非线性时间序列分析STAR模型及其在经济学中的应用被引量：38

The Application In Economics of Nonlinear Time Series Analysis and Smooth Transition Autoregression

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摘要 20世纪90年代末以来,非线性时间序列模型两个主要的研究方向是混沌论模型(chaosmodel)和机制转换模型(switchingregimemodels),而后者考虑了各种不同形式的机制转换行为(switchingregimebehavior),通常被认为由三个最常见的机制转换模型组成①。平滑转换自回归模型(STAR)由于能在某种程度上捕捉到机制转换过程中时间序列的动态过程,因而成为近年国外计量经济学前沿领域追踪的热点之一。本文将主要对平滑转换自回归模型(STAR)的特征、估计、检验方法以及在经济领域的应用做深入的探讨。 Since 1990＇s, the two major classes of nonlinear time series models are the chaos model and switching regime model. The interest in smooth transition autoregression models （STAR） has been steadily increasing, since STAR models can capture the dynamics of regime swithching. This survey will provide a brief sketch on the characteristics, estimation, test procedures and applications of STAR models.

作者王俊孔令夷

机构地区中国人民大学财政金融学院 Simon Fraser University(加拿大)

出处《数量经济技术经济研究》 CSSCI 北大核心 2006年第1期77-85,160,共10页 Journal of Quantitative & Technological Economics

关键词非线性 STAR LSTAR ESTAR Non- linear Time Series Analysis Smooth Transition Autoregression （STAR） Logistic STAR （LSTAR） Exponential STAR （ESTAR）

分类号 F064.1 [经济管理—政治经济学]

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