Advanced Econometrics

ECS503 Advanced Econometrics

  • Topics


    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 inference and identification with method of moments, maximum likelihood, panel data models, identification and natural experiments, applied instrumental variables, differences in differences and regression discontinuities. We also cover some further econometric topics such as choice models, measurement error and missing data, dependent data, limited dependent variables, and computer literacy.

  • Learning outcome

    Learning outcome

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


    • Identify and understand the standard identification strategies in research papers.


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

    General competencies:

    • Transform raw data into canonical useful forms.
    • Use available software to estimate standard models on real world data.
    • Evaluate alternative identification strategies.

  • Teaching


     Lectures and assignments.

  • Required prerequisites

    Required prerequisites

    Master-level econometrics.

  • Requirements for course approval

    Requirements for course approval

    Approved assignments, termpaper, and participation in class

  • Assessment


    Written 4-hour school exam.

  • Grading Scale

    Grading Scale

    Grading scale: Pass/Fail

  • Computer tools

    Computer tools

    Stata and subversion.

  • Semester



  • Literature


    In addition to selected papers, there are two textbooks:

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

    Greene, Wililam H. (2008). Econometric Analysis, Pearson Education, 6 edition.


ECTS Credits
Teaching language

Course responsible

Assistant professor Morten Sæthre, Department of Economics.

Lecturers: Morten Sæthre and professor Katrine Vellesen Løken