Econometric Modeling of Processes with Varying Structural Parameters

该项目继续对一种特别适用于时间序列分析的模型，特别是用于研究金融部门价格变动的模型进行成功的计量经济学研究。用于时间序列分析的传统统计方法假设预测误差的方差从一个观察点到另一个观察点保持不变。恩格尔教授和他的同事们开发了一类模型，称为自回归条件异方差(ARCH)模型，放松了这一限制性假设。在ARCH模型中，变量的方差本身是随机的，并以整个变量集中包含的信息为条件。这些模型被非常成功地用于分析资产价格变动、股票市场波动、预测通胀和衡量风险。在这个项目中，恩格尔教授将他过去的工作扩展到包括多变量时间序列模型。他允许方差随时间变化，但不会降低模型的通用性，但会导致简明的规范。这项工作还包括协整的概念，它是对几系列数据的统计特征，这些数据可能合理地包含共同的趋势或增长趋势。这是一个重要的扩展，因为这些模型有一个直接的经济学解释。恩格尔教授还通过将ARCH规范应用于外汇市场资产价格、利率、期权合约和股票价格的数据，实证地验证了他的理论工作。

This project continues a successful line of econometric research on a type of model especially suited for time series analysis, in particular for examining financial sector price movements. Traditional statistical methods for time series analysis assume that the variances of forecast errors remain constant from one observation to the next. Professor Engle and his colleagues have developed a class of models know as Autoregressive Conditional Heteroskedasticity (ARCH) models which relax this restrictive assumption. In the ARCH model the variances of a variable are themselves stochastic and conditioned on the information contained in the entire variable set. These models have been used very successfully in analyzing asset price movements, volatility in the stock market, in forecasting inflation, and in measuring risk. In this project Professor Engle extends his past work to include multivariate time series models. He allows the variances to change over time in a manner that does not decrease the generality of the model, but results in a parsimonious specification. Also included in this work is the concept of co-integration, which is a statistical characterization of several series of data which might reasonably contain common trends or growth tendencies. This is an important extension in that such models have a straightforward economic interpretation. Professor Engle also empirically validates his theoretical work by applying the ARCH specification to data on asset prices in foreign exchange markets, interest rates, options contracts, and equity prices.