Empirical Strategies

ECS548 Empirical Strategies

  • Topics

    Topics

    Topics to be covered include the construction and interpretation of regression and instrumental variables estimates, differences-in-differences identification strategies, and regression discontinuity methods.

  • Learning outcome

    Learning outcome

    Empirical Strategies is a short course that introduces PhD students to cutting-edge empirical strategies for causal inference. A close understanding of these methods is central to current empirical work in economics but also in business, finance, political science and sociology. Advanced theoretical frameworks will be illustrated throughout the course with recent applications. 

    Upon successful completion of this course the participants should be able to

    • demonstrate a firm grasp of the relevant literature and state of the art thinking in this area
    • are able to independently estimate causal effects and understand the assumptions necessary to estimate causal effects

  • Teaching

    Teaching

    5 lectures, lab sessions and a seminar presentation.

  • Required prerequisites

    Required prerequisites

    Successful completion of an econometrics course at least at the master level.

  • Requirements for course approval

    Requirements for course approval

    Participation and approved paper (maximum 15 pages) on a relevant topic.

  • Assessment

    Assessment

    Approved paper (maximum 15 pages) on a relevant topic.

  • Grading Scale

    Grading Scale

    Grading: Pass / fail

  • Computer tools

    Computer tools

    STATA

  • Semester

    Semester

    Autumn 2014: Intensive PhD course August 18-21

  • Literature

    Literature

    J.D. Angrist and J.S. Pischke, Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press, 2009.

    Additional readings will be announced later.

Overview

ECTS Credits
5
Teaching language
English
Semester
Autumn

Course responsible

Kjell G. Salvanes and Aline Bütikofer Lecturer: Josh Angrist, MIT