The Economic Analysis of Systems Subject to Changes in Regime

本研究的目的是探索一种对非平稳时间序列数据进行经济分析的新方法。 目前大多数可用的模型规范都假设经济事件的最佳预测是过去观察的线性函数。 相比之下，该项目中开发的模型在数据中是非线性的。 非线性源于这样的假设：控制重要经济变量的过程偶尔会受到离散的、剧烈的制度变化的影响。 尽管具有非线性性质，但该模型对于许多理论和经验理性预期应用来说是完全易于处理的。 这项研究很重要，因为新模型有望实现许多有趣的应用，其中包括： (a) 描述商业周期特征的替代方法，这可以使我们更好地预测商业波动； (b) 分析金融数据的更灵活的工具，例如试图识别和理解股票市场的剧烈波动； (c) 在严格的计量经济学框架内分析公共政策急剧变化的影响的更好方法。

The purpose of this research is to explore a new approach to the economic analysis of nonstationary time series data. Most currently available model specifications assume that optimal forecasts of economic events are linear functions of past observations. By contrast, the model developed in this project is nonlinear in the data. The nonlinearity arises from the hypothesis that the process governing important economic variables are occasionally subject to discrete, dramatic changes in regime. Despite its nonlinear nature, the model is shown to be completely tractable for many theoretical and empirical rational-expectations applications. This research is important because the new model holds promise for a number of interesting applications, among them; (a) an alternative approach to characterizing the business cycle, which may enable us to better forecast business fluctuations; (b) a more flexible tool for analyzing financial data, for example in trying to identify and understand the dramatic fluctuations in the stock market; (c) a better approach for analyzing the effects of dramatic shifts in public policy within a rigorous econometric framework.