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OverviewIn 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. Full Product DetailsAuthor: Chihwa Kao (Univ Of Connecticut, Usa) , Long Liu (Univ Of Texas At San Antonio, Usa)Publisher: World Scientific Publishing Co Pte Ltd Imprint: World Scientific Publishing Co Pte Ltd ISBN: 9789811200151ISBN 10: 9811200157 Pages: 180 Publication Date: 24 April 2019 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |