Workshop

Panel-data analysis and difference-in-differences modeling: An applied Stata workshop

Instructor: Chris Cheng, Senior Econometrician

Date: Sunday, 9 August 2026

Time: 2:00–3:30 p.m. ET

Panel-data methods, often referred to as longitudinal methods, are widely used to analyze repeated observations on individuals, households, firms, countries, or other units over time. By exploiting both cross-sectional and time-series variation, panel data allow researchers to account for unobserved heterogeneity and evaluate changes that cannot be identified using cross-sectional data alone. This workshop provides an applied introduction to panel-data analysis and difference-in-differences (DID) methods using Stata. We begin by reviewing core panel-data concepts, including fixed-effects, random-effects, and correlated random-effects models for addressing unobserved individual-level heterogeneity. The session covers both linear and nonlinear panel-data models, with an emphasis on practical implementation, model comparison, and interpretation, including the use of specification tests to guide modeling choices. Throughout the workshop, empirical applications are illustrated using hands-on examples in Stata. [Read more ...]

Chris Cheng

Senior Econometrician

Chris Cheng is a Senior Econometrician at StataCorp LLC. He has a master's degree in economics and a PhD in agricultural and managerial economics from Texas A&M University. He has worked with technical support since 2019. Chris frequently interacts with users about technical questions and gives webinars and training courses. His interests focus on demand analysis, panel-data analysis, and other econometrics.