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SEMIPARAMETRIC ESTIMATION OF A LOCATION PARAMETER IN THE BINARY CHOICE MODEL

Published online by Cambridge University Press:  01 February 1999

Songnian Chen
Affiliation:
Hong Kong University of Science and Technology

Abstract

This paper considers the estimation of a location parameter in the binary choice model with some weak distributional assumptions imposed on the error term in the latent regression model. Two estimators are proposed here, both of which are two-step estimators; in the first step, the slope parameters are consistently estimated by existing methods; in the second step, the location parameter is consistently estimated based on a moment condition. The estimators are shown to be consistent and asymptotically normal. A small Monte Carlo study illustrates the usefulness of the estimators. We also point out that the location and slope parameters can be estimated simultaneously.

Type
Research Article
Copyright
© 1999 Cambridge University Press

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