This is a course in practical application of quantitative methods for doctoral students. The course first introduces methods to collect and store data from existing databases, to generate data by survey approaches and simulation techniques, and to prepare the data for further analysis. Second, it provides theoretical background to analyse data. Third, the course teaches how to use methods from modern empirical tool-boxes to analyse data. Forth, the students applies their skills in quantitative analysis by replicating research from a large number of examples from existing studies, or developing own research-projects. Finally, the course learn the students efficient methods to transform quantita-tive analyses using different statistical softwares to tables, equations and figures in a professional paper.
Course content:
- Dataprocessing
- Introduction to SQL.
- Linear estimation methods.
- Methods for panel dataestimation.
- Instrumental variable regressions.
- Difference-in-difference, matching and event studies.
- Choice modelling using multinomial frameworks.
- Special topics (individual choices).
- Transformation of models, tables and figures into scientific documents.