170 R. P Rumelt In an unpublished working paper I performed a sample of 217 large U. K firms, they measured a variance components analysis of corporate how much of firms' profitability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