The Alternative Techniques: Variance Components analysis versus anova Two schools of thought contest the source of business unit profitability. The classical school of industrial organization economists uses the structure-conduct-performance paradigm Bain 1951,1956), while a school of revisionists argue for firm efficiency(Demsetz, 1973 Conner, 1991). The classical school argues that firms earn abnormal profits due to their industry structure and market power(Bain 1951, 1956); the revisionist school argues that efficient and well-managed firms grow to dominate industries(Wernerfelt, 1984; Rumelt, 1984, 1987) Most empirical studies testing whether industry or firm effects matter more for business unit performance use two techniques, ANOVA and variance components analysis (VCA) Several studies include both, but the authors demonstrate a preference for one method over the other by relying more heavily on one than the other in deriving conclusions. These studies are descriptive rather than positive; they seek to identify the magnitude of a particular effect rather than test an explanation for the effects. These studies often use broad measures, such as dummy variables, to capture industry and firm effects. While industry effects have been modeled consistently across the studies, differing representations of corporate and business effects have been presented Schmalensee(1985) provides the first major study of industry, corporate, and business effects, using both VCA and ANOVA, though clearly preferring vCA for determining importance of effects. He attempts to determine the relative importance of industry or firm on 1974 FTC line-of-business data for manufacturing firms. Using ANoVa to measure the significance of each effect, he finds that firm effects(the same as Rumelt's corporate effects)are insignificant and concludes that firm management does not matter. Using VCa to compare the relative importance of each effect, he finds that corporate effects do not exist, important industry