Tests of Causality
The Message in the Innovations
G. William Schwert
University of Rochester, Rochester, NY 14627
and National Bureau of Economic Research
Carnegie-Rochester Conference Series on Public Policy, 10 (Spring
Reprinted in Theory, Policy, Institutions: Papers from the Carnegie-Rochester
Conferences on Public Policy,
Karl Brunner and Allan Meltzer, eds. (Amsterdam: North-Holland, 1983) 215-256.
This paper describes new time series techniques and shows the advantages
and disadvantages of these techniques compared with more traditional methods.
Cross-correlation analysis of residuals from autoregressive-integrated-moving
average (ARIMA) models to determine the predictive relations between two variables.
I conclude that it is important to consider the power of this procedure
before putting much faith in empirical results that seem to find a "lack of
relationship" between economic variables.
Key words: Causality tests, ARIMA
JEL Classifications: C22
Cited 60 times in the SSCI and SCOPUS through 2017
© Copyright 1979, Elsevier
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