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Policy Evaluation Using Causal Inference Methods

Author

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  • Denis Fougère

    (OSC - Observatoire sociologique du changement (Sciences Po, CNRS) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

  • Nicolas Jacquemet

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

This working-paper describes the main impact evaluation methods, both experimental and quasi-experimental, and the statistical model underlying them. Some of the most important methodological advances to have recently been put forward in this field of research are presented. We focus not only on the need to pay particular attention to the accuracy of the estimated effects, but also on the requirement to replicate assessments, carried out by experimentation or quasi-experimentation, in order to distinguish false positives from proven effects

Suggested Citation

  • Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Working Papers hal-03455978, HAL.
  • Handle: RePEc:hal:wpaper:hal-03455978
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    More about this item

    Keywords

    causal inference; evaluation methods; causal effetcs; statistics;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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