Course Schedule


Applied Causal Analysis using Stata (Seminar)

Dozent/in: Boris Hirsch

wöchentlich | Donnerstag | 08:15 - 11:45 | 16.10.2023 - 02.02.2024 | C 6.317 Seminarraum | Start 1. lecture week

Inhalt: This course covers essential methods used in applied causal analysis: 1. Causal analysis of experimental data 2. Probability models for binary outcomes 3. Instrumental variables estimation 4. Fixed-effects estimation on panel data 5. Differences-in-differences estimation In the first step, the course introduces each method focussing on its correct implementation and interpretation. In the second step, each method is applied to a specific research question from empirical economics using real-world data sets and Stata: 1. Effect of class size on student achievement 2. Discrimination against black job applicants 3. Rate of return to education 4. Effect of wages on individual labour supply 5. Effect of police presence on crime

Theorie und Empirie der Lohnstruktur und Jobzufriedenheit (Seminar)

Dozent/in: Christian Pfeifer

wöchentlich | Donnerstag | 12:15 - 15:45 | 16.10.2023 - 02.02.2024 | C 1.005 Seminarraum | Beginn 1. Vorlesungswoche

Inhalt: This course gives students the chance to conduct own empirical research with real microdata by using their prior knowledge from courses in the Economics Major (e.g., Microeconomics, Labor Economics, Orientation in Economics, Econometrics). It starts with a brief introduction and overview of relevant theories from labor economics including human capital theory and discrimination theories. The course further comprises a short introduction to applied econometrics, earnings functions, happiness research, and job satisfaction as well as Stata applications for estimating earnings functions using the VSE data set and estimating job satisfaction using the ALLBUS data set. Students also have to work at home through textbook Stata commands and applications and should estimate earnings functions and job satisfaction equations on their own using the supplied VSE and ALLBUS. The second part of the course is devoted to own empirical research of students, in which they can choose own topics when estimating earnings functions or job satisfaction with Stata. Students have to give a short presentation of their own research idea, write an own empirical paper, and give a final presentation with their results. These three assignments will be graded in the combined examination.