835833

Ralf A. Wilke, Professor, CBS, Department of Economics, rw.eco@cbs.dk

Estimation of and Inference for the multiple regression model (OLS, 2SLS, LPM, F-,t-,LR-,Wald-, LM-tests), Maximum Likelihood Estimation, Regression with Binary Dependent Variable, Matrix Algebra, Basic concepts of asymptotic theory (consistency and asymptotic normality). The course is compulsory for the PhD students of Copenhagen Business School’s Department of Economics, but also open to other PhD students who have the equivalent knowledge in econometrics of an M.Sc. in Economics or Econometrics.

After the course, students shall be able to:

• demonstrate knowledge of the concepts, models, methods and tools of econometrics as discussed during the course (when to apply what and why) ,
• read and understand international research papers that develop or employ econometric methods,
• perform an econometric analysis including identification of the problem, formulation of the theoretical background, specification of a suitable econometric model, proper estimation of the model , and relevant hypothesis testing and inference,
• and to evaluate an empirical study conducted by another person/researcher.

Designed for PhD students in Economics and related disciplines who want to deepen their understanding of econometrics and widen their statistical methods repertoire for their thesis and later career. The material is useful for students doing empirical work, research on Econometrics or both. The course covers general econometric methods and methods for cross section data. Topics are illustrated in lectures by empirical examples and sample Stata sample code is made available. Students will be offered the opportunity to deepen their understanding of the material during a number of computer classes. The course is centered around topics which should be of interest to a wider audience, rather than focusing on very specialized topics. An introduction to Stata will be provided.

Topics covered by the course include:

General Econometrics:

• Nonparametric Density and Regression, Semiparametric Regression
• Quantile Regression
• Resampling techniques

Cross Section Econometrics:

• Limited Dependent Variable models (Multiple Responses, Continuous Dependent Variables)
• Policy Analysis (Regression Based, Matching)
• Decomposition Methods (Mean, Distribution)
• Duration Models (Single and Competing Risks)

A final list of topics will be given during the lectures.

Lectures and computer-based exercise classes. Students need to bring their own laptop.

Tuesday: 31/1, 7/2

Wednesday: 1/2, 8/2

Thursday: 2/2, 9/2, 2/3

Extended essay (up to 10 pages) and presentation (20 minutes+ 10 minutes discussion) on a topic related to the course content. The topic is chosen by the student and needs approval by the lecturer.

7-step scale

Copenhagen Business School
Department of Economics
Porcelænshaven 16 A, Room PH2.80
Fredriksberg, Denmark