A Sufficient Statistics Approach for Macro Policy Evaluation

Abstract

The evaluation of macroeconomic policy decisions has traditionally relied on the formulation of a specific economic model. In this work, we show that two statistics are sufficient to detect, often even correct, non-optimal policies, i.e., policies that do not minimize the loss function. The two sufficient statistics are (i) the effects of policy shocks on the policy objectives, and (ii) forecasts for the policy objectives conditional on the policy decision. Both statistics can be estimated without relying on a specific model. We illustrate the method by studying US monetary policy decisions.