Login for PhD students/staff at UCPH      Login for others
Advanced Applied Econometrics: Causal Inference with Observational Data
Provider: Faculty of Science

Activity no.: 5226-18-03-31There are no available seats 
Enrollment deadline: 01/05/2018
Date and time14.05.2018, at: 09:00 - 18.05.2018, at: 16:00
Regular seats25
Course fee1,000.00 kr.
LecturersArne Henningsen
ECTS credits5.00
Contact personArne Henningsen    E-mail address: arne@ifro.ku.dk
Enrolment Handling/Course OrganiserCharlotte Bukdahl Jacobsen    E-mail address: cja@ifro.ku.dk
Written languageEnglish
Teaching languageEnglish
Exam formWritten assignment
Grading scalePassed / Not passed
Course workload
Course workload categoryHours
Preparation / Self-Study25.00


Social science researchers are usually interested in investigating causal relationships. The analysis
of causal relationships is generally easiest based on experimental data. The use of experiments in
social sciences, however, has many limitations, and most empirical studies are based on
observational (i.e., nonexperimental) data. The participants of this course will learn the theory and
practice of state-of-the-art empirical approaches used for investigating causal relationships with
observational data. The course participants will also learn how to evaluate and discuss the
appropriateness of identification strategies for analysing causal relationships and to choose the
most appropriate identification strategy for analysing a specific research question. All this will help
the participants obtain more credible and reliable results in their empirical work and to publish their
work in better journals.

Learning outcome
After having completed the course, the course participants will know state-of-the-art statistical and
econometric methods for causal inference with observational data, and they will be able to apply
these methods to investigate causal relationships based on observational data. The participants
will also be able to evaluate and discuss the appropriateness of identification strategies and they
will be able to choose an appropriate identification strategy for a specific research question.

- Bellemare, Marc F. (2018), The Craft of Econometrics , unpublished lecture notes.
- Angrist, J.D. and Pischke, J.S. (2009), Mostly Harmless Econometrics: An Empiricist's Companion. Princeton university press.
- Excerpts from various econometrics textbooks.
- Various articles in scientific journals.

Teaching and learning methods
The theory will be taught mostly through (interactive) lectures, dialogue teaching, and self-study.
The practice will be taught mostly through exercises, group work, self-study, and the exam (i.e.,
conducting econometric/statistical analyses and writing a report, see following section).

Exam form and criteria for assessment:
The exam consists of a brief report about a statistical or econometric analysis (maximum five
pages) each participant has to write and send to the course organiser no later than two months
after the end of the course. The participants need to find a suitable research question and data set
for their analyses themselves. The research question needs to be within the social sciences and
needs to address a causal relationship. The data set needs to contain observational (i.e.,
nonexperimental) data. It is encouraged that the research question and data set are parts of the
participants’ PhD projects. In their reports, the participants need to state their research question,
describe their data, methodology, model specification and results, discuss the appropriateness of
their identification strategy, and derive conclusions based on their empirical analysis. A participant
passes the exam if his/her report indicates that he/she has obtained the intended learning outcome
(see section “learning outcome”).

Preparation and self-study:
Participants are expected to prepare for the course by reading the course material (mostly extracts
from textbooks and journal articles) that will be sent to the students about 4 weeks before the
course starts. It is also expected that the participants recapitulate the contents of the course by
reviewing the lecture notes and the other course material in order to appropriately conduct the
analyses and write their report for the exam.

- Marc F. Bellemare (Department of Applied Economics, University of Minnesota)
- Arne Henningsen (Department of Food and Resource Economics, University of Copenhagen)

Coffee, tea, and lunch is provided at each of the five teaching days. Dinner is provided at one of
the teaching days. Participants need to find accommodation themselves.

Click the search button to search Courses.

Course calendar
See which courses you can attend and when

Publication of new courses
All planned PhD courses at the PhD School are visible in the course catalogue. Courses are published regularly.