Baltagi | Econometric Analysis of Panel Data | Buch | 978-3-030-53952-8 | sack.de

Buch, Englisch, 424 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 828 g

Reihe: Springer Texts in Business and Economics

Baltagi

Econometric Analysis of Panel Data

Buch, Englisch, 424 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 828 g

Reihe: Springer Texts in Business and Economics

ISBN: 978-3-030-53952-8
Verlag: Springer International Publishing


This textbook offers a comprehensive introduction to panel data econometrics, an area that has enjoyed considerable growth over the last two decades. Micro and Macro panels are becoming increasingly available, and methods for dealing with these types of data are in high demand among practitioners. Software programs have fostered this growth, including freely available programs in R and numerous user-written programs in both Stata and EViews.
Written by one of the world’s leading researchers and authors in the field, Econometric Analysis of Panel Data has established itself as the leading textbook for graduate and postgraduate courses on panel data. It provides up-to-date coverage of basic panel data techniques, illustrated with real economic applications and datasets, which are available at the book’s website on springer.com.



This new sixth edition has been fully revised and updated, and includes new material on dynamic panels, limited dependent variables and nonstationary panels, as well as spatial panel data. The author also provides empirical illustrations and examples using Stata and EViews.

“This is a definitive book written by one of the architects of modern, panel data econometrics. It provides both a practical introduction to the subject matter, as well as a thorough discussion of the underlying statistical principles without taxing the reader too greatly."
Professor Kajal Lahiri, State University of New York, Albany, USA.

"This book is the most comprehensive work available on panel data. It is written by one of the leading contributors to the field, and is notable for its encyclopaedic coverage and its clarity of exposition. It is useful to theorists and to people doing applied work using panel data. It is valuable as a text for a course in panel data, as a supplementary text for more general courses in econometrics, and as a reference."
Professor Peter Schmidt, Michigan State University, USA.

“Panel data econometrics is in its ascendancy, combining the power of cross section averaging with all the subtleties of temporal and spatial dependence. Badi Baltagi provides a remarkable roadmap of this fascinating interface of econometric method, enticing the novitiate with technical gentleness, the expert with comprehensive coverage and the practitioner with many empirical applications.”
Professor Peter C. B. Phillips, Cowles Foundation, Yale University, USA.
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Zielgruppe


Upper undergraduate


Autoren/Hrsg.


Weitere Infos & Material


Introduction.- The One-Way Error Component Regression Model.- The Two-Way Error Component Regression Model.- Test of Hypotheses with Panel Data.- Heteroskedasticity and Serial Correlation in the Error Component Model.- Seemingly Unrelated Regressions with Error Components.- Simultaneous Equations with Error Components.- Dynamic Panel Data Models.- Unbalanced Panel Data Models.- Special Topics.- Limited Dependent Variables and Panel Data.- Nonstationary Panels.- Spatial Panel Data Models.


Badi H. Baltagi is a Distinguished Professor of Economics and Senior Research Associate at the Center for Policy Research, The Maxwell School, Syracuse University (USA). Professor Baltagi is the current editor of Economics Letters, having previously served as the editor of Empirical Economics (1999-2018) and as the replication editor for the Journal of Applied Econometrics (2003-2018). He is a fellow of the Journal of Econometrics as well as Econometric Reviews and a recipient of the Multa and Plura Scripsit Awards from Econometric Theory, as well as the Distinguished Authors Award from the Journal of Applied Econometrics.


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