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Nonlinear Cointegration, Misspecification and Bimodality

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  • 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.

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Bibliographic Info

Paper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 577.

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Length: 24p
Date of creation: Oct 2010
Date of revision:
Handle: RePEc:rio:texdis:577

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

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  1. Ibragimov, Rustam & Phillips, Peter C.B., 2008. "Regression Asymptotics Using Martingale Convergence Methods," Econometric Theory, Cambridge University Press, vol. 24(04), pages 888-947, August.
  2. Hansen, Bruce E., 1992. "Heteroskedastic cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 139-158.
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