Testing for Co-Integration in Vector Autoregressions with Non-Stationary Volatility
University of Bologna - Department of Statistics
University of Copenhagen - Department of Statistics and Operations Research
A. M. Robert Taylor
affiliation not provided to SSRN
September 8, 2008
CREATES Research Paper No. 2008-50
Univ. of Copenhagen Dept. of Economics Discussion Paper No. 08-34
Many key macro-economic and financial variables are characterised 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, nor 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.
Number of Pages in PDF File: 39
Keywords: Co-integration, non-stationary volatility, trace and maximum eigenvalue tests, wild bootstrap
JEL Classification: C30, C32working papers series
Date posted: October 3, 2008
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