MWiWi 4.8 Microeconometrics
Prof. Dr. Uta Pigorsch / Prof. Dr. Hendrik Jürges
This module consists of two components, which are both required for a successful completion of this module:
a) Econometrics of Panel Data and Limited Dependent Variables (contact person: Prof. Dr. Uta Pigorsch – Chair of Economic Statistics & Econometrics)
Empirical economic research has become an important part of Economics and Business Administration. To answer empirical questions, a profound knowledge of the corresponding statistical methods and models is essential. This course offers an in-depth discussion of the fundamental multiple linear regression model, the prevalent problem of endogeneity and solutions thereof, as well as the main estimation and inference methods for analyzing panel data and limited dependent variables, such as discrete choice data (e.g. whether a person is employed or unemployed), count data (e.g. the number of car traffic deaths or the number of demanded health care services) and durations (e.g. duration of unemployment, life expectation).
Familiarity with the simple linear regression model on the level of an undergraduate course in Econometrics is recommended.
Alternatively, the Refresher Course in Basic Statistics and Econometrics can be attended, which is offered as a block course at the beginning of the semester.
Course language: English
b) Causal Inference and Research Design (contact person: Prof. Dr. Hendrik Jürges - Chair of Health Economics and Management)
Most economic and social policy questions can only be answered in a fruitful manner by causal analyses, i.e. by answering “what if” questions. This course introduces the counterfactual causal model as the leading conceptual framework to understand and analyze causal questions as well as the related core methods of applied microeconometrics: multiple regression, matching, instrumental variables, differences-in-differences, and regression discontinuity designs.