Sieve Extremum Estimation of Transformation Models
2014/02/12
研討會日期 : 2014-02-12
時間 : 14:00
主講人 : Mr. Jong-Myun Moon
地點 : Conference Room B110
演講者簡介 : Mr. Jong-Myun Moon will receive his Ph.D. in Economics from University of California, San Diego in 2014. His primary research focuses on Econometrics and Secondary are Financial Econometrics, Labor Economics, and Game Theory. He is applying for the position of the Institute of Economics, AS right now.
演講摘要 : This paper studies transformation models T0 (Y ) = X’β0 + ε with an unknown monotone transformation T0. Our focus is on the identification and estimation of 0, leaving the specification of T0 and the distribution of ε nonparametric. We identify β0 under a new set of conditions; specifically, we demonstrate that identification may be achieved even when the regressor X has bounded support and contains discrete random variables. Our identification is constructive and leads to sieve extremum estimator. The empirical criterion of our estimator has a U-process structure, and therefore does not conform to existing results in the sieve estimation literature. We derive the convergence rate of the estimator and demonstrate its asymptotic normality. For inference, the weighted bootstrap is proved to be consistent. The estimator is simple to implement with standard optimization algorithms. A simulation study provides insight on its finite-sample performance.
