Hong Il Yoo (Durham University), 4 April, 2016, 4:30pm, NUBS 1.13

Speaker: Hong II Yoo, Durham University 

Title: Semiparametric Estimation of the Random Utility Model with Rank-Ordered Choice Data  

Date & Time: 4 April 2016 (Monday), 4:30-5:45 PM

Venue:  Newcastle University Business School, Room 1.13

                  5 Barrack Road, Newcastle upon Tyne, NE1 4SE 

Abstract:

We propose semiparametric methods for estimating the random utility model exploiting rank-ordered choice data. The term “semiparametric” refers to the fact that the preference parameters of interest are finite dimensional but the error term in the random utility function has an unspecified distribution. We allow for a flexible form of heteroscedasticity across individuals. The case when random coefficients can be allowed is also discussed. We show the strong consistency of the proposed generalized maximum score (GMS) estimator. The asymptotic distribution of the GMS estimator is nonstandard. For inference purpose, we propose the smoothed GMS (SGMS) estimator. The SGMS estimator is strongly consistent and asymptotically normal, making inference straightforward. Monte Carlo experiments provide the evidence that the proposed estimators outperform the parametric maximum likelihood estimators in the presence of interpersonal heteroscedasticity and unobserved taste heterogeneity. An illustrative empirical application using a bank account choice data set suggests that the proposed estimators are capable of finding plausible and robust solutions.

Last modified: Tue, 15 Mar 2016 12:55:31 GMT