High-Dimensional Econometrics and Identification (Hardcover) (ISBN-13: 9789811200151)

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.

Author: Chihwa Kao, Long Liu
ISBN-10: 9811200157
ISBN-13: 9789811200151
Publisher: World Scientific Publishing Company
Language: English
Published: 04/24/2019
Pages: 180
Format: Hardcover
Weight: 0.91lbs
Size: 9.00h x 6.00w x 0.44d