What Can Time-Series Regressions Tell Us About Policy Counterfactuals?” ; Alisdair McKay (Federal Reserve Bank of Minneapolis)

Abstract

We show that, in a general family of linearized structural macroeconomic models, knowledge of the dynamic causal effects of contemporaneous and news shocks to the prevailing policy rule can be used to: (a) construct counterfactuals under alternative policy rules; and (b) recover the optimal policy rule corresponding to a given loss function. Under our assumptions, the derived counterfactuals and optimal policies are robust to the Lucas critique. We then discuss strategies for applying these insights when only a limited amount of causal evidence on policy shock transmission is available.

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