Module 10: Linear Panel Data Models
This training module provides an overview of linear panel data models as well as testing and correcting for attrition bias.
The general objective of this training module is to provide an overview of linear panel data models as well as testing and correcting for attrition bias. The training materials cover several techniques that can be used to estimate linear panel data models – namely, pooled ordinary least squares (POLS) and the first-differenced (FD), fixed effects (FE), and random effects (RE) estimators. We also briefly introduce the correlated random effects (CRE) approach.
The more specific objectives are to:
- Review the difference between panel/longitudinal data and pooled cross-sectional data
- Describe how to analyze pooled cross-sectional data
- Introduce how to conduct a Chow test for structural change
- Introduce the unobserved effects linear panel data model
- Review the basic theory and implementation of the POLS, FD, FE, and RE estimators
- Introduce the correlated random effects (CRE) approach
- Review what is meant by attrition and attrition bias
- Describe how to test for attrition bias using a regression-based test
- Describe how to correct for attrition bias using inverse probability weights
Nicole Mason-Wardell, Saweda Liverpool-Tasie, and Paul Samboko