Applied Econometric Policy Evaluation

Course content

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.

Education

MSc programme in Economics – elective course

Bacheloruddannelsen i økonomi – Prioriteret valgfag på 3. år

The Danish BSc programme in Economics - prioritized elective at the 3rd year

Learning outcome

After completing the course, the student should be able to:

Knowledge:

  • 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.

 

Skills:

  • 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.

 

Competences:

  • 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.

 

The course will consist of 17 regular lectures and 4 STATA workshops. Most of
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.

Angrist, J.D. and J.-S. Pischke (2009), “Mostly Harmless Econometrics,” Princeton

University Press .

Journal articles.

Schedule:
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

ECTS
7,5 ECTS
Type of assessment
Written examination, 12 hours
take-home exam. The exam assignment is given in English and must be answered in English.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
External censorship
if chosen by the Head of Studies.
Criteria for exam assessment

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.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 42
  • Preparation
  • 152
  • Exam
  • 12
  • English
  • 206