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Organizational training

Panel-data analysis using Stata

Description

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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Course topics

• A quick introduction to Stata
• Overview of basic regression analysis
• Estimators for linear models that require random effects
• Fixed-effect estimators for linear models
• Instrumental-variables estimators
• Hausman–Taylor Models
• Models with endogenous variables
• Dynamic panel-data models
• The Arellano–Bond estimator
• The Arellano–Bover/Blundell–Bond estimator
• Random- and fixed-effects estimators for binary models
• Random- and fixed-effects estimators for count-data models

Prerequisite

A general familiarity with Stata and a graduate-level course in regression analysis or comparable experience.

Notes

This course is available in-person or virtually. In-person training courses generally run for eight hours per day and include morning and afternoon breaks and a lunch break. Virtual training courses are typically divided into three- to four-hour daily sessions. You can arrange a convenient schedule with your instructor.

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