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Course module: 230348-M-3
230348-M-3
Non- and Semiparametric Econometrics (CentER)
Course info
Course module230348-M-3
Credits (ECTS)3
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TiSEM: Econometrics and OR; Econometrics & Operations;
Is part of
M Research Master in Economics
Lecturer(s)
Lecturer
dr. P. Cizek
Other course modules lecturer
Lecturer
prof. dr. J.H.J. Einmahl
Other course modules lecturer
Academic year2019
Starting block
SM 1
Course mode
Full-time
Remarks-
Registration openfrom 19/08/2019 up to and including 24/01/2020
Aims
This course serves as an introduction to nonparametric estimation of the density, distribution, and regression functions and their uses in econometrics. The course consists of two parts: the first part covers various concepts of nonparametric estimation with a special focus on kernel estimation. In the second part, semiparametric estimation using nonparametric estimators as tools for estimating (partially) unknown density or regression functions is discussed. The properties and use of auxiliary nonparametric estimators within least squares, M-estimation, and generalized method of moments are studied theoretically and in the context of typical econometric applications.

Specifics

All non-CentER students should ask formal permission from the Director of Graduate Studies in Economics BEFORE the start of the course.
Please send your request for permission including grade list, CV and motivation letter to CentER Graduate School at center-gs@uvt.nl. Note that asking permission is not just a formality.

Required Prerequisites

A solid background in econometrics and statistics, such as Econometrics 1, 2 and 3 in the CentER Research Master Economics year 1 program
Content
  • Introduction to nonparametric estimation
  • (Kernel) density estimation
  • Nonparametric regression, in particular kernel regression
  • Semiparametric M-estimation and GMM
  • Applications of semiparametric estimators (in linear and nonlinear regression, limited dependent variable models, time series, and panel data)

Type of instructions

lectures

Type of exams

written exam

Recommended Reading
  1. M.P. Wand and M.C. Jones, Kernel Smoothing, Chapman & Hall, London, 1995.
  2. J.L. Horowitz, Semiparametric and Nonparametric Methods in Econometrics, Springer, 2009.
  3. Q. Li and J.S. Racine, Nonparametric Econometrics: Theory and Practice, Princeton University Press, 2006.
  4. A. Pagan and A. Ullah, Nonparametric Econometrics, Cambridge University Press, 1999.
Course available for exchange students
Research Master level, conditions apply
Contact person
prof. dr. J.H.J. Einmahl
Timetable information
Non- and Semiparametric Econometrics (CentER)
Written test opportunities
DescriptionTestBlockOpportunityDate
Written test opportunities (HIST)
DescriptionTestBlockOpportunityDate
Schriftelijk / WrittenEXAM_01SM 1112-12-2019
Schriftelijk / WrittenEXAM_01SM 1217-01-2020
Required materials
-
Recommended materials
-
Tests
Written

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Kies de Nederlandse taal