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Monte Carlo Evidence on Cointegration and Causation
Author(s) -
Zapata Hector O.,
Rambaldi Alicia N.
Publication year - 1997
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/1468-0084.00065
Subject(s) - wald test , cointegration , econometrics , statistics , monte carlo method , causality (physics) , mathematics , multivariate statistics , granger causality , statistical hypothesis testing , physics , quantum mechanics
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.