Panel Data Analysis Essential Training
1h 37mAdvanced2023-03-28
Authors

Franz Buscha
Professor of Economics at the University of Westminster
Course details
Panel data is among the most complex data sources available to data analysis scientists. Analyzing such data requires an understanding of a new class of models that go beyond traditional linear regression techniques. In this course, professor of economics Franz Buscha introduces you to such models and highlights how and when to use them. Franz covers best practices, basic panel data setup, descriptive analysis, and advanced modeling techniques. He explains each topic theoretically and shows you a simple practical example. Franz goes over common panel data models, including FE and RE estimation, and explores advanced panel data techniques, such as Mundlak, dynamic, and nonlinear models.
Skills covered
Data AnalysisEssential TrainingData ScienceBusiness Analysis and StrategyBusiness Software and Tools
Concepts
0. Introduction
- 01 - How panel data makes a difference
- 02 - What you should know
1. Panel Data
- 03 - What is panel data
- 04 - Advantages of panel data
- 05 - Disadvantages of panel data
- 06 - Types of panel data
2. Panel Data Management
- 07 - Long vs. wide form
- 08 - Appending and merging
3. Describing Panel Data
- 09 - Describing panel data
- 10 - Overall, between, and within summaries
- 11 - Transition summaries
4. Linear Models
- 12 - Error component models
- 13 - Pooled OLS models
- 14 - Fixed effect models
- 15 - Random effect models
- 16 - Multilevel models
- 17 - Fixed or random effects
- 18 - Mundlak correction
5. Other Models
- 19 - Nonlinear models
- 20 - Dynamic models
Conclusion
- 21 - Next steps and additional resources