Semiparametric identification and estimation of discrete choice models for bundles

Abstract

We study (point) identification of preference coefficients in semiparametric discrete choice models for bundles. The approach to the identification uses an “identification at infinity” (Chamberlain, 1986) insight in combination with median independence restrictions on unobservables. We propose two-stage maximum score (MS) estimators and show their consistency. Monte Carlo evidence demonstrates that our approach performs satisfactorily in finite samples. Show more