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PA - C6B - ECO562A : Applied Econometrics 2

Domaine > Economie.

Descriptif

Applied econometrics 2

 

Objectives

In this course, we will study how econometric methods can help answer causal questions. We will discuss why establishing credible causal links is difficult in social sciences and how to overcome some of the challenges. We will build upon the tools introduced in applied econometrics 1 (linear regressions) to outline several methods central to modern econometric practice: experiments, instrumental variables, regression discontinuity designs, fixed effects estimations, differences-in-differences, event studies, matching and synthetic control. We will use relevant real-world examples to illustrate the assumptions and the limitations of each method. We will also learn about the experience of guest speakers who studied econometrics at the PhD level and now apply econometric tools in their daily (non-academic) jobs.

During the tutorials, students will work in group to critically assess research articles answering a causal question. They will proceed in five steps:

  • Formulate a causal question and explain why it is interesting / important.
  • Find two research articles using one of the methods studied in the course to answer the question.
  • Discuss the methods used in each paper.
  • Confront the results of both papers.
  • Summarize the findings in a presentation and a term paper.

The intended learning outcomes of this course are the following:

  • Explain why and when econometrics is useful
  • Locate cutting-edge empirical economics research
  • Assess the flaws and limitations of empirical work
  • Evaluate firms’ decisions and public policies

Evaluation

  • The evaluation consists of three parts:

    Active participation during lectures and tutorials (individual grade)

    Oral presentation (individual grade)

    Term paper (group grade)

 

References

Slides are self-contained. Interested students can look at the following textbooks to find additional technical details and examples:

  • Introduction to econometrics, Stock and Watson
  • Mastering metrics, Angrist and Pischke
  • Mostly harmless econometrics, Angrist and Pischke

In the applications we will discuss thoroughly the following articles:

  • Bandiera O, Burgess R, Das J, Gulesci S, Rasul I and Sulaiman (2017) “Labor markets and poverty in village economies”, Quarterly Journal of Economics
  • Duflo, E (2001) “Schooling and labor market consequences of school construction in Indonesia: Evidence from an unusual policy experiment”, American Economic Review
  • Ozier O (2017) “The Impact of Secondary Schooling in Kenya: A Regression Discontinuity Analysis”, Journal of Human Resources.
  • Bleakley H (2003). “Disease and Development: Evidence from the American South.” Journal of the European Economic Association.
  • Acemoglu, D and S Johnson (2007). “Disease and Development: The Effect of Life Expectancy on Economic Growth”, Journal of Political Economy.

Pour les étudiants du diplôme Titre d’Ingénieur diplômé de l’École polytechnique

Vous devez avoir validé l'équation suivante : UE ECO552A

prerequisite ECO552A

Format des notes

Numérique sur 20

Littérale/grade réduit

Pour les étudiants du diplôme Titre d’Ingénieur diplômé de l’École polytechnique

Le rattrapage est autorisé (Note de rattrapage conservée)
    L'UE est acquise si note finale transposée >= C
    • Crédits ECTS acquis : 5 ECTS

    La note obtenue rentre dans le calcul de votre GPA.

    Pour les étudiants du diplôme MScT-Economics for Smart Cities and Climate Policy

    Le rattrapage est autorisé (Note de rattrapage conservée)
      L'UE est acquise si note finale transposée >= C
      • Crédits ECTS acquis : 4 ECTS

      La note obtenue rentre dans le calcul de votre GPA.

      Pour les étudiants du diplôme Non Diplomant

      Le rattrapage est autorisé (Note de rattrapage conservée)
        L'UE est acquise si note finale transposée >= C
        • Crédits ECTS acquis : 5 ECTS

        Pour les étudiants du diplôme Echanges PEI

        Pour les étudiants du diplôme MScT-Economics, Data Analytics and Corporate Finance

        Le rattrapage est autorisé (Note de rattrapage conservée)
          L'UE est acquise si note finale transposée >= C
          • Crédits ECTS acquis : 4 ECTS

          La note obtenue rentre dans le calcul de votre GPA.

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