Testing for causality in variance under nonstationarity in variance
Paulo M.M. Rodrigues
a,1
, Antonio Rubia
b,
⁎
a
Faculty of Economics, University of Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
b
Department of Financial Economics, University of Alicante, Campus de San Vicente, CP 03080, Spain
Received 25 August 2006; received in revised form 12 December 2006; accepted 12 February 2007
Available online 14 June 2007
Abstract
Van Dijk, Osborn and Sensier [van Dijk, D., Osborn, D.R., Sensier, M., 2005, Testing for causality in variance
in the presence of breaks. Economics Letters 89, 193–199.] have recently shown, through Monte Carlo simulation,
that causality-in-variance tests may suffer severe finite sample size distortions in the presence of neglected
structural breaks. In this paper we provide the theoretical foundation to characterize such departures. The
asymptotic theory allows to depict a more complete and general analysis.
© 2007 Elsevier B.V. All rights reserved.
Keywords: Structural changes; Volatility; Causality; Variance breaks
JEL classification: C12; C22
1. Introduction
In a recent paper, van Dijk, Osborn and Sensier (2005) [DOS] show, through Monte Carlo simulation,
that causality-in-variance tests applied to macroeconomic series may suffer from severe finite sample size
distortions in the presence of neglected structural breaks in variance. In this paper, we provide the
theoretical justification for these findings as a particular case of a fairly general class of nonstationary
volatility processes. Our analysis shows that the size departures are not only a small-sample effect but will
also remain asymptotically because of the failure to consistently estimate cross-correlations in this
Economics Letters 97 (2007) 133 – 137
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⁎
Corresponding author. Tel./fax: +34 965 90 36 21.
E-mail addresses: prodrig@ualg.pt (P.M.M. Rodrigues), antonio.rubia@ua.es (A. Rubia).
1
Tel.: +351 289 817 571; fax: +351 289 815 937.
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doi:10.1016/j.econlet.2007.02.032