Econometric Analysis of Panel Data

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Provides up-to-date coverage of panel data analysis

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Includes several applications in economics, illustrated with Stata and EViews,

highlighting the content’s practical value

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Covers important topics in panel data analysis, e.g. dynamic panels,

nonstationary panels, limited dependent variables and spatial panel data

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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.

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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 andto people doing applied work using panel data.

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