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This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.
List of contents
1. Introduction; 2. Homogeneity test for linear regression models (analysis of covariance); 3. Simple regression with variable intercepts; 4. Dynamic models with variable intercepts; 5. Simultaneous-equations models; 6. Variable-coefficient models; 7. Discrete data; 8. Truncated and censored data; 9. Cross-sectional dependent panel data; 10. Dynamic system; 11. Incomplete panel data; 12. Miscellaneous topics; 13. A summary view.
About the author
Cheng Hsiao is Professor of Economics at the University of Southern California. He has worked mainly in integrating economic theory with economic analysis. Professor Hsiao has made extensive contributions in methodology and empirical analysis in the areas of panel data, time series, cross-sectional data, structural modeling, and measurement errors, among other fields. He is the author of the first two editions of Analysis of Panel Data and has been a co-editor of the Journal of Econometrics since 1991. He received his PhD in Economics from Stanford University.
Summary
This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined.
Report
Review of previous edition: 'Researchers will find that the insights that they gain from working through the book's tougher sections are well worth the effort. The book remains an indispensable and comprehensive reference for panel estimation methods.' David C. Ribar, International Journal of Forecasting
