Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/260040 
Authors: 
Year of Publication: 
2012
Series/Report no.: 
Working Paper No. 2012:15
Publisher: 
Lund University, School of Economics and Management, Department of Economics, Lund
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.
Subjects: 
Granger causality
long memory
Monte Carlo simulation
wavelet domain
JEL: 
C30
C51
C63
Document Type: 
Working Paper

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