Econometric Analysis of the Financial Crisis

正如2008年金融危机期间发生的事件及其后果所表明的那样，金融时间序列的极端波动可能会产生广泛的社会经济影响。直接影响包括财富的巨大波动，这反过来可能导致金融不安全、机构破产、经济资源配置不当，以及威胁主要经济机构信誉的全球后果。此外，经济全球化导致了强大的金融联系，一旦发生重大的共同冲击，可能会增加风险敞口。理解这一现象，探索其原因，绘制其在金融市场上的演变图，并研究其对实体经济的影响，这些都是经济学专业面临的重大挑战。这个项目旨在开发有助于我们理解其中一些问题的量化方法。除了政策制定者在最近的金融危机期间面临的直接关切之外，还有与泡沫现象的出现和发现以及由此产生的危机在金融和经济体系中的演变过程有关的问题。这些问题构成了拟议研究的主要计划的重点，该计划寻求设计新的计量经济学方法，以早期发现泡沫行为，并提供经验日期戳技术，以量化动态时间安排，并帮助绘制金融危机的演变历程。该项目将提供一种严格的计量经济学方法来确定金融泡沫的年代，为泡沫发生和破裂日期的经验估计推导出一个极限理论，并使用一个新的金融泡沫活动模型，该模型基于有效市场？模特和？轻微的爆炸性？能够捕捉金融繁荣时期的模型。这项技术将在最近的金融危机数据中得到广泛的经验性应用，提供有关各种泡沫现象的时间范围、规模和过程的经验信息，这些现象涉及金融和大宗商品市场、汇率和实体经济活动。除了这一主要研究计划外，还将进行两个次要项目。第一个问题涉及经济和金融数据的协同移动，在这种情况下，数据中的持续性特征存在一定的不确定性，这在实证研究中很常见。第二个研究项目将探索新的计量经济学方法，用于在存在个体效应的情况下进行动态面板建模。这些领域的重要性反映在社会科学的大量实证文献中，这些文献利用协整方法研究时间序列之间的长期联系，并利用动态面板回归来研究个人决策随时间的影响。

As events during the 2008 financial crisis and its aftermath have shown, extreme movements in financial time series can have wide socio-economic impact. The immediate effects involve huge swings in wealth, which in turn can lead to financial insecurity, institutional insolvency, misallocation of economic resources, and global consequences that threaten the credibility of major economic institutions. In addition, economic globalization has led to strong financial linkages that can increase risk exposure in the event of a large common shock. Understanding this phenomenon, exploring its causes, mapping its evolution over financial markets, and studying its effects on the real economy all present major challenges to the economics profession.This project aims to develop quantitative methods that will contribute to our understanding of some of these issues. Beyond the immediate concerns that have confronted policy makers during the recent financial crisis lie questions that relate to the emergence and detection of the bubble phenomena and the evolutionary course of the resulting crisis through the financial and economic systems. These issues form the focus of the primary program of proposed research, which seeks to design new econometric methodology to enable early detection of bubble behaviour and to provide empirical date stamping technology that quantifies dynamic timing and helps to map the evolutionary course of a financial crisis. The project will provide a rigorous econometric approach to dating financial bubbles, deriving a limit theory for empirical estimates of the origination and collapse dates of bubble episodes, and using a new model of financial bubble activity that is based on the successive conjunction of ?efficient market? models and ?mildly explosive? models that can capture episodes of financial exuberance. An extensive empirical implementation of this technology to recent financial crisis data is envisaged, yielding empirical information on the temporal extent, the magnitude, and the course of the various bubble phenomena that have involved financial and commodity markets, exchange rates and real economic activity.In addition to this primary research program, two secondary projects will be pursued. The first deals with co-movement in economic and financial data where there is some uncertainty about the persistence characteristics in the data, as is common in empirical research. The second program of research will explore new econometric methodology for dynamic panel modelling in the presence of individual effects. The importance of these fields is reflected in the vast empirical literatures in the social sciences that utilize cointegrating methods to study long run linkages among time series and dynamic panel regression to study the effects of individual decision making over time.