| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w30358 |
| 来源ID | Working Paper 30358 |
| What Can Time-Series Regressions Tell Us About Policy Counterfactuals? | |
| Christian K. Wolf; Alisdair McKay | |
| 发表日期 | 2022-08-15 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 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. |
| 主题 | Macroeconomics ; Business Cycles ; Fiscal Policy |
| URL | https://www.nber.org/papers/w30358 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/588031 |
| 推荐引用方式 GB/T 7714 | Christian K. Wolf,Alisdair McKay. What Can Time-Series Regressions Tell Us About Policy Counterfactuals?. 2022. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w30358.pdf（1139KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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