Separating the impact of macroeconomic variables and global frailty in event data
Global frailty is an unobserved macroeconomic variable. In event data contexts, this unobserved variable is assumed to impact the hazard rate of event arrivals. Attempts to identify and estimate the path of frailty are complicated when observed macroeconomic variables also impact hazard rates. It is possible that the impact of the observed macro variables and global frailty can be confused and identification can fail. In this paper I show that, under appropriate assumptions, the path of global frailty and the impact of observed macro variables can both be recovered. This approach differs from previous work in that I do not assume frailty follows a specific stochastic process form. Previous studies identify global frailty by assuming a stochastic form and using a filtering approach. However, chosen stochastic forms are arbitrary and can potentially lead to poor results. The method in this paper shows how to recover frailty without these assumptions. This can serve as a model check to filtering approaches. The methods are applied to simulations and an application to corporate default.
|Date of creation:||10 Jul 2013|
|Contact details of provider:|| Postal: Manor Rd. Building, Oxford, OX1 3UQ|
Web page: https://www.economics.ox.ac.uk/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andrï¿½ Lucas, 2014.
"Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk,"
The Review of Economics and Statistics,
MIT Press, vol. 96(5), pages 898-915, December.
- Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
- Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Creal, Drew, 2013. "Observation driven mixed-measurement dynamic factor models with an application to credit risk," Working Paper Series 1626, European Central Bank.
- Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CIRJE F-Series CIRJE-F-373, CIRJE, Faculty of Economics, University of Tokyo.
- Darrell Duffie & Leandro Siata & Ke Wang, 2006. "Multi-Period Corporate Default Prediction With Stochastic Covariates," NBER Working Papers 11962, National Bureau of Economic Research, Inc.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Darrell Duffie & Andreas Eckner & Guillaume Horel & Leandro Saita, 2009. "Frailty Correlated Default," Journal of Finance, American Finance Association, vol. 64(5), pages 2089-2123, October.
- Darrell DUFFIE & Andreas ECKNER & Guillaume HOREL & Leandro SAITA, "undated". "Frailty Correlated Default," Swiss Finance Institute Research Paper Series 08-44, Swiss Finance Institute.
- Christopher Mayer & Karen Pence & Shane M. Sherlund, 2009. "The Rise in Mortgage Defaults," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 27-50, Winter.
- Christopher J. Mayer & Karen M. Pence & Shane M. Sherlund, 2008. "The rise in mortgage defaults," Finance and Economics Discussion Series 2008-59, Board of Governors of the Federal Reserve System (U.S.).
- Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, 02.
- Sanjiv Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2006. "Common Failings: How Corporate Defaults are Correlated," NBER Working Papers 11961, National Bureau of Economic Research, Inc.
- Lando, David & Nielsen, Mads Stenbo, 2010. "Correlation in corporate defaults: Contagion or conditional independence?," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 355-372, July.
- Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
- Azizpour, Shahriar & Giesecke, Kay & Kim, Baeho, 2011. "Premia for correlated default risk," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1340-1357, August. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:667. See general 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: (Monica Birds)
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.