Kernel estimation of functional coefficients in nonparametric ARX time series models
AbstractThis paper suggests a general functional-coefficient regression model in a form of ARX time series model. Contrast to the common threshold variable in the previous works, our model allows each coefficient to possess a different threshold variable and can cover a wide range of nonlinear dynamic processes. The estimation procedure consists of two steps; local linear smoothing and marginal integration. The asymptotic normality of the proposed estimator is derived with the explicit form of bias and variance. --
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Bibliographic InfoPaper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 2001,101.
Date of creation: 2001
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