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

Author

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  • Christian K. Wolf
  • Alisdair McKay

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.

Suggested Citation

  • Christian K. Wolf & Alisdair McKay, 2022. "What Can Time-Series Regressions Tell Us About Policy Counterfactuals?," NBER Working Papers 30358, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:30358
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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination

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