This course introduces the microeconometric methods needed for the analysis of cross-sectional and panel data and teaches the application of these methods and the programming of the respective estimators using the econometric software STATA. The goal of the course is to be able to read and understand more advanced methods in microeconometric research and to evaluate the output of academic articles using microeconometric methods. In addition, the students should be equipped to untertake their own microeconometric analyses.
The course will be offered in the summer term 2020.
• Reviewing basic methods
– OLS: estimation, inference and model specification
– Heteroscedasticity and endogeneity
• Linear panel data models
– Pooled ordinary least squares
– Random effects (RE) estimation
– Fixed effects (FE) estimation
– First-difference (FD) estimation
• Nonlinear panel data models
– Maximum likelihood (ML) estimation
– Binary response models (LPM, Logit, Probit)
– Corner solutions (Tobit)
– Censored and selected data (Heckman)