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Testing for Cointegration with Nonstationary Volatility

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  • Boswijk, H. P.
  • Zu, Y.

Abstract

The paper generalises recent unit root tests for nonstationary volatility to a multivariate context. Persistent changes in the innovation variance matrix lead to size distortions in conventional cointegration tests, and possibilities of increased power by taking the time-varying volatilities and correlations into account. The testing procedures are based on a likelihood analysis of the vector autoregressive model with a conditional covariance matrix that may be estimated nonparametrically. We find that under suitable conditions, adaptation with respect to the volatility matrix process is possible, in the sense that nonparametric volatility estimation does not lead to a loss of asymptotic local power.

Suggested Citation

  • Boswijk, H. P. & Zu, Y., 2013. "Testing for Cointegration with Nonstationary Volatility," Working Papers 13/08, Department of Economics, City University London.
    • Handle: RePEc:cty:dpaper:13/08
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    File URL: https://openaccess.city.ac.uk/id/eprint/2922/1/13_08_City_WP-Yang2013.pdf
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    References listed on IDEAS

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    1. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    2. Marçal, Emerson F. & Valls Pereira, Pedro L. & Abbara, Omar, 2009. "Testing the long-run implications of the expectation hypothesis using cointegration techniques with structural change," MPRA Paper 15624, University Library of Munich, Germany.

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