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Event
Non- and Semiparametrics [WS192521300]
Lecturers
Organisation
- KIT-Fakultät für Wirtschaftswissenschaften
Part of
- Brick Non- and Semiparametrics | Industrial Engineering and Management (M.Sc.)
- Brick Non- and Semiparametrics | Economics Engineering (M.Sc.)
- Brick Non- and Semiparametrics | Information Systems (M.Sc.)
- Brick Non- and Semiparametrics | Information Engineering and Management (M.Sc.)
- Brick Non- and Semiparametrics | Economathematics (M.Sc.)
Literature
Li, Racine: Nonparametric Econometrics: Theory and Practice. Princeton University Press, 2007.
Appointments
- 16.10.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 23.10.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 30.10.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 06.11.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 13.11.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 20.11.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 27.11.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 04.12.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 11.12.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 18.12.2019 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 08.01.2020 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 15.01.2020 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 22.01.2020 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 29.01.2020 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
- 05.02.2020 11:30 - 13:00 - Room: 10.91 Oberer Hörsaal Maschinenbau
Note
Learning objectives:
The student
- has profound knowledge of non- and semiparametric estimation methods
- is capable of implementing these methods using statistical software and using them to assess empirical problems
Content:
Kernel density estimation, local constant and local linear regression, bandwidth choice, series and sieve estimators, additive models, semiparametric models
Requirements:
It is recommended to attend the course Applied Econometrics prior to this course.
Workload:
Total workload for 4.5 CP: approx. 135 hours
Attendance: 30 hours
Preparation and follow-up: 65 hours
Exam preparation: 40 hours