Block Whittle Estimation of Time Varying Stochastic Regression Models with Long Memory

Chris Toumping Fotso and Philipp Sibbertsen

Hannover Economic Papers (HEP) from Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät

Abstract: This paper proposes an estimator that accounts for time variation in a regression relationship with stochastic regressors exhibiting long-range dependence, covering weak fractional cointegration as a special case. An interesting application of this estimator is its ability to handle situations where the regression coefficient changes abruptly. The parametric formulation of this estimator is introduced using the Block-Whittle-based estimation. We analyze the asymptotic properties of this estimator, including consistency and asymptotic normality. Furthermore, we examine the finite sample behavior of the estimator through Monte Carlo simulations. Additionally, we consider a real-life application to demonstrate its advantages over the constant case.

Keywords: Stochastic regressors; weak fractional cointegration; Block-Whittle-based estimation; consistency; asymptotic normality (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2024-11
New Economics Papers: this item is included in nep-ecm and nep-ets
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