The Limiting Distribution of the Maximum Rank Correlation Estimator
Han's maximum rank correlation estimator is shown to be square-root n-consistent and asymptotically normal. The proof rests on a general method for determining the asymptotic distribution of a maximization estimator, a simple U-statistic decomposition, and a uniform bound for degenerate U-processes. A consistent estimator of the asymptotic covariance matrix is provided, along with a result giving the explicit form of this matrix for any model within the scope of the maximum rate correlation estimator. The latter result is applied to the binary choice model, and it is found that the maximum rate correlation estimator does not achieve the semiparametric efficiency bound. Copyright 1993 by The Econometric Society.
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Volume (Year): 61 (1993)
Issue (Month): 1 (January)
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