Some Pretesting Issues on Testing for Granger Noncausality

Judith A. Giles () and Sadaf Mirza
Authors registered in the RePEc Author Service: Judith Anne Clarke ()

No 9914, Econometrics Working Papers from Department of Economics, University of Victoria

Abstract: We compare testing strategies for Granger noncausality in vector autoregressions (VARs) that may or may not have unit roots and cointegration. Sequential testing methods are examined; these test for cointegration and use either a differenced VAR or a vector error correction model (VECM), in which to undertake the main noncausality test. Basically, the pretesting strategies attempt to verify the validity of appropriate standard limit theory. These methods are contrasted with an augmented lag approach that ensures the limiting Chi Square null distribution irrespective of the data’s nonstationarity characteristics. Our simulations involve bivariate and trivariate VARs in which we allow for the lag order to be selected by general to specific testing as well as by model selection criteria. We find that the current practice of pretesting for cointegration can result in severe over-rejections of the noncausal null while overfitting suffers less size distortion with often little loss in power.

Keywords: cointegration; error correction model; vector autoregressive model; lag length selection; model selection methods; sequential testing; information criteria (search for similar items in EconPapers)
JEL-codes: C32 C51 C52 (search for similar items in EconPapers)
Pages: 49 pages
Date: 1999-12-14
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: ISSN 1485-6441
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

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