Logit Versus Discriminant Analysis: A Specification Test

Andrew Lo ()

Rodney L. White Center for Financial Research Working Papers from Wharton School Rodney L. White Center for Financial Research

Abstract: Two of the most widely used statistical techniques for analyzing discrete economic phenomena are discriminant analysis (DA) and logit analysis. For purposes of parameter estimation, logit has been shown to be more robust than DA. However, under certain distributional assumptions both procedures yield consistent estimates and the DA estimator is asymptotically efficient. This suggests a natural Hausman specification test of these distributional assumptions by comparing the two estimators. In this paper, such a test is proposed and an empirical example is provided. The finite-sample properties of the test statistic are also explored through some sampling experiments.

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