4 days
3–4 hours daily
This course provides an introduction to the theory and practice of panel-data analysis. After introducing the fixed-effects and random-effects approaches to unobserved individual-level heterogeneity, the course covers linear models with exogenous covariates, linear models with endogenous variables, dynamic linear models, and some nonlinear models. A quick introduction to the generalized method of moments estimation technique is also included. The differences between the individual-specific and population-averaged interpretations are discussed throughout the course. Concepts are extensively illustrated using exercises and examples worked in Stata.
Are you more interested in hierarchical linear models with nested data or random slopes? Check out our Multilevel/mixed models using Stata course.
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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.
A quick introduction to Stata
Overview of basic regression analysis
Random-effects for linear models
Fixed-effects for linear models
Correlated random-effects for linear models
Instrumental-variables estimation
Hausman–Taylor Models
Dynamic panel-data models
Random- and fixed-effects for binary models
Random- and fixed-effects for count-data models
