Nonparametric estimation and inference for Granger causality measures

e-Archivo Repository

Show simple item record

dc.contributor.author Taamouti, Abderrahim
dc.contributor.author Bouezmarni, Taoufik
dc.contributor.author El Ghouch, Anouar
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Economía
dc.date.accessioned 2012-04-27T15:19:08Z
dc.date.available 2012-04-27T15:19:08Z
dc.date.issued 2012-03-29
dc.identifier.issn 2340-5031
dc.identifier.uri http://hdl.handle.net/10016/14150
dc.description.abstract We propose a nonparametric estimator and a nonparametric test for Granger causality measures that quantify linear and nonlinear Granger causality in distribution between random variables. We first show how to write the Granger causality measures in terms of copula densities. We suggest a consistent estimator for these causality measures based on nonparametric estimators of copula densities. Further, we prove that the nonparametric estimators are asymptotically normally distributed and we discuss the validity of a local smoothed bootstrap that we use in finite sample settings to compute a bootstrap bias-corrected estimator and test for our causality measures. A simulation study reveals that the bias-corrected bootstrap estimator of causality measures behaves well and the corresponding test has quite good finite sample size and power properties for a variety of typical data generating processes and different sample sizes. Finally, we illustrate the practical relevance of nonparametric causality measures by quantifying the Granger causality between S&P500 Index returns and many exchange rates (US/Canada, US/UK and US/Japen exchange rates).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Economics
dc.relation.ispartofseries 12-12
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Causality measures
dc.subject.other Nonparametric estimation
dc.subject.other Time series
dc.subject.other Copulas
dc.subject.other Bernstein copula density
dc.subject.other Local bootstrap
dc.subject.other Conditional distribution function
dc.subject.other Stock returns
dc.title Nonparametric estimation and inference for Granger causality measures
dc.type workingPaper
dc.subject.jel C12
dc.subject.jel C14
dc.subject.jel C15
dc.subject.jel C19
dc.subject.jel G1
dc.subject.jel G12
dc.subject.jel E3
dc.subject.jel E4
dc.subject.eciencia Economía
dc.rights.accessRights openAccess
dc.type.version submitedVersion
dc.identifier.uxxi DT/0000000875
 Find Full text

Files in this item

*Click on file's image for preview. (Embargoed files's preview is not supported)


The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record