Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls

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 by Bai (2009)'s least squares method with the popular difference in difference estimates as well as with estimates obtained using synthetic control approaches as developed by Abadie and coauthors. We show that difference in differences are generically biased and we derive the support conditions that are required for the application of synthetic controls. We construct an extensive set of Monte Carlo experiments to compare the performance of these estimation methods in small samples. As an empirical illustration, we also apply them to the evaluation of the impact on local unemployment of an enterprise zone policy implemented in France in the 1990s.

Keywords

Replaced by

Laurent Gobillon, and Thierry Magnac, “Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls”, The Review of Economics and Statistics, vol. 98, n. 3, July 2016, pp. 535–551.

Reference

Laurent Gobillon, and Thierry Magnac, “Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls”, TSE Working Paper, n. 13-419, July 2013.