Semiparametric Estimation of the Random Utility Model with Rank-Ordered Choice Data
2015/07/21
研討會日期 : 2015-07-21
時間 : 14:30
主講人 : Professor Jin Yan
主持人 : Professor Jen-Che Liao
地點 : Conference Room B110
演講者簡介 : Professor Yan received her Ph.D. in Economics from University of Wisconsin-Madison at 2013. She is currently an Assistant Professor at Chinese University of Hong Kong. Her research fields are Econometric Theory, Applied Econometrics, Semiparametric Estimation and Discrete Choice Modelling.
演講摘要 : We propose a semiparametric method 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 unspecified distributions. We allow for a flexible form of heteroskedasticity across individuals. The method does not suffer from the problem of unstable coefficients estimation across rankings that results from misspecification of parametric models, providing a way to disentangle the limited cognitive capability and model misspecification. The case that 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 another two estimators: the smoothed GMS (SGMS) and the Laplace Type (LT) estimator. Both the SGMS estimator and the LT estimator are strongly consistent and asymptotically normal, making inference straightforward. Monte Carlo experiments provide the evidence that the proposed estimators outperform the rank-ordered logit model in the presence of heteroskedasticity.
