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A model free cointegration approach for pairs of I(d) variables


  • Arranz, Miguel A.
  • Aparicio, Felipe M.
  • Escribano, Álvaro


In this paper we propose several model free (non parametric) statistics to measure serial dependence that are useful to characterize the short and the long memory properties of series in the time and the frequency domain. Conditions on the joint memory properties of the series such as cointegration are introduced by means of these statistics. We show that the relationship between the non parametric concept of cointegration and the cross-covariance functions of the series, has a natural interpretation as an instrumental variable estimator. We show that its small sample behavior is better than the usual least squares estimator. Finally, from our characterization it is posibble to discriminate between fractional and integer cointegration

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  • Arranz, Miguel A. & Aparicio, Felipe M. & Escribano, Álvaro, 2000. "A model free cointegration approach for pairs of I(d) variables," DES - Working Papers. Statistics and Econometrics. WS 9967, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:9967

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    References listed on IDEAS

    1. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
    2. Aparicio, Felipe M. & Escribano, Álvaro, 1997. "Searching for linear and nonlinear cointegration: a new approach," DES - Working Papers. Statistics and Econometrics. WS 6219, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Arranz, Miguel A & Escribano, Alvaro, 2000. " Cointegration Testing under Structural Breaks: A Robust Extended Error Correction Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(1), pages 23-52, February.
    4. Escribano, A., 1987. "Error-correction systems: nonlinear adjustments to linear long-run relationships," CORE Discussion Papers 1987030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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