Skip to main navigation Skip to search Skip to main content

Global Credit Risk: World, Country and Industry Factors

Research output: Contribution to JournalArticleAcademicpeer-review

77 Downloads (Pure)

Abstract

We investigate the dynamic properties of systematic default risk conditions for firms in different countries, industries and rating groups. We use a high-dimensional nonlinear non-Gaussian state-space model to estimate common components in corporate defaults in a 41 country samples between 1980:Q1 and s2014:Q4, covering both the global financial crisis and euro area sovereign debt crisis. We find that macro and default-specific world factors are a primary source of default clustering across countries. Defaults cluster more than what shared exposures to macro factors imply, indicating that other factors also play a significant role. For all firms, deviations of systematic default risk from macro fundamentals are correlated with net tightening bank lending standards, suggesting that bank credit supply and systematic default risk are inversely related.
Original languageEnglish
Pages (from-to)296-317
Number of pages22
JournalJournal of Applied Econometrics
Volume32
Issue number2
Early online date20 Apr 2016
DOIs
Publication statusPublished - Mar 2017

Funding

We thank the seminar and conference participants at the Bundesbank, European Central Bank, and RMI International Risk Management Conference 2014 at NUS Singapore. Lucas acknowledges support from the Dutch National Science Foundation (NWO; grant VICI453-09-005). Koopman acknowledges support from CREATES, Aarhus University, Denmark, as funded by the Danish National Research Foundation, (DNRF78). Further, Koopman and Lucas acknowledge support from the European Union Seventh Framework Programme (FP7-SSH/2007-2013, grant agreement 320270—SYRTO). The views expressed in this paper are those of the authors and they do not necessarily reflect the views or policies of the European Central Bank or the European System of Central Banks.

FundersFunder number
CREATES
Aarhus Universitet
NUS Singapore
European Central Bank
European Commission
Seventh Framework Programme320270, FP7-SSH/2007-2013
Nederlandse Organisatie voor Wetenschappelijk OnderzoekVICI453-09-005
Danmarks GrundforskningsfondDNRF78

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 10 - Reduced Inequalities
      SDG 10 Reduced Inequalities
    2. SDG 17 - Partnerships for the Goals
      SDG 17 Partnerships for the Goals

    Cite this