Introduction to Regression Models for Panel Data Analysis

Abstract

Panel methods are appropriate for large-N, small-T data where N represents individual units – for example persons, families, organizations, cities – observed at two or more points in time T. This workshop covers the basic theory underlying the analysis of panel data along with essential terminology, an overview of the kind of data that are appropriate for panel analysis, examples from various disciplines, and a list of common mistakes made when working with panel data models. We then work through an example of an application of the linear error components model from assumptions to estimation, specification tests and interpretation. The workshop concludes with a brief discussion of limitations, extensions, and related approaches.