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Title: Nonparametric dynamic discrete choice models for time series data Authors:  Byeong Park - Seoul National University (Korea, South)
Leopold Simar - Universite Catholique de Louvain (Belgium)
Valentin Zelenyuk - University of Queensland (Australia) [presenting]
Abstract: The non-parametric quasi-likelihood method is generalized to the context of discrete choice models for time series data and, in particular, when lags of the discrete dependent variable appear among regressors. We derive consistency and asymptotic normality of the estimator for such models for general case and illustrate it with a few simulated and real data examples.