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Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modelling.
・ISBN 978-1-83867-420-5 hard US$ 116.99
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| 著者・編者 | Jeliazkov, Ivan / Tobias, J. (eds.), |
|---|---|
| シリーズ | Advances in Econometrics |
| 出版社 | (Emerald, UK) |
| 出版年月 | 2019 |
| ページ数 | 290 pp. |
| 言語 | ENG |
| ニュース番号 | <652-452 652-P1045> |
解説
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.