Course Overview

Dive into the world of panel data analysis with our comprehensive course on Panel Data Models using Stata. This program is designed to enhance your understanding of interpreting panel-data estimates and the assumptions underlying these models. Each session is reinforced with practical exercises to ensure you gain hands-on experience.

Course Objectives

By the end of this course, you will be able to:

• Analyze and implement linear, nonlinear, and dynamic panel data estimators using Stata with proficiency.
• Understand both the theoretical foundations and practical applications of panel data models.
• Make informed choices between different panel data models based on your dataset characteristics.

Duration

5 Days

Who Should Attend

This course is ideal for researchers and practitioners across various fields who are keen to deepen their understanding of panel data estimates using Stata. Whether you're in academia, industry, or policy-making, this course will enrich your analytical toolkit.

Course Content

Day 1: Introduction to Panel Data

• Overview and importance of panel data
• Getting started with panel data in Stata
• Summary statistics and dynamics

Day 2: Basic Estimation Concepts

• Data generation techniques
• Regression models and variance-covariance estimators
• Understanding margins and marginal effects

Day 3: Fixed and Random Effects

• Fixed-effects model fundamentals
• Random-effects model and comparisons
• Decision-making: Choosing between random and fixed effects

Day 4: Advanced Models and Estimation

• First-differenced estimator and population-averaged models
• Probit and logit models for panel data: random effects, fixed effects, and population averaged
• Poisson models for panel data

Day 5: Dynamic Models and Endogeneity

• Cross-sectional estimation under endogeneity
• Panel-data estimation under endogeneity
• Building and interpreting dynamic models with complex structures