040161 UK Nonparametric and semiparametric Methods of Econometrics (2016S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from We 17.02.2016 09:00 to We 24.02.2016 12:00
- Deregistration possible until Mo 14.03.2016 23:59
Details
max. 35 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
- Monday 07.03. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 14.03. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 04.04. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 11.04. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 18.04. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 25.04. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 02.05. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 09.05. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 23.05. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 30.05. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 06.06. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 13.06. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 20.06. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 27.06. 18:30 - 20:00 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Thursday 30.06. 15:00 - 16:30 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
The course will introduce nonparametric kernel methods to estimate density and regression functions in an iid setting. The basic asymptotic properties of our estimators will be derived.Furthermore we will discuss issues such as bandwidth selection and the curse of dimensionality.Time permitting we will also look at extensions such as alternative estimators (sieves), additive models, semiparametric models, endogeneity problems, dependent data or the bootstrap. For the extensions we will not deal with the theory in the same detail as for the kernel methods for density and regression function estimation.
Assessment and permitted materials
The assessment details have not been finalized yet. However, they will be communicated before the students are asked to complete a task that will count towards their final grade. Thus, they will have the chance to quit the course without receiving a grade.Depending on the size of the course the assessment will be based on a combination of homeworks and possibly at least one exam. Furthermore, I may decide to do some "inverted classroom lite", i.e. the students will be given material which they should work through independently and then present the results.
Minimum requirements and assessment criteria
Examination topics
- Kernel methods for estimation of density and regression functions and their asymptotic properties.
- Bandwidth Selection.
- Extensions as mentioned above.
- Bandwidth Selection.
- Extensions as mentioned above.
Reading list
Nonparametric Econometrics: Theory and Practice :: Qi Li und Jeffrey S. Racine (2007) :: Princeton University Press.
Association in the course directory
Last modified: Mo 07.09.2020 15:28