Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation
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Whether a country's central bank independence (CBI) status has a lowering effect on inflation is a controversial hypothesis. To date, this question could not be answered satisfactorily because the complex macroeconomics structure that gives rise to the data has not been adequately incorporated into statistical analyses. We have developed a causal model that summarizes the economic process of inflation. Based on this causal model and recent data, we discuss and identify the assumptions under which the effect of CBI on inflation can be identified and estimated. Given these and alternative assumptions we estimate this effect using modern doubly robust effect estimators, i.e. longitudinal targeted maximum likelihood estimators. The estimation procedure incorporated machine learning algorithms and was tailored to address the challenges that come with complex longitudinal macroeconomics data. We could not find strong support for the hypothesis that a central bank that is independent over a long period of time necessarily lowers inflation. Simulation studies evaluate the sensitivity of the proposed methods in complex settings when assumptions are violated, and highlight the importance of working with appropriate learning algorithms for estimation.
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