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

• 成果类型: Article
• 署名作者: Mckay, Alisdair; Wolf, Christian K.
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - Minneapolis; Massachusetts Institute of Technology (MIT); National Bureau of Economic Research
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA21045
• 发表日期: 2023
• 页码: 1695-1725
• 关键词: monetary-policy; shocks

摘要

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.