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  • Jiti Gao (a1), Maxwell King (a2), Zudi Lu (a3) and Dag Tjøstheim (a4)


This paper considers a nonparametric time series regression model with a nonstationary regressor. We construct a nonparametric test for whether the regression is of a known parametric form indexed by a vector of unknown parameters. We establish the asymptotic distribution of the proposed test statistic. Both the setting and the results differ from earlier work on nonparametric time series regression with stationarity. In addition, we develop a bootstrap simulation scheme for the selection of suitable bandwidth parameters involved in the kernel test as well as the choice of simulated critical values. An example of implementation is given to show that the proposed test works in practice.


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*Address correspondence to Jiti Gao, School of Economics, University of Adelaide, Adelaide SA 5005, Australia; e-mail:


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  • Jiti Gao (a1), Maxwell King (a2), Zudi Lu (a3) and Dag Tjøstheim (a4)


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