SOURCES OF SUPERIOR PERFORMANCE were all essentially single business firms and in 1979 their combined market share ex ceeded 80%0 4. Results The correlation between yearly changes in market share and yearly value creation is 0. 4906, significant beyond the 1% level with 47 degrees of freedom. (This result does lot change materially if Philip morris, a diversified firm, is removed from the sample.) This finding suggests that these industry leaders, on the average, competed too fiercely for market share during the study period. As further evidence, Table 1 lists the estimated super normal returns of the six firms On the average, firm value was destroyed during this period although market share gains were substantial If in fact these firms engaged in occasional price and advertising wars during the study period, there should be a strong positive correlation between firm and industry returns To evaluate the effect of unexpected industry developments(e.g. price wars )on a firm's stock price, one can relate the firms returns, after controlling for systematic risk to those of a portfolio of industry stocks Because such disag total amount of value created but decomposes it into specific sources, it has been pursued less intensely in the field of finance. Nevertheless, quite a substantial literature on so-called industry-betas has de eloped over the years( King 1966; Cohen and Pogue 1967; Elton and Gruber 1973 Myers 1973; Livingston 1977; Brown and Weinstein 1985). Unfortunately, no general agreement exists on how to measure the industry effect. Some studies are sequential in nature and look at value from the CaPm residuals, while others decompose the raw returns. Furthermore, both regression and factor analysis methods are used In the present study, we are in the fortunate position of having a portfolio of industry stocks. Therefore, we do not need to create and interpret factors. To estimate the industry component of value creation, we take the daily residuals ait from CAPM and estimate an=a”+(Rn-Rn)+e,t∈T, where Ri is the return on a value weighted portfolio of industry stocks in period t and ni estimates the fraction of industry returns that translate into excess returns for firm j. These estimates are given in Table 2 To arrive at a minimalistic interpretation of these results, recall that a positive bias was created by including R t in the calculation of Rit. Even in the absence of an industry effect, the average y should be equal to 6. In fact, the average y is 0. 341, exceeding 6 by TABLE I Market Share Changes and Average Yearly alpha Change in Alphat Firm arket Share Entire Period Anheuser-Busch 0.005*(1969-79) 16.3 -0.010(1969-79) 0.003*(1969-79) 00 Pabst 0 0.007*(1969-79) 0.001(1976-79) 0.00l 0.007(1974-79) 0.004 In percentage of total barrelage sold in U.S.(Keithahn 1978) Significantly different from zero at the 0.05 level tool implies 1%"extra"return to stockholders per year