AØKA08225U Applied Econometric Policy Evaluation
The aim of the course is to develop knowledge, skills and competences that enable students to provide answers to real applied econometric problems rather than just econometric theory, and in this way prepare students to carry out their own empirical analyses.
The course is divided into four blocks. In the first block, the counter-factual setup is introduced and natural experiments and methods assuming unconfoundedness are considered. In the second block, methods based on the availability of panel data are considered. These lectures focus on the difference-in-differences estimator and event studies. Furthermore, since the usual standard errors of panel data estimates are likely to be seriously biased, one lecture will be devoted to consider how to obtain correct (clustered) standard errors. In the third block, regression discontinuity and regression kink designs are dealt with. Finally, in the fourth block methods using instrumental variables are considered. Each of the four blocks will be concluded by a workshop, where the students will get hands-on experience in how to apply the methods.
After completing the course, the student should be able to:
- be introduced to the counterfactual set-up and the key treatment parameters we seek to estimate.
- Understand how the estimated treatment parameters rely on specific identifying assumptions.
- have learned a list of research designs that have been used in the literature.
- Understand how arguments in favor of a research design are developed in research articles.
- Set-up appropriate evaluation designs matching specific empirical applications.
- Discuss the identifying assumptions and use regressions or descriptive data analysis to assess the assumptions.
- Implement an empirical policy evaluation analysis using Stata.
- Formulate an empirical research question.
- Develop a policy evaluation research design.
- Identify how to exploit variation induced by a policy to set-up a credible research design.
- Apply the appropriate econometric techniques to the policy evaluation problems using micro data.
- Develop arguments supporting an identification strategy.
- Assess the identification strategies in existing research papers as well as in their own analyses.
Angrist, J.D. and J.-S. Pischke (2009), “Mostly Harmless Econometrics,” Princeton
University Press .
the necessary econometric theory being taught in the lectures will draw on the
Angrist and Pischke (2009) textbook. Besides teaching the econometric theory,
an important part of the lectures is devoted to considering how to apply the
methods taught to real policy evaluation problems. Teaching how to develop
appropriate research designs will be case-based drawing on examples from
development economics, health economics, labor economics, the economics of
education, tax policy, and public economics. The course will thus be
complementary to many of the other course in the economics programme.
2 hours lectures 1 to 2 times a week from week 6 to 20 (except holidays).
Timetable and venue:
The schedule for the semester spring 2018 will be available no later than 7th of November 2017
Registration and information for students not enrolled please find more information at Study Economics.
- 7,5 ECTS
- Type of assessment
- Written examination, 12 hourstake-home exam. The exam assignment is given in English and must be answered in English.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
if chosen by the Head of Studies.
- Exam period
The schedule for the exam 2018 will be available no later than 7th of November 2017
The schedule for the reexam 2018 will be available no later than 7th of November 2017
If only a few students have registered for the re-exam, the exam might change to an oral exam including the date, time and place for the exam, which will be informed by the Examination Office.
Criteria for exam assesment
Students are assessed on the extent to which they master the learning outcome for the course.
To receive the top grade, the student must be able to demonstrate in an excellent manner that he or she has acquired and can make use of the knowledge, skills and competencies listed in the learning outcomes.