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.

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 Source: International Journal of Forecasting