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Searching for linear and nonlinear cointegration: a new approach

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  • Aparicio, Felipe M.
  • Escribano, Álvaro

Abstract

In this paper we propose several statistics to measure serial dependence that are useful to characterize short and long memory properties. By doing that we can measure nonlinear serial dependence, which allows us to extend the usual linear framework and to discuss short-memory and long-memory properties in a nonlinear contexto Bootstrap simulation experiments report promising results for the new indices to detect nonlinearities in the cointegrating relationship,prior to estimating the nonlinear cointegrating function.

Suggested Citation

  • 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.
    • Handle: RePEc:cte:wsrepe:6219
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    References listed on IDEAS

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    1. Aparicio F. M. & Escribano A., 1998. "Information-Theoretic Analysis of Serial Dependence and Cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(3), pages 1-24, October.
    2. Robert Engle & Clive Granger, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
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    4. Alvaro Escribano & Santiago Mira, 2002. "Nonlinear error correction models," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(5), pages 509-522, September.
    5. Granger, Clive W J & Hallman, Jeffrey J, 1991. "Long Memory Series with Attractors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 53(1), pages 11-26, February.
    6. Escribano, Álvaro & Mira, Santiago, 1997. "Nonlinear cointegration with mixing errors," DES - Working Papers. Statistics and Econometrics. WS 6204, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    8. Escribano, A., 1987. "Error-correction systems: nonlinear adjustments to linear long-run relationships," LIDAM Discussion Papers CORE 1987030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    10. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    11. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    12. James G. MacKinnon, 1990. "Critical Values for Cointegration Tests," Working Paper 1227, Economics Department, Queen's University.
    13. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    14. Granger, Clive W J, 1995. "Modelling Nonlinear Relationships between Extended-Memory Variables," Econometrica, Econometric Society, vol. 63(2), pages 265-279, March.
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    1. Aparicio, Felipe M. & Arranz, Miguel A. & 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.

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