Focused Information Criterion and Model Averaging for Large Panels with a Multifactor Error Structure
2018/11/20
研討會日期 : 2018-11-20
時間 : 14:30
主講人 : Professor Chu-An Liu (劉祝安)
主持人 : Professor Hsuan-Chih Lin
地點 : Conference Room B110
演講者簡介 : Professor Liu received his Ph.D. in Economics from University of Wisconsin-Madison in 2012. He is currently an Assistant Research Fellow at the Institute of Economics, Academia Sinica. His research field is Econometrics.
演講摘要 : This paper considers model selection and model averaging in panel data models with a multifactor error structure. We investigate the limiting distribution of the common correlated effects estimator (Pesaran, 2006) in a local asymptotic framework and show that the trade-off between bias and variance remains in the asymptotic theory. We then propose a focused information criterion and a plug-in averaging estimator for large heterogeneous panels and examine their theoretical properties. The novel feature of the proposed method is that it aims to minimize the sample analog of the asymptotic mean squared error and can be applied to cases irrespective of whether the rank condition holds or not. Monte Carlo simulations show that both proposed selection and averaging methods generally achieve lower expected squared error than other methods. The proposed methods are applied to examine possible causes that lead to the increasing wage inequality between high-skilled to low-skilled workers in the U.S. manufacturing industries.
