World Scientific Publishing Company High-Dimensional Econometrics And Identification

Product Description In many applications of econometrics and economics, a large proportion of the questions of interest are identification. An economist may be interested in uncovering the true signal when the data could be very noisy, such as time-series spurious regression and weak instruments problems, to name a few. In this book, High-Dimensional Econometrics and Identification, we illustrate the true signal and, hence, identification can be recovered even with noisy data in high-dimensional data, e.g., large panels. High-dimensional data in econometrics is the rule rather than the exception. One of the tools to analyze large, high-dimensional data is the panel data model.High-Dimensional Econometrics and Identification grew out of research work on the identification and high-dimensional econometrics that we have collaborated on over the years, and it aims to provide an up-todate presentation of the issues of identification and high-dimensional econometrics, as well as insights into the use of these results in empirical studies. This book is designed for high-level graduate courses in econometrics and statistics, as well as used as a reference for researchers. About the Author Chihwa Kao is Professor of Economics and Department Head at University of Connecticut, USA. He received his PhD from SUNY-Stony Brook in 1983. He has held a faculty position at Syracuse University from 1985 to 2016. Chihwa's research focuses primarily on the large dimensional econometrics, such as testing and estimation arising in the cross-sectional dependence, panel change points, large factor models, and asset pricing. His work has been published in top economics and statistics journals, including Econometrica, Journal of the American Statistical Association, Journal of Econometrics, Journal of Business and Economic Statistics, Review of Economics and Statistics, Journal of Business, Econometrics Journal, and Econometric Reviews.Long Liu is Associate Professor of Economics at the University of Texas at San Antonio. He received his PhD from Syracuse University in 2008. His research interests focus on panel data problems and spatial regressions. Liu's publication have appeared in Advances in Econometrics, Applied Economics, Econometric Journal, Econometric Reviews, Economics Letters, International Journal of Forecasting, Journal of Applied Econometrics, Journal of Forecasting, Spatial Economic Analysis, Statistical Papers and Statistics and Probability Letters.