Nonparametric cointegration analysis

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Abstract

In this paper we propose consistent cointegration tests, and estimators of a basis of the space of cointegrating vectors, that do not used specification of the data-generating process, apart from some mild regularity conditions, or estimation of structural and/or nuisance parameters. This nonparametric approach is in the same spirit as Johansen's LR method in that the test statistics involved are obtained from the solutions of a generalized eigenvalue problem, and the hypotheses to be tested are the same, but in our case the two matrices in the generalized eigenvalue problem involved are constructed independently of the data-generating process. We compare our approach empirically as well as by a limited Monte Carlo simulation with Johansen's approach, using the series for In(wages) and In(GNP) from the extended Nelson-Plosser data.

References (33)

  • H.P. Boswijk

    Testing for an unstable root in conditional and structural error correction models

    Journal of Econometrics

    (1994)
  • R.F. Engle

    On the theory of cointegrated economic time series

  • R.F. Engle et al.

    Cointegrating and error correction: Representation, estimation, and testing

    Econometrica

    (1987)
  • R.F. Engle et al.

    Cointegrated economic time series: A survey with new results

    (1989)
  • P. Hall et al.

    Martingale limit theory and its applications

    (1980)
  • R.W. Hamming

    Numerical methods for scientists and engineers

    (1973)
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    This paper was written and revised while affiliated with the Southern Methodist University and enjoying the hospitality of Tilburg University during the summers of 1993, 1994, and 1995. The helpful comments of Manfred Deistler, Philip Hans Franses, Noud van Giersbergen, Esfandiar Maassoumi, Rolf Tschernig, Ben Vogelvang, and four referees are gratefully acknowledged. Previous versios of this paper have been presented at the University of Amsterdam, Free University of Amsterdam, University of Houston, Rice University, Texas A&M University, Tinbergen Institute Rotterdam University of British Columbia, University of Virginia, the University of Wisconsin, ESEM 1994, and the ERNSI Econometric Workshop 1995, The Netherlands.

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