Synchronization and Other Generalizations of Cointegration

这个项目的主要部分是关于一个新的想法， 在低水平下， 频率称为同步。 同步发生在 一个经济体的长期组成部分是密切相关的， 重要的经济变量同步变化。 的 该项目的目标是（1）开发一个简单的 宏观经济理论，这将导致某种形式的 同步;（2）设计同步测试，以共同 （3）开发同步测试， （4）不确定性;（4）确定合适的 不平衡机制，导致同步合作， 整合作为一种平衡;（5）应用技术 发展到各种实际系列，包括利率 不同的到期日，不同行业的就业率， 人均国民生产总值和人均国民生产总值的一对强有力的国家， 贸易流动，如加拿大和美国;以及（6） 综述工程中关于同步的文献， 物理学，看看这些文献是否相关或适用于 经济学 该项目还分析了与时间的协整- 改变参数。 这是一项非常令人兴奋和重要的研究。 的早期工作 研究人员开发了一种时间的统计特征， 一系列被称为协整，其中一个线性组合 独立非平稳的数据序列是平稳的。 这一发展非常重要，因为大多数经济 时间序列数据通常包括非平稳过程 作为趋势。 为了获得对实际运动的任何有意义的洞察 在经济中的变量，必须清除数据的 非平稳过程的影响。 协整检验和 技术大大简化了实现平稳性 特别是对于包括多个数据系列的分析模型 每一个都有相似的生长趋势。 同步， 该项目的主题，开辟了一个新的研究领域， 一体化 经济均衡可以表明 关键经济变量的同步。 因此， 该项目开发的同步技术将为经济学家提供 新的和更强大的测试的存在和特点 经济均衡。

The main part of this project is concerned with a new idea about the relative dynamics of co-integrated processes at low frequencies called synchronization. Synchronization occurs when long-run components of an economy are closely related and cause important economic variables to move together in phase. The objectives of the project are (1) to develop a simple macroeconomic theory which would lead to some form of synchronization; (2) to devise tests of synchronization for co- integrated series; (3) to develop tests of synchronization for series that are not co-integrated; (4) to find an appropriate disequilibrium mechanism that leads to synchronized co- integration as an equilibrium; (5) to apply the techniques developed to various actual series, including interest rates of differing maturities, employment rates in different sectors of a country and GNP per capita for a pair of countries with strong trade flows such as Canada and the United States; and (6) to survey the literature on synchronization in engineering and physics to see if this literature is relevant or applicable to economics. The project also analyzes co-integration with time- varying parameters. This is very exciting and important research. Earlier work by the investigator developed a statistical characterization of time series known as co-integration in which a linear combination of data series that are independently non-stationary is stationary. This development is extremely important because most economic time series data typically include non-stationary processes such as trends. To gain any meaningful insight into actual movements of the variables in an economy, one must purge the data of the influence of non-stationary processes. Co-integration tests and techniques have greatly simplified achieving stationarity especially for analytical models including several data series each containing similar growth tendencies. Synchronization, the subject of this project, opens a new line of research within co- integration. Economic equilibrium can be shown to imply synchronization of key economic variables. Thus the tests for synchronization developed by this project will give economists new and more powerful tests for the existence and characteristics of economic equilibria.