In this paper, Debortoli, Galı́, and Gambetti offer compelling empirical evidence that extraordinary actions taken by the Federal Reserve were able to shield the macroeconomy from many of the policy constraints associated with the zero lower bound (ZLB) on nominal interest rates. As Debortoli et al. argue, if these extraordinary actions had been ineffective, the United States would have witnessed a change in the volatility of macro aggregates and a change in their response to specific nonfinancial shocks. Yet volatility and impulse responses remained largely unchanged during the ZLB period. There is no one more qualified than the paper’s first discussant to discuss the ZLB, the Fed’s actions, and their effects on the macroeconomy. With this in mind, I will offer no comments of substance about this excellent paper, beyond the observation that I am in agreement with Debortoli et al.’s overall empirical conclusions. Instead, I will focus my comments on a methodological issue: statistical inference in sign-restricted structural vector autoregressions (SVARs), which is one of the methods used in Debortoli et al.’s paper. Sign-restricted SVARs are an increasingly popular method for estimating dynamic causal effects in macroeconomics. Many researchers use a variant of Uhlig’s (2005) Bayes method for imposing these sign restrictions and conducting inference. Thismethod has both strengths and weaknesses. The strengths are widely recognized by macroeconomists but the weaknesses far less so. This discussion explains and highlights these weaknesses. I make two initial comments. First, Debortoli et al. use a sophisticated time-varying SVAR identified by both long-run equality restrictions and shorter-run sign restrictions. To keep things simple, I will focus on a time-invariant SVAR. Second, there is nothing original in my comments beyond a few numerical calculations. Sign-restricted SVARs are a special

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评论

在本文中，Debortoli、Galı́ 和 Gambetti 提供了令人信服的经验证据，表明美联储采取的非凡行动能够保护宏观经济免受与名义利率零下限 (ZLB) 相关的许多政策约束。正如德博托利等人。争辩说，如果这些非常规行动无效，美国将见证宏观总量波动的变化以及它们对特定非金融冲击的反应的变化。然而，在 ZLB 期间，波动性和脉冲响应基本保持不变。没有人比该论文的第一位讨论者更有资格讨论 ZLB、美联储的行动及其对宏观经济的影响。考虑到这一点，我不会对这篇出色的论文发表任何实质性的评论，除了我同意 Debortoli 等人的总体经验结论之外的观察。相反，我将把我的评论集中在一个方法论问题上：符号限制结构向量自回归 (SVAR) 中的统计推断，这是 Debortoli 等人的论文中使用的方法之一。符号限制的 SVAR 是一种越来越流行的方法，用于估计宏观经济学中的动态因果效应。许多研究人员使用 Uhlig (2005) 贝叶斯方法的变体来施加这些符号限制并进行推理。这种方法有优点也有缺点。宏观经济学家广泛认可其优势，但其劣势却远不及。本次讨论解释并强调了这些弱点。我提出两个初步意见。首先，Debortoli 等人。使用由长期等式限制和短期符号限制确定的复杂时变 SVAR。为简单起见，我将专注于时不变 SVAR。其次，除了一些数值计算之外，我的评论中没有任何原创内容。受符号限制的 SVAR 是一个特殊的