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May 12, 2016The Review of Economics and Statistics421 citations

Regional Policy Evaluation: Interactive Fixed Effects and Synthetic Controls

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LGLaurent GobillonTMThierry Magnac

Key Points

  • To investigate the application of interactive fixed effects and linear factor models in regional policy evaluation and contrast their performance with difference-in-differences and synthetic control methods.
  • Derived mathematical properties and support conditions comparing interactive effect estimators with difference-in-differences and synthetic controls.
  • Conducted Monte Carlo simulation experiments to analyze estimator behavior in small samples.
  • Evaluated the empirical effect of a 1990s French enterprise zone policy on local unemployment rates.
  • Demonstrated that traditional difference-in-differences estimators are generically biased in the presence of unobserved interactive effects.
  • Derived specific support conditions necessary for valid estimation using synthetic controls.
  • Showed through small-sample simulations and empirical enterprise zone data that factor models offer a robust alternative for estimating regional treatment effects.

Abstract

In this paper, we investigate the use of interactive effect or linear factor models in regional policy evaluation. We contrast treatment effect estimates obtained using Bai (2009) with those obtained using difference in differences and synthetic controls (Abadie and coauthors). We show that difference in differences are generically biased, and we derive support conditions for synthetic controls. We construct Monte Carlo experiments to compare these estimation methods in small samples. As an empirical illustration, we provide an evaluation of the impact on local unemployment of an enterprise zone policy implemented in France in the 1990s.

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Cite This Study

Gobillon et al. (2016) studied this question.

synapsesocial.com/papers/69dc57948bac30e30e9f58ddhttps://doi.org/10.1162/rest_a_00537
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