2024/2025 KAN-CMECV1702U Cross Section and Panel Econometrics
English Title | |
Cross Section and Panel Econometrics |
Kursusinformation |
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Sprog | Dansk |
Kursets ECTS | 7,5 ECTS |
Type | Valgfag |
Niveau | Kandidat |
Varighed | Et semester |
Starttidspunkt | Efterår |
Tidspunkt | Skemaet bliver offentliggjort på calendar.cbs.dk |
Min. antal deltagere | 30 |
Max. antal deltagere | 80 |
Studienævn |
MEC Studienævnet for HA/cand.merc. i erhvervsøkonomi og
matematik, MSc
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Kursusansvarlig | |
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Primære fagområder | |
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Undervisningsformer | |
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Sidst opdateret den 25-01-2024 |
Relevante links |
Læringsmål | ||||||||||||||||||||||||||
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Forudsætninger for at deltage i kurset | ||||||||||||||||||||||||||
The course has a high technical level. Students
are expected to have knowledge of the statistical properties of
ordinary least squares estimation and maximum likelihood
estimation, as well as hypotheses tests about parameters in
regression analysis.
Knowledge of matrix algebra, fundamentals of probability and mathematical statistics are required. Basic knowledge of either R or STATA. |
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Prøve/delprøver | ||||||||||||||||||||||||||
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Kursets indhold, forløb og pædagogik | ||||||||||||||||||||||||||
Topics in Cross Section Econometrics: We consider various violations of common model assumptions (such as Gauss-Markov assumptions), including heteroskedasticity, auto/serial correlation, omitted variables, functional form misspecification, measurement error and simultaneity. We see how this can be tested for and what solutions exist (e.g. robust inference statistics, (F)GLS, IV/2SLS methods). We then consider crafting and estimation of a system of equations including simultaneous equations and seemingly unrelated regression by 2SLS/3SLS and GMM.
Topics in Panel Models: We start with the main static linear panel models: Pooled OLS, FE,RE,FD. We then combine common static linear panel models with IV methods (FD-IV, FE-IV and RE- IV, Hausman-Taylor type models). We consider dynamic panel models (Anderson-Hsiao/ System 2SLS, Arrelano-Bond/ GMM) before we move to nonlinear panel models (binary dependent variable only). Here we extend ML estimation to cope with dependent observations (using Kullback-Leibler Information criterion) and consider methods to correct estimated standard errors and statistics. The final point will be to consider panel attrition/unbalanced panels, if time permits.
The econometric theory is illustrated with data examples throughout the course. Sample code for R and Stata is provided and students can choose whether they work with R or Stata. |
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Beskrivelse af undervisningsformer | ||||||||||||||||||||||||||
The course comprises of 25 hours of lectures and 8 hours of computer classes. The first computer class is an introductory class. The following classes cover problem sets with mainly empirical questions to practice the work on the computer and interpretation of results. There are also theoretical questions to deepen the understanding of the derivation of statistical properties of estimators and the role of model assumptions. | ||||||||||||||||||||||||||
Feedback i undervisningen | ||||||||||||||||||||||||||
1) Office hours.
2) Computer classes: students are encouraged to present their solutions to problem sets to receive formative feedback. |
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Studenterarbejdstimer | ||||||||||||||||||||||||||
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Foreløbig litteratur | ||||||||||||||||||||||||||
Lectures:
Further recommended readings, revision material and articles will be posted on Canvas.
Textbooks:
Croissant and Millo (Wiley, 2018) "Panel Data Econometrics with R". |