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.