Semiparametric Identification and Estimation of Multinomial Discrete Choice Models using Error Symmetry

[题目] Semiparametric Identification and Estimation of Multinomial Discrete Choice Models using Error Symmetry

[主讲人] 颜瑾,香港中文大学经济系

[主持人] 章勇辉,中国人民大学经济学院 [时间] 2019年9月20日15:00 [地点] 明德主楼729会议室

[摘要] Individual heterogeneity is prevalent in economic studies of choice behavior. A single type of error structure may not represent all the individuals in the population and the preference or taste for each attribute of an alternative could vary across individuals. We provide a new strategy to identify and estimate the preference parameters in utility functions in the presence of unobserved individual heterogeneity with cross-sectional multinomial choice data. Our method allows for an arbitrary mixture of error structures as long as each one satisfies conditional central symmetry. Random coefficients are also permitted if the joint distribution of the random coefficients and error terms is centrally symmetric. In this case, we focus on studying the median or mean of each random coefficient. The econometrician can be agnostic about the number of random coefficients and which regressors have random coefficients. Flexible correlation and heteroskedasticity among alternatives are also permitted. In addition to central symmetry in error structure, we need a special regressor for each alternative that is independent of the error terms conditional on other regressors. But the usual large support condition on those special regressors is not required by our method. Based on the identification strategy, we propose an M-estimator by minimizing the squared difference of the estimated volumes of two symmetric hyper-rectangles under the probability measure of the error terms. We show that the M-estimator has a root N convergence rate and admits a normal limiting distribution, making statistical inference straightforward.

[主讲人简介] Jin Yan is an econometrician from the department of economics at the Chinese University of Hong Kong. She was awarded a PhD in Economics degree from the University of Wisconsin-Madison and joined the Chinese University of Hong Kong as an assistant professor in 2013. Her main research field is econometrics. Specifically, she focuses on studying semiparametric methods, discrete choice, rank-ordered choice, dynamic choice, and experimental choice data. She has published her work in the Journal of Econometrics. In addition to econometric theory, she is also working on applied micro topics such as dynamics in labor market states and risk preferences in stochastic choices.