Large-dimensional panel data econometrics testing, estimation and structural changes
"This book aims to fill the gap between panel data econometrics textbooks, and the latest development on "big data", especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, esti...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
New Jersey
World Scientific
2021
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| Online Zugang: | Inhaltsverzeichnis |
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Tag hinzufügen | Zusammenfassung: | "This book aims to fill the gap between panel data econometrics textbooks, and the latest development on "big data", especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, estimation of factor-augmented panel data models, structural breaks in panels and group patterns in panels. To tackle these high dimensional issues, some techniques used in Machine Learning approaches are also illustrated. Moreover, the Monte Carlo experiments, and empirical examples are also utilised to show how to implement these new inference methods. Large-Dimensional Panel Data Econometrics: Testing, Estimation and Structural Changes also introduces new research questions and results in recent literature in this field." |
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| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | x, 156 Seiten Illustrationen |
| ISBN: | 9789811220777 978-981-12-2077-7 |