Financial Stress and Economic Dynamics: The Transmission of Crises
Financial Stress and Economic Dynamics: The Transmission of Crises
复制标题
DOI：
10.2139/ssrn.2199557
复制
发表时间：
2012-10
期刊：
影响因子：
--
通讯作者：
K. Hubrich;R. Tetlow
中科院分区：
文献类型：
--
作者：
K. Hubrich;R. Tetlow
最近的金融危机以及与此相关的经济活动下降，提出了一些关于经济活动及其与金融部门的联系的重要问题。本文介绍了一个金融压力指数--一个被联邦储备委员会的工作人员用于监测危机的真实的时间的指数--并展示了压力如何与真实的活动、通货膨胀和货币政策相互作用。我们定义了我们所谓的压力事件-一个时期的冲击方差和模型系数的压力影响-并描述了金融压力如何影响宏观经济动态。我们还研究了什么构成了一个有用的和可信的措施的压力和货币政策的作用。我们解决这些问题，使用一个丰富的参数化马尔可夫切换VAR模型，估计使用贝叶斯方法。我们的研究结果表明，允许时间变化是很重要的：恒定参数，恒定冲击方差模型是一个穷人的数据表征。我们发现，一般来说，高压力系数的时期，特别是压力事件，与美国近代历史上的金融事件吻合得很好。我们发现，转向压力事件对真实的经济前景非常不利，在此期间，传统货币政策相对较弱。最后，我们认为，我们的研究结果对DSGE金融事件建模的影响，研究人员希望捕捉的现象比花园品种的商业周期波动更重要，指向远离线性DSGE模型，无论是MS-DSGE模型或完全非线性模型解决了全球性的方法。
The recent financial crisis and the associated decline in economic activity have raised some important questions about economic activity and its links to the financial sector. This paper introduces an index of financial stress - an index that was used in real time by the staff of the Federal Reserve Board to monitor the crisis - and shows how stress interacts with real activity, inflation and monetary policy. We define what we call a stress event - a period affected by stress in both shock variances and model coefficients - and describe how financial stress affects macroeconomic dynamics. We also examine what constitutes a useful and credible measure of stress and the role of monetary policy. We address these questions using a richly parameterized Markov-switching VAR model, estimated using Bayesian methods. Our results show that allowing for time variation is important: the constant-parameter, constant-shock-variance model is a poor characterization of the data. We find that periods of high stress coefficients in general, and stress events in particular, line up well with financial events in recent U.S. history. We find that a shift to a stress event is highly detrimental to the outlook for the real economy, and that conventional monetary policy is relatively weak during such periods. Finally, we argue that our findings have implications for DSGE modeling of financial events insofar as researchers wish to capture phenomena more consequential than garden-variety business cycle fluctuations, pointing away from linearized DSGE models toward either MS-DSGE models or fully nonlinear models solved with global methods.