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2025/2026  KAN-CMECV1702U  Cross Section and Panel Econometrics

English Title
Cross Section and Panel Econometrics

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 30
Max. participants 80
Study board
Study Board of Finance, Economics & Mathematics
Course coordinator
  • Ralf Andreas Wilke - Department of Economics (ECON)
Main academic disciplines
  • Mathematics
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Face-to-face teaching
Last updated on 25-02-2025

Relevant links
Learning objectives
  • Detect situations in which the ordinary least squares estimator is not adequate and be able to explain why.
  • Understand econometric methods of estimation and inference for cross section data and panel data.
  • Understand proofs and derivations in matrix notation.
  • Choosing an econometric model, form those introduced in the course, and explaining why it is the suitable model for the specific situation
  • Interpret estimation results in R/STATA output correctly and comment on appropriateness of their presentation.
  • Relate R/STATA code and R/STATA output to the econometric models introduced in the course
  • Competence in R or STATA to do econometric analysis with the introduced models of the course.
Course prerequisites
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. A good preparation of the course are the courses Økonometri (BA-BMECV1031U) or Econometrics (KAN-CEADO1004U).
Knowledge of matrix algebra, fundamentals of probability and mathematical statistics are required.
Basic knowledge of either R or STATA.
Examination
Cross Section and Panel Econometrics:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
The main textbody must not exceed 10 pages and should contain main result tables and figures which are required for the understanding of the main text. References and appendices with additional material (additional results or figures, code or proofs/derivations) do not count for the page limit but should not be too excessive.
Assignment type Project
Release of assignment Subject chosen by students themselves, see guidelines if any
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

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.
Research-based teaching
CBS’ programmes and teaching are research-based. The following types of research-based knowledge and research-like activities are included in this course:
Research-based knowledge
  • Classic and basic theory
  • Methodology
  • Models
Research-like activities
  • Development of research questions
  • Analysis
  • Discussion, critical reflection, modelling
  • Studerende udfører selvstændige forskningslignende aktiviteter uden vejledning
Description of the teaching methods
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 during the teaching period
1) Office hours.
2) Computer classes: students are encouraged to present their solutions to problem sets to receive formative feedback.
Student workload
Lectures 33 hours
Preparation 87 hours
Project 86 hours
Expected literature

Lectures:

Lecture notes.
Selected scientific articles to be specified during the course.
  

Further recommended readings, revision material and articles will be posted on Canvas.

 

Main Textbook:
Wooldridge (MIT, 2010) "Econometric Analysis of Cross Section and Panel Data"

 

Additional textbooks:
Cameron and Trivedi (Cambridge, 2005) "Microeconometrics".

 

Croissant and Millo (Wiley, 2018) "Panel Data Econometrics with R".

 

Hansen (Princeton, 2022) "Econometrics".
Last updated on 25-02-2025