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Testing for co-integration in vector autoregressions with non-stationary volatility

Cavaliere, G and Rahbek, A and Taylor, AMR (2010) 'Testing for co-integration in vector autoregressions with non-stationary volatility.' Journal of Econometrics, 158 (1). 7 - 24. ISSN 0304-4076

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Abstract

Many key macroeconomic and financial variables are characterized by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special cases. We show that the conventional rank statistics computed as in Johansen (1988, 1991) are potentially unreliable. In particular, their large sample distributions depend on the integrated covariation of the underlying multivariate volatility process which impacts on both the size and power of the associated co-integration tests, as we demonstrate numerically. A solution to the identified inference problem is provided by considering wild bootstrap-based implementations of the rank tests. These do not require the practitioner to specify a parametric model for volatility, or to assume that the pattern of volatility is common to, or independent across, the vector of series under analysis. The bootstrap is shown to perform very well in practice. © 2010 Elsevier B.V.

Item Type: Article
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User: Jim Jamieson
Date Deposited: 30 Aug 2013 14:01
Last Modified: 05 Sep 2017 20:15
URI: http://repository.essex.ac.uk/id/eprint/7492

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