This paper describes, in a non-technical way, the main impact evaluation methods, both experimental and quasi-experimental, and the statistical model underlying them. In the first part, we provide a brief survey of the papers making use of those methods that have been published by the journal Economie et Statistique / Economics and Statistics over the past fifteen years. In the second part, some of the most important methodological advances to have recently been put forward in this field of research are presented. To finish, 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 evaluations, carried out by experimentation or quasi-experimentation, in order to distinguish false positives from proven effects.

Citation: Fougère, D. & Jacquemet, N. (2019). Causal Inference and Impact Evaluation. Economie et Statistique / Economics and Statistics, 510-511-512, 181–200.
https://doi.org/10.24187/ecostat.2019.510t.1996