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Module (6 Credits)

Nonparametric Econometrics

Name in diploma supplement
Nonparametric Econometrics
Responsible
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 EaFWahlpflichtbereich1st-3rd Sem, Elective
  • ECMXWahlpflichtbereichME7 Econometric Methods1st-3rd Sem, Elective
  • GOEMIKWahlpflichtbereich Bereich Volkswirtschaftslehre1st-3rd Sem, Elective
  • MuUWahlpflichtbereich IWahlpflichtbereich I A.: Methodologie und allgemeine Theorien zur Untersuchung von Märkten und Unternehmen1st-2nd Sem, Elective
  • VWLWahlpflichtbereich I1st-3rd Sem, Elective
Elements
Name in diploma supplement
Nonparametric Econometrics
Organisational Unit
Lecturers
SPW
2
Language
English
Cycle
irregular
Participants at most
no limit
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.

Participants
Lecture: Nonparametric Econometrics (WIWI‑C1204)
Name in diploma supplement
Nonparametric Econometrics
Organisational Unit
Lecturers
SPW
2
Language
English
Cycle
irregular
Participants at most
no limit
Preliminary knowledge

see lecture

Contents

see lecture

Literature

see lecture

Participants
Exercise: Nonparametric Econometrics (WIWI‑C1207)
Module: Nonparametric Econometrics (WIWI‑M0940)