EconPapers    
Economics at your fingertips  
 

Nonparametric Copula-Based Test for Conditional Independence with Applications to Granger Causality

Taoufik Bouezmarni, Jeroen V.K. Rombouts and Abderrahim Taamouti

Journal of Business & Economic Statistics, 2011, vol. 30, issue 2, 275-287

Abstract: This article proposes a new nonparametric test for conditional independence that can directly be applied to test for Granger causality. Based on the comparison of copula densities, the test is easy to implement because it does not involve a weighting function in the test statistic, and it can be applied in general settings since there is no restriction on the dimension of the time series data. In fact, to apply the test, only a bandwidth is needed for the nonparametric copula. We prove that the test statistic is asymptotically pivotal under the null hypothesis, establishes local power properties, and motivates the validity of the bootstrap technique that we use in finite sample settings. A simulation study illustrates the size and power properties of the test. We illustrate the practical relevance of our test by considering two empirical applications where we examine the Granger noncausality between financial variables. In a first application and contrary to the general findings in the literature, we provide evidence on two alternative mechanisms of nonlinear interaction between returns and volatilities: nonlinear leverage and volatility feedback effects. This can help better understand the well known asymmetric volatility phenomenon. In a second application, we investigate the Granger causality between stock index returns and trading volume. We find convincing evidence of linear and nonlinear feedback effects from stock returns to volume, but a weak evidence of nonlinear feedback effect from volume to stock returns.

Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2011.638831 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality (2009) Downloads
Working Paper: A nonparametric copula based test for conditional independence with applications to Granger causality (2009) Downloads
Working Paper: A nonparametric copula based test for conditional independence with applications to granger causality (2009) Downloads
Working Paper: A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality (2009) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:30:y:2011:i:2:p:275-287

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20

DOI: 10.1080/07350015.2011.638831

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan

More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:jnlbes:v:30:y:2011:i:2:p:275-287