MONTE CARLO EVIDENCE ON COINTEGRATION AND CAUSATION

Hector O. Zapata and Alicia Rambaldi (a.rambaldi@uq.edu.au)

No 31690, Staff Papers from Louisiana State University, Department of Agricultural Economics and Agribusiness

Abstract: 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.

Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
Pages: 19
Date: 1996
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https://ageconsearch.umn.edu/record/31690/files/lsu9608.pdf (application/pdf)

Related works:
Journal Article: Monte Carlo Evidence on Cointegration and Causation (1997)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:lsustp:31690

DOI: 10.22004/ag.econ.31690

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