This course focusses on the interpretation of panel-data estimates and the assumptions underlying the models. The concepts presented are reinforced with practical exercises at the end of each session.

Course Objectives

At the end of this course the participants will be able to:

• Analyse linear, nonlinear, and dynamic panel data estimators using STATA.
• Implement linear, nonlinear, and dynamic panel data estimators using STATA.

Duration

5 Days

Who Should Attend

This course targets researchers, practitioners in all fields who want to learn about panel data estimates using STATA.

Course Content

• Introduction to panel data
• Start working with Panel data.
• Statistics and dynamics summary
• Data generation
• Regression model
• Variance covariance estimators
• Margins and Marginal effects
• Basic Panel- data estimation concepts
• Moment-based estimation
• Fixed effects model
• Panel data, regression, and efficiency
• Random-effects model
• Comparing and random-effects estimates
• First-differenced estimator
• Choosing between random and fixed effects
• First-differenced estimator
• 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 foe panel data: Radom effects
• Logit models foe panel data: fixed effects
• Logit models foe 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

General Notes

• This course is delivered by our seasoned trainers who have vast experience as expert professionals in the respective fields of practice. The course is taught through a mix of practical activities, theory, group works and case studies.
• Training manuals and additional reference materials are provided to the participants.
• Upon successful completion of this course, participants will be issued with a certificate.