A Sufficient Statistics Approach for Macro Policy Evaluation

Régis Barnichon and Geert Mesters

No 2022, Working Paper Series from Federal Reserve Bank of San Francisco

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.

Keywords: optimal policy; impulse responses; forecasting (search for similar items in EconPapers)
JEL-codes: C14 C32 E32 E52 (search for similar items in EconPapers)
Pages: 15
Date: 2022-04-27
New Economics Papers: this item is included in nep-cba and nep-ecm
Note: First draft: March 2020.
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Citations: View citations in EconPapers (3)

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Related works:
Working Paper: A Sufficient Statistics Approach for Macro Policy Evaluation (2020)
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DOI: 10.24148/wp2022-15

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