| 主讲人简介： | Cheng Hsiao is a Professor of Economics at the University of Southern California. He is a fellow of Academia Sinica, a Fellow of the Econometric Society, and a Fellow of the Journal of Econometrics. In 2018, he became a Founding Fellow of the International Association for Applied Econometrics and was also awarded the Multa Scripsit Award by Econometric Theory in 2012. He has served on the advisory boards of the Pacific Economic Review and Singapore Economic Review, and as the Editor of Journal of Econometrics for over two decades.
Professor Hsiao's research interests include theoretical and applied econometrics. He has published extensively in these areas, with numerous research articles in leading journals such as Econometric Theory, Econometrica, Journal of Business and Economic Statistics, Journal of Econometrics, Journal of the American Statistical Association, Journal of Monetary Economics, and Review of Economic Studies, and several books, including Analysis of Panel Data and Panel Data Econometrics. |
| 讲座简介： | We argue that the fundamental issue of measuring the treatment effects is to obtain good predictions of the missing outcomes. However, there is no realized value to evaluate how good the predicted value generated by a particular method is. The choice of prediction method has to rely on the compatibility of the observed data with the underlying assumptions of an approach and the approach’s predictive ability. In this paper, we selectively review some causal and noncausal approaches and discuss their limitations from this perspective. |
