Econometrica: Sep, 2023, Volume 91, Issue 5
What Can Time-Series Regressions Tell Us About Policy Counterfactuals?
https://doi.org/10.3982/ECTA21045
p. 1695-1725
Alisdair McKay, Christian K. Wolf
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.
Supplemental Material
Supplement to "What Can Time-Series Regressions Tell Us About Policy Counterfactuals?"
Alisdair McKay and Christian K. Wolf
This online appendix contains supplemental material for the article “What Can Time-Series Regressions Tell Us About Policy Counterfactuals?”. We provide (i) supplementary results complementing our theoretical identification analysis in Section 2, (ii) implementation details for our empirical methodology in Section 3, and (iii) several supplementary findings and alternative experiments complementing our empirical applications in Section 4.
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Supplement to "What Can Time-Series Regressions Tell Us About Policy Counterfactuals?"
Alisdair McKay and Christian K. Wolf
This zip file contains the replication files for the manuscript.
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