What Can Timeseries Regressions Tell Us About Policy Counterfactuals

Working Paper: NBER ID: w30358

Authors: 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.

Keywords: No keywords provided

JEL Codes: E32; E61


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
knowledge of the causal effects of contemporaneous and news shocks to a given policy rule (D80)construct robust counterfactuals for alternative policy rules (E61)
multiple distinct policy shocks (E65)expected future path of a policy instrument (E60)
policy affects private-sector behavior (G38)current and expected future path of the policy instrument (E61)
contemplated counterfactual rule is enforced ex post along the equilibrium path (D80)circumvent the Lucas critique (E19)
empirical method can be applied to monetary policy rule counterfactuals (C54)demonstrate method's robustness and applicability (C90)
given a loss function (C51)characterize optimal policy (H21)

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