What Can Time‐Series Regressions Tell Us About Policy Counterfactuals?
证明在线性化结构宏观经济模型中，利用可估计的政策冲击因果效应就能构造替代政策规则下的反事实，并推导最优政策规则，且结果对卢卡斯批判具有稳健性。
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.