Monte Carlo Evidence on Cointegration and Causation
Hector O Zapata and
Alicia Rambaldi ()
Oxford Bulletin of Economics and Statistics, 1997, vol. 59, issue 2, 285-98
The small sample performance of Granger causality tests under different model dimensions, degree of cointegration, direction of causality, and system stability are presented. Two tests based on maximum likelihood estimation of error-correction models (LR and WALD) are compared to a Wald test based on multivariate least squares estimation of a modified VAR (MWALD). In large samples, all test statistics perform well in terms of size and power. For smaller samples, the LR and WALD tests perform better than the MWALD test. Overall, the LR test outperforms the other two in terms of size and power in small samples. Copyright 1997 by Blackwell Publishing Ltd
References: Add references at CitEc
Citations: View citations in EconPapers (188) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Working Paper: MONTE CARLO EVIDENCE ON COINTEGRATION AND CAUSATION (1996)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bla:obuest:v:59:y:1997:i:2:p:285-98
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0305-9049
Access Statistics for this article
Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple
More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().