Estimating Long Run Economic Equilibrium

估计长期经济均衡

• 批准号: 8821180
• 负责人: Peter Phillips
• 金额: $ 14.31万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-04-01 至 1992-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8821180&HistoricalAwards=false
• 关键词: Estimating; Long; Run; Economic; Equilibrium

This project focuses on three important topics in econometric analysis, namely 1) the estimation of long run economic equilibrium, 2) the dynamics of models which are not fully identified, and 3) the unification of econometric distribution theory. The first topic involves examining the properties of economic time series data, in particular joint dependency of time series data sets, and nonstationarity. This project serves to link the econometric methodologies of cointegration models, vector-autoregression techniques, and error correction models into a unified framework. In doing so it derives an important relationship between correlation among time series variables and economic equilibrium. The work on partially identified models concentrates on two models in which identification is particularly important, namely simultaneous equations models, and spurious regressions in time series. Simultaneous equations models are analyzed in detail via systems methods of estimation. The project will produce a complete theory for estimation systems in which some equations are not fully identified or in which components of equations are not identified. The third part of the project applies operational algebra, a recently developed matrix calculus, to distributional problems in econometrics and statistics. This approach avoids much of the complex polynomial algebra that accompanies analysis of multivariate distribution theory. In particular, it obviates the need for expansion series representation of probability densities, and in turn greatly facilitates the derivation of both asymptotic properties and finite sample properties of estimators. %%% This research project is an analysis of the relationship between the statistical properties exhibited by many sets of economic time series data and the concept of econommic equilibrium. At the heart of most economic theory is the notion that systems tend to move toward a point of stability, rather than fluctuating randomly. From an empirical standpoint, however, the isolation of equilibrium points in actual data has proven to be very difficult. This is particularly true for time series data. When more than one series of data enter a model, for instance income data and price data, deriving an economic interpretation to the results of econometric analysis becomes problematic, since the values in both set of data exhibit the same tendency to grow over time. By applying recently developed statistical techniques this research isolates long run equilibrium in economic time series data. Tests are developed for the stability of such equilibruim points. Other econometric issues such as the identification of models consisting of simultaneous equations and the derivation of asymptotic properties of estimators are also addressed.

这个项目集中在计量经济学中的三个重要课题 分析，即1）长期经济均衡的估计， 2)未完全识别的模型的动态，以及3） 计量经济学分布理论的统一。 第一个主题涉及审查经济时间的属性 系列数据，特别是时间系列数据集的联合相关性， 和非平稳性。 该项目旨在将计量经济学 协整模型方法，向量自回归 技术和纠错模型到一个统一的框架。 在 这样做可以得出一个重要的关系， 时间序列变量和经济均衡之间的关系。 部分识别模型的工作集中在两个模型， 其中识别是特别重要的，即同时 方程模型和时间序列中的虚假回归。 联立方程模型进行了详细分析，通过系统 估计方法。 该项目将产生一个完整的理论 对于其中某些方程不完全 识别或其中方程的分量不被识别。 该项目的第三部分应用了运算代数， 发展了矩阵演算，在计量经济学中的分布问题 和统计数据。 这种方法避免了许多复杂的多项式 伴随多元分布理论分析的代数。 特别是，它避免了对展开级数的需要。 概率密度的表示，反过来大大 便于推导渐近性质和有限 估计量的样本性质。 %%% 本研究项目是对 多组经济时间序列所表现出的统计特性 数据和经济均衡的概念。 在大多数人的核心 经济学理论认为系统趋向于一个点 稳定性，而不是随机波动。 从实证 然而，从实际的角度来看，平衡点的隔离 事实证明，数据是非常困难的。 尤其如此 时间序列数据。 当多个数据序列进入模型时， 例如收入数据和价格数据， 对计量经济学分析结果的解释成为 问题，因为两组数据中的值显示相同 随时间增长的趋势。 通过应用最近发展的统计技术，这项研究 分离经济时间序列数据中的长期均衡。 测试 这是为了平衡点的稳定性而开发的。 其他 计量经济学问题，如确定模型， 的渐近性质的推导 估计器也解决。