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Advanced Econometrics - 7,5 ECTS
Date and time
Tuesday 26 April 2022 at 09:00 to Thursday 2 June 2022 at 16:00
Registration Deadline
Tuesday 26 April 2022 at 09:00
Location
Room TBA,
Campus TBA,
2000 Frederiksberg
Room TBA
Campus TBA
2000 Frederiksberg
Advanced Econometrics - 7,5 ECTS
Event Description
| Faculty | ||
| Ralf A. Wilke, Professor, CBS, Department of Economics | ||
Course Coordinator |
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| Ralf A. Wilke, Professor, CBS, Department of Economics, rw.eco@cbs.dk | ||
Prerequisites |
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| 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. |
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Aim |
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| 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. |
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Course content |
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| The course will run on 7 days in the Spring Semester 2022 with 6 hours per day. The first 6 days consists of 4 hours lectures and 2 hours computer sessions, which makes 36 hours. The remaining 6 hours are reserved for student presentations on the last day of the course. In the case of more than 12 participants, an additional contact hour is added per every 2 additional participants to accommodate the additional presentations.
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 Valued Discrete Responses, Continuous Dependent Variables) • Policy Analysis (Regression Based, IPW, Matching, Synthetic Control) • Decomposition Methods (Mean, Distribution) • Duration Models (Single and Competing Risks) A final list of topics will be given during the lectures |
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Teaching style |
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Lectures and computer-based exercise classes. Students need to bring their own laptop.
Face-to-Face teaching with the option to join online (hybrid). Zoom links will be available prior to course start via CBS’s virtual learning environment (Canvas). Software: STATA licenses are available for CBS students. Students from other universities need to have their own license. R is open source.Maximum number of participants: 18 |
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Lecture plan |
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| The course has 36 lectures (à 45 minutes). Lectures take place 6 hours a day on 6 days between 9:00-12:00 and 13:00 and 16:00.
This is followed by at least 6 hours of student presentations on 3.- and possibly more hours on 4. March 2022.
An additional contact hour for every two participants is added if the number of course participants exceeds 12. If the number of participants exceeds 14, the student presentations will take place on two adjacent days (3.-4. March), otherwise on one day only (3. March). This means the minimum number of contact hours is 42. The following tables contain provisional timing of topics with main references. More references will be provided during the course. 26.4.2022 Morning - Intro (1h), Non-semiparametric models (2h) Afternoon - Non-semiparametric models (2h) , Quantile regression (1h) 27.4.2022 Morning - Quantile regression (3h) Afternoon - Resampling methods (3h) 28.4.2022 Morning - Limited Dependent Variable models (3h) Afternoon - Limited Dependent Variable models (3h) 3.5.2022 Morning - Limited Dependent Variable models (2h), Policy analysis (1h) Afternoon - Policy analysis (3h) 4.5.2022 Morning - Policy analysis (3h) Afternoon - Decomposition methods (3h) 5.5.2022 Morning - Duration models (3h) Afternoon - Duration models (2h), QA, Summary & Evaluation (1h) 29.5.2022 9:00 - Project Submission Deadline, by email: rw.eco@cbs.dk 2.6.2022 Whole day - Student presentations, feedback & open discussion – CBS and external students 3.6.2022 Morning - Student presentations, feedback & open discussion – CBS students Topic Main References - Non-semiparametric models - CT2005, Chapter 9 - Quantile regression - CT 2005, Chapter 4.6; W2010, Chapter 12.10 - Resampling methods - CT2005, Chapter 11 - Limited dependent variable models - W2010, Chapters 16, 17, 18.2, 19.2, 19.5 - Policy analysis - W2010, Chapter 21; CT2005, Chapter 25 - Decomposition methods - Fortin, N., Lemieux, T. and Firpo, S. (2011) - Duration models - CT2005, Chapters 17-19; W2010, Chapter 22 |
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Learning objectives |
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Exam |
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| Extended essay (up to 10 pages) and student 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. Grading scale: 7-step scale
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Other |
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Start date |
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| 26/04/2022 | ||
End date |
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| 02/06/2022 | ||
Level |
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| PhD | ||
ECTS |
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| 7.5 | ||
Language |
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| English | ||
Course Literature |
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| This is indicative: • Lecture Notes • Jeffrey Wooldridge (2010), Econometric Analysis of Cross Section and Panel Data, 2nd edition, MIT Press: Cambridge, Mass. • A.Colin Cameron, Pravon Trivedi (2005), Microeconometrics: Methods and Applications, Cambridge University Press. • Academic journal articles on topics taught in the course. Main textbooks: • W2010: Jeffrey Wooldridge (2010), Econometric Analysis of Cross Section and Panel Data, 2nd edition, MIT Press: Cambridge, Mass. • CT2005: A.Colin Cameron, Pravon Trivedi (2005), Microeconometrics: Methods and Applications, Cambridge University Press. |
Event Location
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Organizer Contact Information
CBS PhD School
Nina Iversen
Phone: +45 3815 2475
ni.research@cbs.dk
Registration
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Organizer Contact Information
CBS PhD School
Nina Iversen
Phone: +45 3815 2475
ni.research@cbs.dk