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.
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