Indirect Estimation of Semiparametric Binary Choice Models


  • Previous versions of the paper were presented at seminars at the statistics unit at Hanken School of Economics and at Helsinki Center of Economic Research (HECER). The authors would like to thank seminar participants, and in particular Victoria Prowse and two anonymous referees for many valuable comments and suggestions. Thanks also to the Jan Wallander and Tom Hedelius Foundation for financial support under research grants W2006–0068:1, P2007–0147:1 and W2009–0079:1.


One of the most cited studies within the field of binary choice models is that of Klein and Spady (1993), in which the authors propose a semiparametric estimator for use when the distribution of the error term is unknown. However, although theoretically appealing, the estimator has been found to be difficult to implement, and therefore not very attractive from an applied point of view. The current study offers an indirect inference-based solution to this problem. The new estimator is not only simple with good small-sample properties, but also consistent and asymptotically normal.