PhD Econometrics II

ECS509 PhD Econometrics II

Autumn 2021

  • Topics

    This is the second of the two courses in econometrics in the PhD program in economics. The goal of the course is to make students familiar with econometric techniques at an advanced level. The course provides a deeper understanding of modern econometric methods that are applied in many fields of economics. The course also puts strong emphasis on practical empirical exercises. The students train at critically assessing studies, but also in doing advanced empirical studies with data that are provided in class. We cover identification, randomization, causal inference, instrumental variables, difference-in-differences, regression discontinuity, and matching methods. We also cover a number of more specialized applied topics such as bad controls, measurement error, and clustering. 

  • Learning outcome

    Upon completion of the course, the students will be able to:

    Knowledge:

    • Identify and understand [explain or discuss?] the standard identification strategies in research papers

    Skills:

    • Calculate standard estimators and corresponding standard errors
    • Discuss inferential issues with dependent data

    General competencies:

    • Use available software to estimate standard models on real world data
    • Evaluate alternative identification strategies

  • Teaching

     Lectures and assignments. Due to the current pandemic, the lectures will be filmed and/or streamed.

  • Recommended prerequisites

    ECS508.

  • Required prerequisites

    ECS508.

  • Requirements for course approval

    Approved referee assignment and class participation. 

  • Assessment

    Group-based replication project.

    Group size: 2.

    Scope: 4000 words maximum.

    The assignment will be distributed in January. The submission deadline will be in April. 

  • Grading Scale

    Pass/Fail.

  • Literature

    In addition to selected papers provided on canvas, there is one textbook:

    Angrist and Pischke (2009). Mostly Harmless Econometrics: An Empiricist's Companion, Princeton, NJ: Princeton University.

Overview

ECTS Credits
7.5
Teaching language
English.
Semester

Spring. Offered spring 2021.

Course responsible

Assistant Professor Alexander Willén, Department of Economics.