Nonlinear Cointegration, Misspecification and Bimodality
AbstractWe 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 InfoPaper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 577.
Date of creation: Oct 2010
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Cointegration; nonlinearity; bimodality; misspecification; instrumental variables; asymptotic theory.;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-11-06 (All new papers)
- NEP-ECM-2010-11-06 (Econometrics)
- NEP-ETS-2010-11-06 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hansen, Bruce E., 1992. "Heteroskedastic cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 139-158.
- Ibragimov, Rustam & Phillips, Peter C.B., 2008.
"Regression asymptotics using martingale convergence methods,"
2624459, Harvard University Department of Economics.
- 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.
- Rustam Ibragimov & Peter C.B. Phillips, 2004. "Regression Asymptotics Using Martingale Convergence Methods," Cowles Foundation Discussion Papers 1473, Cowles Foundation for Research in Economics, Yale University.
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