Panel Data Models in STATA Training Course

Overview

Introduction

This course focuses on the interpretation of panel-data estimates and the assumptions underlying the models. This course is geared for researchers and practitioners in all fields. The concepts presented are reinforced with practical exercises at the end of each section. We also provide additional exercises at the end of each section and discussion sections on which you

Course Objective:

These course will equip you with analysis and implementation of linear, nonlinear, and dynamic panel-data estimators using STATA.

Course content

• An introduction to panel data
• Getting started with panel data
• Summary statistics and dynamics
• Data generation
• The regression model
• Variance-covariance estimators
• Margins and marginal effects
• Basic panel-data estimation concepts
• Moment-based estimation
• Panel data, regression, and efficiency
• Random-effects model
• Fixed-effects model
• Comparing and random-effects estimates
• First-differenced estimator
• Deciding between random and fixed effects
• Population-averaged models
• Probit models for panel data: Random effects
• Probit models for panel data: Population averaged
• Probit models for panel data: Remarks
• Logit models for panel data: Random effects
• Logit models for panel data: Fixed effects
• Logit models for panel data: Population averaged
• Poisson models for panel data
• Cross-sectional estimation under endogeneity
• Panel-data estimation under endogeneity
• Building dynamic models
• Complex dynamic structure

What you will learn

Learning Objective:

These course will equip you with analysis and implementation of linear, nonlinear, and dynamic panel-data estimators using STATA.