Does economic policy matter? A note on the narrative approach and exact inference
研究从罕见事件中进行时间序列推断的不确定性，发现少量叙事冲击可能捕捉到无关的宏观经济噪音，并利用费希尔精确推断量化了美国宏观经济数据中政策效应的不确定性。
This note examines uncertainty in time-series inference from rare episodes, focusing on the narrative approach. A small number of randomly drawn episodes may falsely suggest policy effects because they are associated with macroeconomic shocks that do not cancel out in inference. We illustrate this using Fisher-style exact inference. Applying our test to Romer and Romer’s (2023) analysis, we find substantial uncertainty. Although the unemployment rate’s peak response to an identified monetary contraction exceeds the 95-percent confidence bands of the counterfactual distribution based on randomly drawn months—suggesting systematic policy effects—this finding is reversed once additional controls are included. • Small numbers of narrative shocks risk capturing unrelated macroeconomic noise. • Fisher-style inference quantifies uncertainty in identifying policy effects. • We find that this type of uncertainty is substantial in US macroeconomic data. • Results highlight fragility of inference from rare policy shock episodes.