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High-dimensional econometrics and id...

Kao, Chihwa.

High-dimensional econometrics and identification

Record Type:	Electronic resources : Monograph/item
Title/Author:	High-dimensional econometrics and identificationChihwa Kao, Long Liu.
Author:	Kao, Chihwa.
other author:	Liu, Long.
Published:	Singapore :World Scientific Publishing,c2019.
Description:	1 online resource (180 p.) :ill. (some col.)
Subject:	Econometrics.
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/11273#t=toc
ISBN:	9789811200168$q$q(electronic bk.)

High-dimensional econometrics and identification
Kao, Chihwa.

High-dimensional econometrics and identification[electronic resource] /Chihwa Kao, Long Liu. - 1st ed. - Singapore :World Scientific Publishing,c2019. - 1 online resource (180 p.) :ill. (some col.)

Includes bibliographical references (p. 155-162) and index.

"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."--

ISBN: 9789811200168$q$q(electronic bk.)Subjects--Topical Terms:

182271
Econometrics.

LC Class. No.: HB139 / .K34 2019

Dewey Class. No.: 330.01/5195

High-dimensional econometrics and identification
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245 1 0 $a High-dimensional econometrics and identification $h [electronic resource] / $c Chihwa Kao, Long Liu.
250 $a 1st ed.
260 $a Singapore : $b World Scientific Publishing, $c c2019.
300 $a 1 online resource (180 p.) : $b ill. (some col.)
504 $a Includes bibliographical references (p. 155-162) and index.
520 $a "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."-- $c Publisher's website.
588 $a Title from web page (viewed April 5, 2019)
650 0 $a Econometrics. $3 182271
650 0 $a Identification. $3 276757
700 1 $a Liu, Long. $3 873373
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11273#t=toc