Ergodicity of Nonlinear Autoregression with Nonlinear ARCH Innovations

  • Hwang, S.Y. (Dept. of Statistics, Sookmyung Women′s University) ;
  • Basawa, I.V. (Dept. of Statistics, University of Georgia)
  • Published : 2001.08.01

Abstract

This article explores the problem of ergodicity for the nonlinear autoregressive processes with ARCH structure in a very general setting. A sufficient condition for the geometric ergodicity of the model is developed along the lines of Feigin and Tweedie(1985), thereby extending classical results for specific nonlinear time series. The condition suggested is in turn applied to some specific nonlinear time series illustrating that our results extend those in the literature.

Keywords

References

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