Become an expert in the analysis and implementation of linear,
nonlinear, and dynamic panel-data estimators using Stata. This course
focuses on the interpretation of panel-data estimates and the
assumptions underlying the models that give rise to them. The course is
geared for researchers and practitioners in all fields. The breadth of
the lectures will be helpful if you want to learn about panel-data
analysis or if you are familiar with the subjects.
Course content of NetCourse 101 or equivalent knowledge
Familiarity with basic time-series, cross-sectional summary statistics and linear regression
Internet web browser, installed and working (course is platform independent)
Course content
Expand all sections
Lesson 1
An introduction to panel data and its features
Getting started with panel data
Summary statistics and dynamics
Overview of basic concepts
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
Closing remarks
Lesson 2
Random-effects model
The model
Fixed-effects model
Within estimator
Comparing within and random-effects estimates
First-differenced estimator
Deciding between random and fixed effects
Hausman test
Mundlak test
Population-averaged models
Lesson 3
Probit model
Probit models for panel data: Random effects
Probit models for panel data: Population averaged
Probit models for panel data: Remarks
Logit model
Logit models for panel data: Random effects
Logit models for panel data: Fixed effects
Logit models for panel data: Population averaged
Poisson model
Poisson models for panel data
Lesson 4
Endogeneity
Cross-sectional estimation under endogeneity
Panel-data estimation under endogeneity
Dynamic models
Building your own dynamic models
A more complex dynamic structure
Concluding remarks
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$495.00
Self-paced
