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Published online by Cambridge University Press: 06 July 2012
This paper studies a nonlinear cointegrating regression model with nonlinear nonstationary heteroskedastic error processes. We establish uniform consistency for the conventional kernel estimate of the unknown regression function and develop atwo-stage approach for the estimation of the heterogeneity generating function.
The authors thank the co-editor Professor Saikkonen and two referees for helpful comments on the original version. The main idea of this paper greatly benefited from discussions with Professor Phillips when the first author visited Singapore Management University in April 2009. Wang acknowledges partial research support from the Australian Research Council.