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Nonlinear Cointegration, Misspecification and Bimodality

Author

Listed:
  • MArcelo Cunha Medeiros

    (Department of Economics, PUC-Rio)

  • Eduardo Mendes

    (DEPARTMENT OF STATISTICS, NORTHWESTERN UNIVERSITY,)

  • Les Oxley

    (DEPARTMENT OF ECONOMICS, CANTERBURY UNIVERSITY,)

Abstract

We show that the asymptotic distribution of the ordinary least squares estimator in a cointegration regression may be bimodal. A simple case arises when the intercept is erroneously omitted from the estimated model or in nonlinear-in-variables models with endogenous regressors. In the latter case, a solution is to use an instrumental variable estimator. The core results in this paper also generalises to more complicated nonlinear models involving integrated time series.

Suggested Citation

  • MArcelo Cunha Medeiros & Eduardo Mendes & Les Oxley, 2010. "Nonlinear Cointegration, Misspecification and Bimodality," Textos para discussão 577, Department of Economics PUC-Rio (Brazil).
    • Handle: RePEc:rio:texdis:577
    as

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    References listed on IDEAS

    as
    1. Ibragimov, Rustam & Phillips, Peter C.B., 2008. "Regression Asymptotics Using Martingale Convergence Methods," Econometric Theory, Cambridge University Press, vol. 24(4), pages 888-947, August.
    2. Park, Joon Y. & Phillips, Peter C.B., 1988. "Statistical Inference in Regressions with Integrated Processes: Part 1," Econometric Theory, Cambridge University Press, vol. 4(3), pages 468-497, December.
    3. Hansen, Bruce E., 1992. "Heteroskedastic cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 139-158.
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    Keywords

    Cointegration; nonlinearity; bimodality; misspecification; instrumental variables; asymptotic theory.;
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