W HILE many aspects of conglomerate firms have been studied, empirical tests of their performance remain limited. Most of the studies to date test aspects of mergers generally.' Professor Eamon Kelly (1967) compared a sample of 21 firms which grew 20 per cent or more by acquisitions during the period from 1946 to various terminal dates through 1963, with firms of similar size and products but with growth mainly internal (Kelly, 1967). He found no significant difference in profitability between the two groups. Gort and Hogarty (1970) also examined a number of general aspects of mergers. Their statistical analysis indicated that the stockholders of acquired firms gained on the average, while the owners of acquiring firms lost on the average. They found that mergers have an approximately neutral effect on Ithe aggregate worth of firms that participated in them (Hogarty, 1970). Reid's studies (1968) included data evaluating a sample of conglomerate firms for the decade ending in 1961. He utilized three measures which he characterized as reflecting the interests of managers, and three reflecting the interests of stockholders. Reid concluded that more actively merging firms and firms that diversified to a greater extent in their merging activity scored higher on the criteria related to managers' interests and lower on criteria related to stockholders' interests. Lorie and Halpern (1970) studied the performance of 117 mergers taken from the Federal Trade Commission listing for 1954-1967 of all mergers in manufacturing and mining in which the acquired firm had assets greater than 10 million dollars. In the Lorie and Halpern study, the focus was particularly on the possibility of deception of investors. The mergers which they studied, therefore, were ones in which the shareholders of the acquired company received relatively complex instruments such as convertibles or warrants.2 The investment return to, stockholders of the acquired firms was analyzed on various bases measured in the period six months prior to the merger to two years after the merger. In general, the investment return performance to stockholders of the acquired firms was superior to the market performance of broad market indexes for comparable periods of time. For example, the mean rates of return for the 12and 14-month periods subsequent to the mergers were 9.34 per cent and 9.52 per cent, respectively, while corresponding rates for the market index were 7.73 per cent and 7.38 per cent. Hogarty (1970) analyzed the success of 43 mergers by the criteria of post-merger investment performance (capital gains plus dividend returns) adjusted by an Investment Performance Index (IPI) for the industry of the acquiring company. Using measurements including reinvestment of dividends, he classified 14 failures (F), 24 ambiguous (A), and 5 successes (S). For an IPI of 10 per cent, a failure was defined as a return of 9 per cent or less, a success was a return of 11 per cent or more, and the ambiguous category represented returns between 9 and 11 per cent. Not assuming reinvestment of dividends, the distribution was 3 S, 19 A and 21 F. Hogarty found these Received for publication April 5, 1971. Revision accepted for publication June 21, 1972. * This study was supported by the Research Program in Competition and Business Policy, UCLA. We appreciate the helpful suggestions of the reviewer. ' The 1171-page special edition of the Spring 1970 St. John's Law Review on conglomerate mergers contains no article with empirical data on the comparative performance of conglomerate firms. Two empirical articles in the volume deal with other aspects of performance. The S. E. Boyle paper analyzes the premerger growth and profitability characteristics of acquired companies. The paper by T. F. Hogarty reviews earlier historical studies of the success of mergers generallv. 2 Since this kind of funny money (Lorie and Halpern's term) was alleged to be characteristic of conglomerate mergers, their sample of firms is presumed to be of conglomerates. However, no formal criteria for selection were emnlnved .

T HE most frequently used estimating technique for applied economic research has been ordinary least squares (OLS). There are two theoretical justifications for its use. First, the Gauss-Markov theorem suggests that OLS estimators will outperform all other techniques in the class of linear unbiased estimators.1 Secondly, under the assumption that the error terms are normally distributed, OLS estimators can be derived as the maximum likelihood estimates. Frequently when OLS is introduced in elementary texts, the method of minimizing the sum of absolute deviations (MAD) is presented for comparison purposes, but rarely is it given serious consideration for applied uses.) Certainly one reason for such behavior stems from previous evaluations of OLS versus MAD estimators. Asher and Wallace (1963) found that the use of MAD meant one should be prepared to give up considerable efficiency 3 More recently Glahe and Hunt (1970), suggested several estimators derived under the general minimization criterion. In contrast to the Asher-Wallace study, the Glahe-Hunt model was a two-equation linear simultaneous system. Their results show that neither form of absolute deviation estimator outperformed either OLS or two-stage least squares.4 The purpose of this paper is to suggest that in at least one aspect these comparisons have given OLS a differential advantage. That is, both of these studies employed errors for their hypothesized models which were drawn from normal distributions. Consequently the OLS estimators are both maximum likelihood and best linear unbiased estimators (BLUE) under such circumstances. Since recently published works by Zeckhauser and Thompson (1970), Fama (1965) and others have called into question the assumption of normally distributed error terms, attention has begun to shift to other alternatives.5 Blattberg and Sargent (1971) have examined three techniques including both OLS and MAD when the errors are drawn from a stable Paretian distribution. Their findings indicate that the MAD estimator . performs sufficiently well that it deserves further study and elaboration. G Accordingly we have chosen to explore the relative merits of OLS and MAD for a single equation model whose errors are drawn from a double exponential parent distribution. This distribution was chosen because both estimators will exhibit theoretically desirable properties. OLS remains the BLUE estimator, while MAD is the maximum likelihood estimator. Furthermore, this distribution is one member of the power distribution suggested by Zeckhauser and Thompson as an alternative to the normal. This paper is divided into, three sections. The first describes the design of the experiments. Section II presents the empirical results and the last summarizes the primary findings of the paper.