Estimating Long Memory Causality Relationships by a Wavelet Method

Yushu Li

No 2012:15, Working Papers from Lund University, Department of Economics

Abstract: The traditional causality relationship proposed by Granger (1969) assumes the relationships between variables are short range dependent with the same integrated order. Chen (2006) proposed a bi-variate model which can catch the long-range dependent among the two variables and the series do not need to be fractionally co-integrated. A long memory fractional transfer function is introduced to catch the long-range dependent in this model and a pseudo spectrum based method is proposed to estimate the long memory parameter in the bi-variate causality model. In recent years, a wavelet domain-based method has gained popularity in estimations of long memory parameter in unit series. No extension to bi-series or multi-series has been made and this paper aims to fill this gap. We will construct an estimator for the long memory parameter in the bi-variable causality model in the wavelet domain. The theoretical background is derived and Monte Carlo simulation is used to investigate the performance of the estimator.

Keywords: Granger causality; long memory; Monte Carlo simulation; wavelet domain (search for similar items in EconPapers)
JEL-codes: C30 C51 C63 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2012-05-21
New Economics Papers: this item is included in nep-ecm and nep-ets
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