Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/54580
Type: Conference paper
Title: A new test in parametric linear models with nonparametric autoregressive errors
Author: Gao, Jiti
King, Maxwell L.
Citation: Proceedings of the Markets and Models: Policy Frontiers in the AWH Phillips Tradition, 2008 (ESAM08)
Issue Date: 2008
Conference Name: ESAM08 (2008 : Wellington, New Zealand)
School/Discipline: School of Economics
Statement of
Responsibility: 
Jiti Gao and Maxwell King
Abstract: This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is proposed and studied to deal with the parametric specification of the nonparametric autoregressive errors with either stationarity or nonstationarity. Such a test procedure can initially avoid misspecification through the need to parametrically specify the form of the errors. In other words, we propose estimating the form of the errors and testing for stationarity or nonstationarity simultaneously. We establish asymptotic distributions of the proposed test. Both the setting and the results differ from earlier work on testing for unit roots in parametric time series regression. We provide both simulated and real–data examples to show that the proposed nonparametric unit–root test works in practice.
Keywords: Error process; nonparametric method; nonlinear time series; random walk; unit root test.
Description (link): http://www.phillips08.org.nz/
Appears in Collections:Economics publications

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