ABSTRACT

In the last 20 years, econometric theory on panel data has developed rapidly, particularly for analyzing common behaviors among individuals over time. Meanwhile, the statistical methods employed by applied researchers have not kept up-to-date. This book attempts to fill in this gap by teaching researchers how to use the latest panel estimation methods correctly.

Almost all applied economics articles use panel data or panel regressions. However, many empirical results from typical panel data analyses are not correctly executed. This book aims to help applied researchers to run panel regressions correctly and avoid common mistakes. The book explains how to model cross-sectional dependence, how to estimate a few key common variables, and how to identify them. It also provides guidance on how to separate out the long-run relationship and common dynamic and idiosyncratic dynamic relationships from a set of panel data.

Aimed at applied researchers who want to learn about panel data econometrics by running statistical software, this book provides clear guidance and is supported by a full range of online teaching and learning materials. It includes practice sections on MATLAB, STATA, and GAUSS throughout, along with short and simple econometric theories on basic panel regressions for those who are unfamiliar with econometric theory on traditional panel regressions.

chapter 1|9 pages

Basic Structure of Panel Data

chapter 3|15 pages

Factor Number Identification

chapter 4|20 pages

Decomposition of Panel

Estimation of common and idiosyncratic components

chapter 5|20 pages

Identification of Common Factors

chapter 6|35 pages

Static and Dynamic Relationships

chapter 7|24 pages

Convergence

chapter 8|11 pages

Appendix

Basic panel regressions