Nonparametric Econometrics

Module: Nonparametric Econometrics (6 Credits)
Name in diploma supplement	Nonparametric Econometrics
Responsible	Prof. Dr. Christoph Hanck
Admission criteria	See exam regulations.
Workload	180 hours of student workload, in detail: Attendance: 60 hours Preparation, follow up: 60 hours Exam preparation: 60 hours
Duration	The module takes 1 semester(s).
Qualification Targets	Students acquire broad knowledge of modern nonparametric methods from both statistics and econometrics are proficient to use these to empirically investigate topics in economics and related fields gather and process data to do so critically comment on published empirical findings as well as on limitations of own analyses can assess and formally demonstrate the theoretical properties of the most central methods independently apply and extend statistical software to practically conduct empirical work solve suitable methodological problem sets
Relevance	The practical relevance of the module is high in view of the key and increasing importance of empirical work in economics and elsewhere.
Module Exam	Examination for this module takes place through a written exam (typically 60-90 minutes), or an oral exam (typically 20-40 minutes), or an empirical project (70% of the final grade) combined with a presentation (typically 20 minutes, 30% of the final grade). The type of examination will be communicated at the start of the semester.
Usage in different degree programs	BWL EaF Master > Wahlpflichtbereich > 1.-3. Sem, Elective ECMX Master > Wahlpflichtbereich > ME7 Econometric Methods > 1.-3. Sem, Elective GOEMIK Master > Wahlpflichtbereich > Bereich Volkswirtschaftslehre > 1.-3. Sem, Elective MuU Master > Wahlpflichtbereich I > Wahlpflichtbereich I A.: Methodologie und allgemeine Theorien zur Untersuchung von Märkten und Unternehmen > 1.-2. Sem, Elective VWL Master > Wahlpflichtbereich I > 1.-3. Sem, Elective
Elements	Lecture Nonparametric Econometrics (3 Credits) Exercise Nonparametric Econometrics (3 Credits)
Module: Nonparametric Econometrics (WIWI‑M0940)

Lecture: Nonparametric Econometrics (3 Credits)
Name in diploma supplement	Nonparametric Econometrics
Organisational Unit	Lehrstuhl für Ökonometrie
Lecturers	Prof. Dr. Christoph Hanck, Prof. Dr. Yannick Hoga
Hours per week	2	Language	English
Cycle	irregular	Participants at most	###LABEL_NOLIMIT###
Preliminary knowledge 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.
Contents Univariate density estimation Multivariate density estimation Inference about the density Nonparametric regression Smoothing discrete variables Regression with discrete covariates Semiparametric methods Instrumental variables
Literature 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
Teaching concept 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.
Lecture: Nonparametric Econometrics (WIWI‑C1204)

Exercise: Nonparametric Econometrics (3 Credits)
Name in diploma supplement	Nonparametric Econometrics
Organisational Unit	Lehrstuhl für Ökonometrie
Lecturers	Prof. Dr. Christoph Hanck, wissenschaftliche Mitarbeiter(innen)
Hours per week	2	Language	English
Cycle	irregular	Participants at most	###LABEL_NOLIMIT###
Preliminary knowledge see lecture
Contents see lecture
Literature see lecture
Exercise: Nonparametric Econometrics (WIWI‑C1207)