Gaussian Inference in General AR(1) Models Based on Long Difference
2011/01/11
研討會日期 : 2011-01-11
時間 : 14:30
主講人 : Professor Biing-Shen Kuo
地點 : Conference Room B110
演講者簡介 : Biing-Shen Kuo got his Ph.D. in Economics from University of Rochester in 1995. He is currently serving as Professor and Head of Department of International Trade at National Chengchi University. His research field is in time series theory and empirical international finance.
演講摘要 : This paper develops a simple long-difference transformation for estimation and inference in general AR(1) models. As in Phillips and Han (2008), a Gaussian limit theory with a convergence rate of $\sqrt{T}$ is available, whether or not a unit root is present in the process. Yet, the novelties of our limit results are that the same weak convergence applies to the models with or without a trend, and that the asymptotic distribution is characterized by a constant variance of value 2. The merits promise usefulness of the long-difference transformation in applications to dynamic panels.
