Estimating the effects of Iberian price cap using a Bayesian multivariate synthetic control approach

In causal inference a popular tool to assess policy effect is the synthetic control method (SCM). An undeveloped aspect is the use of SCM in complex contexts, as the estimation of causal effects on multiple outcomes simultaneously, where correlation structure across multiple outcomes can be leveraged to estimate more reliable and transparent policy effects. In this work, we propose an expansion of the current methods to deal with these complications. Our motivating application is the so-called Iberian Exception, the mechanism implemented by Spain in 2022 to set a cap for natural gas prices exploited in energy production. These interventions, starting with energy prices, have multiple impacts on other macroeconomic measures, such as GDP and unemployment. Here we evaluate the overall assessment of the policy on multiple outcomes, using a novel Bayesian multivariate approach for policy evaluation.