What Can Time-Series Regressions Tell Us About Policy Counterfactuals?

Christian Wolf and Alisdair McKay

No 30358, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We show that, in a general family of linearized structural macroeconomic models, knowledge of the empirically estimable causal effects of contemporaneous and news shocks to the prevailing policy rule is sufficient to construct counterfactuals under alternative policy rules. If the researcher is willing to postulate a loss function, our results furthermore allow her to recover an optimal policy rule for that loss. 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 empirical causal evidence on policy shock transmission is available.

JEL-codes: E32 E61 (search for similar items in EconPapers)
Date: 2022-08
New Economics Papers: this item is included in nep-cba, nep-ecm and nep-ets
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Citations: View citations in EconPapers (5)

Published as Alisdair McKay & Christian K. Wolf, 2023. "What Can Time‐Series Regressions Tell Us About Policy Counterfactuals?," Econometrica, Econometric Society, vol. 91(5), pages 1695-1725, September.

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Working Paper: What Can Time-Series Regressions Tell Us About Policy Counterfactuals? (2023)
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