Nonlinear Cointegration, Misspecification and Bimodality
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.
|Date of creation:||Oct 2010|
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- Ibragimov, Rustam & Phillips, Peter C.B., 2008.
"Regression Asymptotics Using Martingale Convergence Methods,"
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.
- Ibragimov, Rustam & Phillips, Peter C.B., 2008. "Regression asymptotics using martingale convergence methods," Scholarly Articles 2624459, Harvard University Department of Economics.
- Hansen, Bruce E., 1992. "Heteroskedastic cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 139-158. Full references (including those not matched with items on IDEAS)
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