Making Causal Inferences in Small Samples Using Synthetic Control Methodology: Did Chrysler Benefit from Government Assistance?

Abstract

We introduce synthetic control analysis to management research. This recently developed statistical methodology overcomes challenges to causal inference in contexts constrained by small samples or few occurrences of the phenomenon of interest. Synthetic control constructs a replica of a focal firm, or other observation unit, based on a weighted combination of untreated firms with similar attributes within the sample population. The method quantifies the magnitude and direction of a treatment effect by comparing the actual performance of a focal unit to its counterfactual replica without treatment. As an illustration, we assess the impact of government intervention in the auto sector on the performance of Chrysler which, following the financial crisis, accepted government support in return for Treasury oversight. The synthetic Chrysler we construct — representing the firm’s estimated performance without government intervention — sold 29% more vehicles in the U.S. than did the actual firm during the intervention period.

Keywords: Synthetic Control, Counterfactual Methodology, Government Intervention, TARP, Automobile Industry, Case Study Methods

JEL Classification: M00, K00, L1, L2, L9, H1, H5, C4