Econometric Analysis of the Financial Crisis

正如2008年金融危机期间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，这反过来又会导致金融不安全、机构破产、经济资源分配不当，以及威胁主要经济机构信誉的全球性后果。此外，经济全球化导致了强有力的金融联系，在发生大规模共同冲击时可能增加风险。理解这一现象，探索其原因，绘制其在金融市场上的演变，研究其对真实的经济的影响，都是经济学专业面临的重大挑战。本项目旨在开发定量方法，有助于我们理解其中的一些问题。除了决策者在最近的金融危机中面临的直接关切之外，还有一些问题涉及泡沫现象的出现和发现，以及由此产生的危机通过金融和经济体系的演变过程。这些问题形成了拟议研究的主要计划的重点，该计划旨在设计新的计量经济学方法，以早期发现泡沫行为，并提供实证日期戳技术，量化动态时间，并有助于绘制金融危机的演变过程。该项目将提供一个严格的计量经济学的方法来约会金融泡沫，推导出一个极限理论的起源和泡沫事件的崩溃日期的经验估计，并使用一个新的模型，金融泡沫活动的基础上，连续连接？有效市场？模型和？轻度爆炸性？可以捕捉金融繁荣时期的模型。设想将这一技术广泛地应用于最近的金融危机数据，产生关于涉及金融和商品市场、汇率和真实的经济活动的各种泡沫现象的时间范围、规模和过程的经验信息。第一个涉及经济和金融数据的共同运动，其中数据的持续性特征存在一些不确定性，这在实证研究中很常见。研究的第二个程序将探讨新的计量经济学方法的动态面板模型中存在的个人影响。这些领域的重要性反映在社会科学的大量经验文献中，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.