Identification of Dynamic Regression (Distributed Lag) Models Connecting Two Time Series
作者:
LarryD. Haugh,
G.E. P. Box,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1977)
卷期:
Volume 72,
issue 357
页码: 121-130
ISSN:0162-1459
年代: 1977
DOI:10.1080/01621459.1977.10479920
出版商: Taylor & Francis Group
关键词: Rational distributed lag;Identification of distributed lag model;Bivariate time-series model;Autoregressive moving average model;Cross-correlation function;Univariate innovations
数据来源: Taylor
摘要:
A methodology is introduced for identifying dynamic regression or distributed lag models relating two time series. First, specification of a bivariate time-series model is discussed, and its relationship to the usual dynamic regression model is indicated. Then, a two-stage identification procedure is presented which involves fitting univariate time-series models to each series, and identifying a dynamic shock model relating the two univariate model innovation series. The models obtained at these two stages are combined to identify a dynamic regression model, which may then be fitted in the usual ways. Two systems of economic time series illustrate the methodology.
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