时 间：2022年10月24日9:30
地 点：Zoom会议ID：8155-9570-657 密码：686474
报告人：高集体 教授
主持人：周勇 教授
摘 要：
In this paper, we propose a simple dependent wild bootstrap procedure for us to establish valid inferences for a wide class of panel data models including those with interactive fixed effects. The proposed method allows for the error components having weak correlation over both dimensions, and heteroskedasticity. The asymptotic properties are established under a set of simple and general conditions, and bridge the literature of bootstrap methods and the literature of HAC approaches for panel data models. The new findings fill some gaps left by the bulk literature of the block bootstrap based panel data studies. Finally, we show the superiority of our approach over several natural competitors using extensive numerical studies.
报告人简介：
Professor Jiti Gao is Donald Cochrane Chair of Business and Economics at the Monash Business School, and Professor of Econometrics and Statistics in the Department of Econometrics and Business Statistics at Monash University. Professor Jiti Gao was an Australian Professorial Fellow between January 2010-December 2014. Since September 2012, he becomes an Elected Fellow of the Academy of the Social Sciences in Australia. He is also an Elected Fellow of the International Association for Applied Econometrics and The Journal of Econometrics.
Currently, he is a Co-Editor of the World Scientific Book Series on Econometrics and Statistics, and an Associate Editor of Econometric Theory, Journal of Business and Economic Statistics and Econometric Reviews.
Professor Jiti Gao’s recent research interests include Non- and Semi-Parametric Models and Methods, Nonstationary Time Series and Panel Data Econometrics. Since January 2000, he has published two books, two book chapters and about 100 articles by leading international journals in economics, econometrics, finance and statistics, such as Annals of Statistics, Econometric Theory, Energy Economics, Health Economics, Journal of Applied Econometrics, Journal of Banking and Finance, Journal of Business and Economic Statistics, Journal of Econometrics, Journal of Financial Econometrics, Journal of the American Statistical Association and Journal of the Royal Statistical Society Series B.