Economics at your fingertips  

Measuring connectedness of euro area sovereign risk

Rebekka Buse and Melanie Schienle

International Journal of Forecasting, 2019, vol. 35, issue 1, 25-44

Abstract: We introduce a method for measuring the default risk connectedness of euro zone sovereign states using credit default swap (CDS) and bond data. The connectedness measure is based on an out-of-sample variance decomposition of model forecast errors. Due to its predictive nature, it can respond to crisis occurrences more quickly than common in-sample techniques. We determine the sovereign default risk connectedness using both CDS and bond data in order to obtain a more comprehensive picture of the system. We find evidence that there are several observable factors that drive the difference between CDS and bonds, but both data sources still contain specific information for connectedness spill-overs. In general, we can identify countries that impose risk on the system and the respective spill-over channels. Our empirical analysis covers the years 2009–2014, such that the recovery paths of countries exiting EU and IMF financial assistance schemes and the responses to the ECB’s unconventional policy measures can be analyzed.

Keywords: Variance decomposition; Sovereign risk; Connectedness; Credit default swaps; Bonds; Eurozone crisis (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Measuring connectedness of euro area sovereign risk (2019) Downloads
Working Paper: Measuring Connectedness of Euro Area Sovereign Risk (2015) 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:

DOI: 10.1016/j.ijforecast.2018.07.010

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Haili He ().

Page updated 2020-06-12
Handle: RePEc:eee:intfor:v:35:y:2019:i:1:p:25-44