Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling (Hardcover)

Volume 40 in the Advances in Econometrics series features twenty-three chapters that are split thematically into two parts. Part A presents novel contributions to the analysis of time series and panel data with applications in macroeconomics, finance, cognitive science and psychology, neuroscience, and labor economics. Part B examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression. Individual chapters, written by both distinguished researchers and promising young scholars, cover many important topics in statistical and econometric theory and practice. Papers primarily, though not exclusively, adopt Bayesian methods for estimation and inference, although researchers of all persuasions should find considerable interest in the chapters contained in this work. The volume was prepared to honor the career and research contributions of Professor Dale J. Poirier. For researchers in econometrics, this volume includes the most up-to-date research across a wide range of topics.

General

Imprint:	Emerald Publishing Limited
Country of origin:	United Kingdom
Series:	Advances in Econometrics
Release date:	October 2019
First published:	2019
Editors:	Ivan Jeliazkov • Justin Tobias
Dimensions:	229 x 152 x 25mm (L x W x T)
Format:	Hardcover
Pages:	272
ISBN-13:	978-1-83867-420-5
Categories:	Books > Business & Economics > Economics > Econometrics > Economic statistics
LSN:	1-83867-420-9
Barcode:	9781838674205

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