Asymptotic theory for regression models with fractional local to unity root errors

Farzad Sabzikar; Kris De Brabanter

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arXiv · 2002.09753

Asymptotic theory for regression models with fractional local to unity root errors

Farzad Sabzikar·Kris De Brabanter

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Abstract

This paper develops the asymptotic theory for parametric and nonparametric regression models when the errors have a fractional local to unity root (FLUR) model structure. FLUR models are stationary time series with semi-long range dependence property in the sense that their covariance function resembles that of a long memory model for moderate lags but eventually diminishes exponentially fast according to the presence of a decay factor governed by a noncentrality parameter. When this parameter is sample size dependent, the asymptotic normality for these regression models admit a wide range of stochastic processes with behavior that includes long, semi-long, and short memory processes.

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Farzad Sabzikar, Kris De Brabanter. 2020-02-22. Asymptotic theory for regression models with fractional local to unity root errors. https://arxiv.org/abs/2002.09753

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