The empirical performance of the financial accelerator since 2008

IF 1.9 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2024-08-02 DOI:10.1016/j.jedc.2024.104927
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引用次数: 0

Abstract

We evaluate the empirical performance of financial frictions à la Bernanke et al. (1999) during and after the Global Financial Crisis. We document that in an ex-post analysis based on nonlinear Bayesian methods, these frictions do not improve the standard medium-scale DSGE model's ability to explain the macroeconomic dynamics during the Great Recession. The reason is that in the estimated model with financial frictions, the drastic post-2008 collapse of investment causes firms' leverage to decline. Taking the model at face value, this would trigger a narrowing of the credit spread, contradicting the observed persistently large credit spread throughout the post-2008 period. Additionally, the estimated model attributes only a minor role to risk shocks à la Christiano et al. (2014). These findings are confirmed independently for US and euro area data.

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2008 年以来金融加速器的实证表现
我们评估了伯南克等人(1999)的金融摩擦在全球金融危机期间和之后的实证表现。我们根据非线性贝叶斯方法进行了事后分析,结果表明,在大衰退期间,这些摩擦并没有提高标准中等规模 DSGE 模型解释宏观经济动态的能力。原因在于,在有金融摩擦的估计模型中,2008 年后投资的急剧崩溃导致企业杠杆率下降。根据模型的表面价值,这将导致信贷息差缩小,这与所观察到的 2008 年后整个时期信贷息差持续较大的情况相矛盾。此外,估计模型认为风险冲击的作用很小,类似于 Christiano 等人(2014 年)的研究。这些发现在美国和欧元区的数据中都得到了证实。
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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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