Characterizing nonlinearities in business cycles using smooth transition autoregressive models
作者:
T. Terasvirta,
H. M. Anderson,
期刊:
Journal of Applied Econometrics
(WILEY Available online 1992)
卷期:
Volume 7,
issue S1
页码: 119-136
ISSN:0883-7252
年代: 1992
DOI:10.1002/jae.3950070509
出版商: Wiley Subscription Services, Inc., A Wiley Company
数据来源: WILEY
摘要:
AbstractDuring the past few years investigators have found evidence indicating that various time‐series representing business cycles, such as production and unemployment, may be nonlinear. In this paper it is assumed that if the time‐series is nonlinear, then it can be adequately described by a smooth transition autoregressive (STAR) model. The paper describes the application of these models to quarterly logarithmic production indices for 13 countries and ‘Europe’. Tests reject linearity for most of these series, and estimated STAR models indicate that the nonlinearity is needed mainly to describe the responses of production to large negative shocks such as oil price
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