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Tests for Predictive Relationships between Time Series Variables: A Monte Carlo Investigation

 

作者: CharlesR. Nelson,   G.William Schwert,  

 

期刊: Journal of the American Statistical Association  (Taylor Available online 1982)
卷期: Volume 77, issue 377  

页码: 11-18

 

ISSN:0162-1459

 

年代: 1982

 

DOI:10.1080/01621459.1982.10477761

 

出版商: Taylor & Francis Group

 

关键词: Monte Carlo;ARIMA models;Causality tests

 

数据来源: Taylor

 

摘要:

Bivariate time series models have been used extensively to analyze the relationship between pairs of economic variables. Various tests have been proposed that can be used to examine the adequacy of specific models. The empirical literature is noteworthy for the frequency with which different authors using different tests reach different conclusions, and for the apparent lack of evidence for certain relationships strongly suggested by economic theory. The objective of this study is to use Monte Carlo methods to examine the size and power of alternative tests, and to relate these findings to the analytical structure of the tests.

 

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