Econometrics

About the course

Topics

Economics Statistics Quantitative methods

Course content

This course builds on a standard introductory course in econometrics. Students are expected to have knowledge of fundamental concepts in mathematics and statistics and to be familiar with matrix notation.

The aim of the course is to develop both a theoretical and applied understanding of econometric models and estimation methods. The course emphasizes what can and cannot be concluded from empirical analysis, how to identify limitations and potential shortcomings of different approaches, and how to distinguish between causal and non-causal relationships. Students will learn to assess plausible identification strategies for causal inference given the available data and its constraints.

The course covers both cross-sectional and panel data, with applications involving continuous and binary dependent variables.

Each topic is introduced in technical terms and followed by exercises and applied examples. Lectures combine traditional instruction with short individual or group exercises to reinforce key concepts. Exercise sessions provide opportunities for more in-depth practice on problems not covered in lectures, with students working individually or in groups, followed by class discussions and explanations.

See the full course description in the course catalogue

What you learn

Define and interpret key econometric concepts, including estimator, estimation, estimate, identification, and causality, and explain their roles in empirical analysis
Identify key challenges to causal inference in a given research setting (e.g., omitted variables, selection bias, reverse causality), and evaluate the strengths, limitations, and feasibility of alternative identification strategies given the available data.
Select and justify an appropriate econometric model and identification strategy for a specific research question, taking into account data limitations and the assumptions required for causal interpretation.
Estimate econometric models using STATA, ensuring correct implementation of commands and procedures.
Interpret and evaluate estimation results from STATA output, including coefficients, standard errors, statistical significance.
Link econometric theory to practice by clearly connecting model assumptions, STATA code, and empirical results.
Present empirical findings clearly and appropriately, assessing whether results are reported and communicated in a meaningful way.

Course prerequisites

This is a mandatory course for the MSc in Advanced Economics and Finance. It is assumed that students have knowledge similar to the entry requirements for this programme. The course has 60 contact hours and there is a high level of interaction betw. lecturer and students, and in general a high work load. The course has a high technical level and is intended for OECON students. Students are required to have the knowledge of the content of the introductory econometrics course "BA-BHAAI1108U Introduction to Econometrics with R" or equivalent. This includes that basic tools and fundamentals of mathematics and statistics are already known to students (Compare Appendices A-D in Wooldridge, 2020, Introductory Econometrics, 7th Edition, Cengage ). To sign up send a 1-page motivational letter and a grade transcript to ily.stu@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https://studentcbs.sharepoint.com/sites/ChoicesAndOptions/SitePages/en/Registration-for-electives.aspx ) Please also remember to sign up through the online registration.

Facts

Level

Master

Type

Mandatory course – also offered as elective

ECTS

7.5

Course code

CEADO1004U

Teaching periods

Autumn – semester

Academic year

2026/2027

Teaching language

English

Teaching Format

Hybrid

Exams

Written exam on campus
Individual exam, autumn
Written exam on campus
Individual exam, winter

Assessment

7 point grading scale