Description

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.

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

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Hardback by Ivan Jeliazkov , Justin Tobias

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Volume 40 in the Advances in Econometrics series features twenty-three chapters that are split thematically into two parts. Part A... Read more

    Publisher: Emerald Publishing Limited
    Publication Date: 18/10/2019
    ISBN13: 9781838674205, 978-1838674205
    ISBN10: 1838674209

    Number of Pages: 272

    Non Fiction , Business, Finance & Law

    Description

    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.

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