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Testing and Inference in Nonlinear Cointegrating Vector Error Correction Models

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  • Dennis Kristensen

    ()
    (Dep. of Economics, Columbia University and CREATES)

  • Anders Rahbek

    ()
    (Department of Economics, University of Copenhagen and CREATES)

Abstract

In this paper, we consider a general class of vector error correction models which allow for asymmetric and non-linear error correction. We provide asymptotic results for (quasi-)maximum likelihood (QML) based estimators and tests. General hypothesis testing is considered, where testing for linearity is of particular interest as parameters of non-linear components vanish under the null. To solve the latter type of testing, we use the so-called sup tests, which here requires development of new (uniform) weak convergence results. These results are potentially useful in general for analysis of non-stationary non-linear time series models. Thus the paper provides a full asymptotic theory for estimators as well as standard and non-standard test statistics. The derived asymptotic results prove to be new compared to results found elsewhere in the literature due to the impact of the estimated cointegration relations. With respect to testing, this makes implementation of testing involved, and bootstrap versions of the tests are proposed in order to facilitate their usage. The asymptotic results regarding the QML estimators extend results in Kristensen and Rahbek (2010, Journal of Econometrics) where symmetric non-linear error correction considered. A simulation study shows that the fi?nite sample properties of the bootstrapped tests are satisfactory with good size and power properties for reasonable sample sizes.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2010-68.

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Length: 43
Date of creation: 10 Jan 2010
Date of revision:
Handle: RePEc:aah:create:2010-68

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Nonlinear error correction; cointegration; testing nonlinearity; nonlinear time series; sup tests; vanishing parameters; testing.;

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  1. de Jong, Robert M., 2001. "Nonlinear estimation using estimated cointegrating relations," Journal of Econometrics, Elsevier, vol. 101(1), pages 109-122, March.
  2. de Jong, Robert M., 2002. "Nonlinear minimization estimators in the presence of cointegrating relations," Journal of Econometrics, Elsevier, vol. 110(2), pages 241-259, October.
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Cited by:
  1. Line Elvstrøm Ekner & Emil Nejstgaard, 2013. "Parameter Identification in the Logistic STAR Model," Discussion Papers 13-07, University of Copenhagen. Department of Economics.
  2. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.

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