4/30일 금요일 개최되는 학과세미나를 안내드립니다. 이번 세미나는 온라인으로만 진행할 예정이오니, 참고 부탁드립니다. 많은 참여 부탁드립니다.
- 일시 : 2021년 4월 30일 (금) 16:30 - 18:00 - 발표자 : 이성원 교수님(서강대학교) - 주제 : Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection
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This paper develops nonparametric panel quantile regression models with sample selection. The class of models allows the unobserved heterogeneity to be correlated with time-varying regressors in a time-invariant manner. I adopt the correlated random effects approach proposed by Mundlak (1978) and Chamberlain (1980), and the control function approach to correct the sample selection bias. The class of models is general and flexible enough to incorporate many empirical issues, such as endogeneity of regressors and censoring. Identification of the model requires that T ≥ 3, where T is the number of time periods, and that there is an excluded variable that affects the selection probability. I also suggest semiparametric models for practical implementation of estimation. Based on the identification result, this paper proposes sieve two-step estimation to estimate the model parameters and establishes the asymptotic theory for the sieve two-step estimators, including consistency, convergence rates, and asymptotic normality of functionals. A small Monte-Carlo simulation study with a semiparametric model confirms that the estimators perform well in finite samples.