中國人民大學經濟學院          數量經濟學Seminar      
    
題目：Model Selection and Model Averaging for Nonlinear Regression Models  
報告人：劉慶豐 教授  
時間：2017年3月23日（周四）15:00－16:00  
地點：明德主樓0404  
         
   
Abstract: This paper considers the problem of model selection and model averaging for nonlinear regression models. We propose a new information criterion called nonlinear model information criterion (NIC)，which is proved to be an asymptotically unbiased estimator of the risk function under nonlinear settings. We also develop a nonlinear model averaging method (NMA) and extend NIC to NICMA criterion, which is the corresponding weight choosing criterion for NMA. By taking account of complexity of model form into the penalty term, NIC and NICMA achieve significant gain of performance. The optimality of NMA, convergence of the selected weight and other theoretical properties are proved. Simulation results show that NIC and NMA lead to relatively lower risks compared with alternative model selection and model averaging methods under most situations.  
   
報告人簡介：日本國立小樽商科大學教授，日本京都大學經濟研究所訪問教授。2007年獲得日本京都大學經濟學博士，2008年在美國普林斯頓大學做博士后研究。研究領域為計量經濟學理論與方法，研究成果發表在Econometrics Journal, Econometric Reviews, Mathematics and Computers in Simulation等多個國際專業雜志。  
   
   
                 中國人民大學經濟學院          數量經濟學教研室          2016年3月20日