A Plug-In Averaging Estimator for Regressions with Heteroskedastic Errors
2012/10/02
研討會日期 : 2012-10-02
時間 : 14:30
主講人 : Professor Chu-An Liu
地點 : Conference Room C103
演講者簡介 : Chu-An Liu received his Ph.D. in Economics from University of Wisconsin_Madison in 2012. He is serving as Visiting Assistant Professor of Economics at National University of Singapore. His research field is in econometric theory and applied econometrics.
演講摘要 : This paper proposes a new model averaging estimator for the linear regression model with heteroskedastic errors. We address the issues of how to optimally assign the weights for candidate models and how to make inference based on the averaging estimator. We derive the asymptotic mean squared error (AMSE) of the averaging estimator in a local asymptotic framework, and then choose the optimal weights by minimizing the AMSE. We propose a plug-in estimator of the optimal weights and use these estimated weights to construct a plug-in averaging estimator of the parameter of interest. We derive the asymptotic distribution of the plug-in averaging estimator and suggest a plug-in method to construct confidence intervals. Monte Carlo simulations show that the plug-in averaging estimator has much smaller expected squared error, maximum risk, and maximum regret than other existing model selection and model averaging methods. As an empirical illustration, the proposed methodology is applied to cross-country growth regressions.
