AbstractThe synthetic control method (SCM) is widely used to evaluate causal effects under quasi-experimental designs. However, SCM suffers from weaknesses that compromise its accuracy, stability and meaningfulness, due to the nested optimization problem of covariate relevance and counterfactual weights. We propose a decoupling of both problems. We evaluate the economic effect of government formation deadlock in Spain-2016 and find that SCM method overestimates the effect by 0.23 pp.

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... , we replicate two studies and compare results from standard and decoupled SCM. Decoupled SCM offers higher accuracy and stability, while ensuring the economic meaningfulness of covariates used in building the counterfactual.