are coupled with claims that the more aggregate firms cluster around industry means. Assigning phenomena are spurious or counter-claims that firms to 3-digit and 4-digit industries, they found less aggregate phenomena are noise. My intention to their surprise that the data failed to support here is to suppress concern with causal mechan- the hypothesis that industries have different isms and focus instead on the question of locus. characteristic levels of profitability. Furthermore Put differently, my concern here is with the they noted that the proportion of the total existence and relative importance of time, corpo- variance explained by industry was low rate, industry, and business-unit effects, however (approximately 11 percent, adjusted), did not generated,on the total dispersion of reported increase as they moved from 3-digit to 4-digit rates of return industry definitions, and did not increase as the sample was restricted to more specialized firm See Weiss'( 1974)survey of this line of work ad and See Demsetz(1973)and Mancke(1974), as well as Lippi Plotkin computed intra-industry variances and Rumelt(1982). directly from deviations about industry averages. Because hey are not based on true Hatten and Schendel (1977) provided early contribution their results may overestimate intra-industry variances and see McGee and Thomas(1986)for a review of the strategic produce substantially upwards biased estimates of inter- dustry variances (although the latter was not of direct K See Teece(1982), Rumelt(1984)and Wernerfelt(1984) interest to them or to McEnally)
170 R. P Rumelt In an unpublished working paper I performed a sample of 217 large U. K firms, they measured a variance components analysis of corporate how much of firms' profitability movements over returns using 20 years of Compustat data(Rumelt, time were unique, how much were related to 1982). Although problems of industry definition other firms' movements, and how much were and firm diversification prevented definitive related to common industry movements. Nearly results, here again the intra-industry effect one-half of the companies in their sample dominated the inter-industry effect: the measured exhibited no common industry-wide response to intra-industry variance in long-term firm effects dynamic factors was three to ten times as large as the variance Hansen and Wernerfelt (1989) studied the due to industry-specific effects relative importance of Schmalensee's(1985)study was the first pub- zational factors in explaining inter-firm differences is the direct ancestor of the work presented he aa in profit rates. They found that industry explained lished work aimed squarely at these issues an Looking at the 1975 FTC LB data, Schmalensee that organizational characteristics were roughly estimated the following random-effects model: o twice as important rk=μ+ax1+βk+nS/k+∈ DATA where rik is the rate of return of corporation k's tivity in industry i, Sik is the corresponding Because the impetus for this study comes from market share, a, and Bk are industry and the existence of the unique FTC LB data corporate effects respectively, and Eik is a and because the statistical work performed is disturbance. Schmalensee used regression to fundamentally descriptive rather than hypothesis conclude that corporate effects were non-existent testing, I break with convention and discuss the Bk=0), and variance components estimation data before introducing the model to show that industry effects were significant and Data on the operations of large U. S. corpo substantial (o>0), and that share effects were rations are available from a variety of sources significant but not substantial(m >0 and o> However, there is only one source of disaggregate 2a3) data on the profits of corporations by industry- Kessides (1987) re-analyzed Schmalensee's the FTCs Line of Business Program. The FTC data, excluding corporations active in less than collected data on the domestic operations of three industries. He found statistically significant large corporations in each of 261 4-digit FTC corporate effects in the restricted sample, suggest- manufacturing industry categories. Information ng that inclusion of the less-diversified corpo- on a total of 588 different corporations was rations had lowered the power of Schmalensee's collected for the years 1974-1977; because of late test. In a related vein, Wernerfelt and Montgom- additions, deletions, acquisitions, and mergers ery(1988)estimated a model patterned after the number of corporations reporting in any one Schmalensee's, replacing return on assets with year ranged from 432 to 471. The average Tobin,s q and replacing the numerous corporate corporation reported on about 8 business-units dummy variables with a single continuous meas- Schmalensee's sample was constructed by ure of ' focus'(the inverse of diversification). starting with Ravenscraft's(1983)data-set of They found industry effects and share effects of 3186 stable and meaningful business-units-those about the same magnitudes as Schmalensee which were not in miscellaneous categories and found, and also found a small. bl all, but statistically which were neither newly created nor terminated significant, positive association between corporate during the 1974-1976 period. He then dropped focus and performance business-units in 16 FTC industries judged to Cubbin and Geroski (1987) attacked the be primarily residual classifications, dropped question of the relative strength of industry and business-units with sales less than 1 percent of firm effects with a different methodology. Using 1975 FTC industry total sales, and excluded one I I have altered his notation to preserve consistency within sets were used his research labeled A and B Sample a was constructed by