MONTE CARLO EVIDENCE ON COINTEGRATION AND CAUSATION

dc.creatorZapata, Hector O.
dc.creatorRambaldi, Alicia N.
dc.date2017-04-01T20:22:14Z
dc.date.accessioned2026-07-09T04:14:09Z
dc.descriptionThe 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.
dc.identifierdoi:10.22004/ag.econ.31690
dc.identifierhttps://ageconsearch.umn.edu/record/31690/files/lsu9608.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/31690
dc.identifier.urihttp://hdl.handle.net/123456789/546859
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/31690
dc.titleMONTE CARLO EVIDENCE ON COINTEGRATION AND CAUSATION
dc.typeText

Archivos