Policy Evaluation Using Causal Inference Methods

Denis Fougere and Nicolas Jacquemet ()

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

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

Keywords: causal inference; evaluation methods; causal effetcs; statistics (search for similar items in EconPapers)
Date: 2020-01
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Policy Evaluation Using Causal Inference Methods (2021)
Working Paper: Policy Evaluation Using Causal Inference Methods (2021)
Working Paper: Policy Evaluation Using Causal Inference Methods (2021)
Working Paper: Policy Evaluation Using Causal Inference Methods (2021)
Working Paper: Policy Evaluation Using Causal Inference Methods (2020)
Working Paper: Policy Evaluation Using Causal Inference Methods (2020)
Working Paper: Policy Evaluation Using Causal Inference Methods (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:hal-03455978

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