Designed for PhD students in Economics and related disciplines who want to deepen their understanding of econometrics and widen their statistical methods repertoire for their thesis and later career. The material is useful for students doing empirical work, research on Econometrics or both. The course covers general econometric methods and methods for cross section data. Topics are illustrated in lectures by empirical examples. Stata and R sample code is made available. Students will be offered the opportunity to deepen their understanding of the material during a number of computer classes. The course is centered around topics which should be of interest to a wider audience, rather than focusing on very specialized topics. An introduction to Stata will be provided.
Topics covered by the course include:
- Nonparametric Density and Regression, Semiparametric Regression
- Quantile Regression
- Resampling techniques
Cross Section Econometrics:
- Limited Dependent Variable models (Multiple Valued Discrete Responses, Continuous Dependent Variables)
- Policy Analysis (Regression Based, IPW, Matching, Synthetic Control)
- Decomposition Methods (Mean, Distribution)
- Duration Models (Single and Competing Risks)
A final list of topics will be given during the lectures.
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