Economics at your fingertips  

Granger causality testing in mixed-frequency Vars with possibly (co)integrated processes

Alain Hecq () and Thomas Goetz
Authors registered in the RePEc Author Service: Thomas Götz

MPRA Paper from University Library of Munich, Germany

Abstract: We analyze Granger causality testing in mixed-frequency VARs with possibly (co)integrated time series. It is well known that conducting inference on a set of parameters is dependent on knowing the correct (co)integration order of the processes involved. Corresponding tests are, however, known to often suffer from size distortions and/or a loss of power. Our approach, which boils down to the mixed-frequency analogue of the one by Toda and Yamamoto (1995) or Dolado and Lutkepohl (1996), works for variables that are stationary, integrated of an arbitrary order, or cointegrated. As it only requires an estimation of a mixed-frequency VAR in levels with appropriately adjusted lag length, after which Granger causality tests can be conducted using simple standard Wald test, it is of great practical appeal. We show that the presence of non-stationary and trivially cointegrated highfrequency regressors (Goetz et al., 2013) leads to standard distributions when testing for causality on a parameter subset, without any need to augment the VAR order. Monte Carlo simulations and two applications involving the oil price and consumer prices as well as GDP and industrial production in Germany illustrate our approach.

Keywords: Mixed frequencies; Granger causality; Hypothesis testing, Vector autoregressions; Cointegration (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2018-06-27
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) original version (application/pdf)

Related works:
Journal Article: Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes (2019) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

Page updated 2021-01-17
Handle: RePEc:pra:mprapa:87746