empfohlenes Vorwissen

Knowledge of basic econometric concepts such as communicated in our bachelor and master courses “Einführung in die Ökonometrie" and “Methoden der Ökonometrie“ as well as good working knowledge of mathematical statistics.

Lehrinhalte

• Univariate density estimation
• Multivariate density estimation
• Inference about the density
• Nonparametric regression
• Smoothing discrete variables
• Regression with discrete covariates
• Semiparametric methods
• Instrumental variables

Literaturangaben

• Hayashi, F. (2000). Econometrics. Princeton: Princeton Univ. Press.
• Henderson, D. J.; Parmeter, C. F. (2015). Applied Nonparametric Econometrics. New York: Cambridge University Press
• Li, Q.; Racine, J. S. (2006). Nonparametric Econometrics: Theory and Parctice. Princeton University Press

didaktisches Konzept

Classes are organized around traditional lectures. Students are however expected to contribute intensively through active discussion. Lectures are complemeted via, e.g., illustrations in R, joint interactive programming to better understand the statistical concepts as well as comprehensive problem sets to deepen students’ proficiency.

Hörerschaft

• BWL-EaF-Ma-2015 > Wahlpflichtbereich > (1.-3. Fachsemester, Wahlpflicht) Modul "Nonparametric Econometrics"
• ECMX-Ma-2019 > Wahlpflichtbereich > ME7 Econometric Methods > (1.-3. Fachsemester, Wahlpflicht) Modul "Nonparametric Econometrics"
• GOEMIK-Ma-2016 > Wahlpflichtbereich > Bereich Volkswirtschaftslehre > (1.-3. Fachsemester, Wahlpflicht) Modul "Nonparametric Econometrics"
• MuU-Ma-2013 > Wahlpflichtbereich I > Wahlpflichtbereich I A.: Methodologie und allgemeine Theorien zur Untersuchung von Märkten und Unternehmen > (1.-2. Fachsemester, Wahlpflicht) Modul "Nonparametric Econometrics"
• VWL-Ma-2009-V2013 > Wahlpflichtbereich I > (1.-3. Fachsemester, Wahlpflicht) Modul "Nonparametric Econometrics"