Default prediction with dynamic sectoral and macroeconomic frailties
This paper extends the macroeconomic frailty model to include sectoral frailty factors that capture default correlations among firms in a similar business. We estimate sectoral and macroeconomic frailty factors and their effects on default intensity using the data for Japanese firms from 1992 to 2010. We find strong evidence for the presence of sectoral frailty factors even after accounting for the effects of observable covariates and macroeconomic frailty on default intensity. The model with sectoral frailties performs better than that without. Results show that accounting for the sources of unobserved sectoral default risk covariations improves the accuracy of default probability estimation.
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
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.:
- Duffie, Darrell & Lando, David, 2001. "Term Structures of Credit Spreads with Incomplete Accounting Information," Econometrica, Econometric Society, vol. 69(3), pages 633-664, May.
- Siem Jan Koopman & André Lucas & André Monteiro, 2005.
"The Multi-State Latent Factor Intensity Model for Credit Rating Transitions,"
Tinbergen Institute Discussion Papers
05-071/4, Tinbergen Institute, revised 04 Jul 2005.
- Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005.
"Multi-Period Corporate Default Prediction With Stochastic Covariates,"
CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- 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.
- Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
- 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.
- Durbin, James & Koopman, Siem Jan, 2001.
"Time Series Analysis by State Space Methods,"
Oxford University Press, number 9780198523543, December.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Hertzel, Michael G. & Officer, Micah S., 2012. "Industry contagion in loan spreads," Journal of Financial Economics, Elsevier, vol. 103(3), pages 493-506.
- Fukuda, Shin-ichi & Kasuya, Munehisa & Akashi, Kentaro, 2009.
"Impaired bank health and default risk,"
Pacific-Basin Finance Journal,
Elsevier, vol. 17(2), pages 145-162, April.
- Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2008. "Impaired Bank Health and Default Risk," CIRJE F-Series CIRJE-F-564, CIRJE, Faculty of Economics, University of Tokyo.
- Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2005. "Impaired Bank Health and Default Risk," Bank of Japan Working Paper Series 05-E-13, Bank of Japan.
- Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, 09.
- Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
- Philippe Jorion & Gaiyan Zhang, 2009. "Credit Contagion from Counterparty Risk," Journal of Finance, American Finance Association, vol. 64(5), pages 2053-2087, October.
- Lu, Yang-Cheng & Shen, Chung-Hua & Wei, Yu-Chen, 2013. "Revisiting early warning signals of corporate credit default using linguistic analysis," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 1-21.
- Maria Vassalou & Yuhang Xing, 2004. "Default Risk in Equity Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 831-868, 04.
- Jarrow, Robert & Li, Haitao & Liu, Sheen & Wu, Chunchi, 2010. "Reduced-form valuation of callable corporate bonds: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 95(2), pages 227-248, February.
- Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
- Darrell DUFFIE & Andreas ECKNER & Guillaume HOREL & Leandro SAITA, "undated".
"Frailty Correlated Default,"
Swiss Finance Institute Research Paper Series
08-44, Swiss Finance Institute.
- Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
- Kimie Harada & Takatoshi Ito & Shuhei Takahashi, 2010. "Is the Distance to Default a Good Measure in Predicting Bank Failures? Case Studies," NBER Working Papers 16182, National Bureau of Economic Research, Inc.
- Jorion, Philippe & Zhang, Gaiyan, 2007. "Good and bad credit contagion: Evidence from credit default swaps," Journal of Financial Economics, Elsevier, vol. 84(3), pages 860-883, June.
- Naifar, Nader, 2011. "What explains default risk premium during the financial crisis? Evidence from Japan," Journal of Economics and Business, Elsevier, vol. 63(5), pages 412-430, September.
- Kao, Chihwa & Wu, Chunchi, 1990. "Two-Step Estimation of Linear Models with Ordinal Unobserved Variables: The Case of Corporate Bonds," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 317-325, July.
When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:40:y:2014:i:c:p:211-226. 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: (Shamier, Wendy)
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.