E$cient estimation of binary choice models under symmetry
نویسنده
چکیده
This paper proposes a semiparametric maximum likelihood estimator for both the intercept and slope parameters in a binary choice model under symmetry and index restrictions. The estimator attains the semiparametric e$ciency bound in Cosslett (1987) under the symmetry and independence restrictions. Compared with the estimator of Klein and Spady (1993), which attains the semiparametric e$ciency bound in Chamberlain (1986), and Cosslett (1987) under the independence restriction, we show that there are possible e$ciency gains in estimating the slope parameters by imposing the additional symmetry restriction. A small Monte Carlo study is carried out to illustrate the usefulness of our estimator. ( 2000 Elsevier Science S.A. All rights reserved. JEL classixcation: C31; C34
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