非常规货币政策与政策前瞻

IF 1.9 3区 经济学 Q2 ECONOMICS
Sebastian Laumer , Andreas-Entony Violaris
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引用次数: 0

摘要

非常规货币政策干预对经济有何影响?利用传统 SVAR 模型进行的实证研究一致报告了对产出和价格的扩张性影响,但只考虑了少数变量。由于各国央行经常提前数月宣布其非常规政策,本文首次提出了说明和经验证据,表明这些模型容易受到政策预见的影响。为了解决政策预见问题,我们利用欧元区的扩展信息集估计了一个贝叶斯 FAVAR 模型。与现有文献一致,我们发现非常规货币政策冲击通过增加工业生产和降低失业率来促进经济活动。值得注意的是,与之前的研究结果相比,我们估计的影响更大且更持久。此外,冲击还降低了利率、利差和政府债券收益率,从而改善了金融状况。值得注意的是,与以往的研究不同,我们发现对消费者和生产者价格的影响存在很大的不确定性,这凸显了进一步研究的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unconventional monetary policy and policy foresight

What are the effects of unconventional monetary policy interventions on the economy? Empirical studies utilizing traditional SVAR models consistently report expansionary effects on output and prices while considering only a small number of variables. This paper is the first to present both narrative and empirical evidence indicating that these models are susceptible to policy foresight, as central banks frequently announce their unconventional policies months in advance. To address policy foresight, we estimate a Bayesian FAVAR model with an extended set of information for the Euro Area. Consistent with the existing literature, we find that an unconventional monetary policy shock boosts economic activity by increasing industrial production and reducing the unemployment rate. Notably, our estimated effects are both larger and more persistent compared to previous findings. Furthermore, the shock decreases interest rates, interest rate spreads, and government bond yields, leading to an improvement in financial conditions. In a noteworthy departure from previous research, we find significant uncertainty regarding the impacts on consumer and producer prices, highlighting the need for further research.

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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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