A New Approach to Causality Testing
AbstractA new causality test based on Higher Order Cumulants (HOC) is proposed in this paper. The test can be applied on non Gaussian time series. The methodological novelty is the usage of a two- step method based on digital whitening, which is performed by ARMA-HOC filter. To substantiate the method further, an empirical analysis of the relationship between the interest rate spread and real gross domestic product (GDP) growth is presented for the period 1982:q1 -2010:q1. The spread is measured as a difference between 10-year bond yields and three-month Treasury bill rates in the US. The fist step applies ARMA-HOC models to obtain white residuals from a quarterly term spread (TS) and GDP growth. The second step tests the dynamical correlation of TS and GDP growth residuals. The results show that the proposed test can capture the information about non Gaussian properties of the random variables being tested. The test is compared with the Granger-Sims causality test. The paper questions the reliability of the Granger test.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Institute of Economic Sciences in its journal Economic Analysis.
Volume (Year): 44 (2011)
Issue (Month): 1-2 ()
Contact details of provider:
Postal: 12 Zmaj Jovina St, 11000 Belgrade, Serbia
Phone: +381 11 2622 357, 2623-055
Fax: +381 11 2181 471
Web page: http://www.ien.bg.ac.rs
More information through EDIRC
Non Gaussian time series; causality testing; higher order cumulants; Granger-Sims test; Box-Hough test; ARMA-HOC test;
Find related papers by JEL classification:
- P43 - Economic Systems - - Other Economic Systems - - - Finance; Public Finance
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zorica Bozic).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.