Non-stationary Gaussian ARFIMA processes: Estimation and application

Sílvia Regina Costa Lopes, Bárbara Patrícia Olbermann and Valderio Anselmo Reisen

Brazilian Review of Econometrics, 2002, vol. 22, issue 1

Abstract: Recently, the study of time series turned the attention to the ones having long memory property. The ARFIMA (p,d,q) model shows this property when the degree of differencing d is in the interval (0.0,0.5), range where the process is stationary. In this work, we analyze the estimation of the degree d* in ARFIMA (p,d*,q) processes when d* >0.5, that is, when the processes are non-stationary but still have the property of long memory. We present a simulation study for the estimators of d* with semiparametric and parametric methods and different sample sizes. The methodology is applied to the experimental data series of UK long interest gilts.

Date: 2002
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