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Firm default and aggregate fluctuations

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  • Tor Jacobson
  • Jesper Lindé
  • Kasper Roszbach

Abstract

This paper studies the relationship between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm-specific factors. By using a panel data set for virtually all incorporated Swedish businesses over 1990-2009, a period which includes a full-scale banking crisis, we find strong evidence for a substantial and stable impact from aggregate fluctuations on business defaults. A standard logit model with financial ratios augmented with macroeconomic factors can account surprisingly well for the outburst in business defaults during the banking crisis, as well as the subsequent fluctuations in default frequencies. Moreover, the effects of macroeconomic variables differ across industries in an economically intuitive way. Out-of-sample evaluations show that our approach is superior to models that exclude macro information and standard well-fitting time-series models. Our analysis shows that firm-specific factors are useful in ranking firms' relative riskiness, but that macroeconomic factors are necessary to understand fluctuations in the absolute risk level.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 1029.

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Date of creation: 2011
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Handle: RePEc:fip:fedgif:1029

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Keywords: Business failures - Sweden ; Business cycles - Econometric models;

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Citations

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Cited by:
  1. Orth, Walter, 2013. "Multi-period credit default prediction with time-varying covariates," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 214-222.
  2. Nakamura, L.I. & Roszbach, K., 2010. "Credit Ratings and Bank Monitoring Ability," Discussion Paper 2010-37S, Tilburg University, Center for Economic Research.
  3. Ongena, Steven & Popov, Alexander & Udell, Gregory F., 2012. "When the cat's away the mice will play: does regulation at home affect bank risk taking abroad?," Working Paper Series 1488, European Central Bank.
  4. Angela González Arbeláez, . "Determinantes del riesgo de crédito comercial en Colombia," Temas de Estabilidad Financiera 045, Banco de la Republica de Colombia.
  5. Konstantin Belyaev & Aelita Belyaeva & Tomas Konecny & Jakub Seidler & Martin Vojtek, 2012. "Macroeconomic Factors as Drivers of LGD Prediction: Empirical Evidence from the Czech Republic," Working Papers 2012/12, Czech National Bank, Research Department.
  6. Lawrence J. Christiano & Mathias Trabandt & Karl Walentin, 2010. "Introducing financial frictions and unemployment into a small open economy model," CQER Working Paper 2010-04, Federal Reserve Bank of Atlanta.
  7. Lana Ivicic & Sasa Cerovac, 2009. "Credit Risk Assessment of Corporate Sector in Croatia," Financial Theory and Practice, Institute of Public Finance, vol. 33(4), pages 373-399.
  8. Orth, Walter, 2011. "Multi-period credit default prediction with time-varying covariates," MPRA Paper 30507, University Library of Munich, Germany.
  9. Giordani, Paolo & Jacobson, Tor & von Schedvin , Erik & Villani, Mattias, 2011. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Working Paper Series 256, Sveriges Riksbank (Central Bank of Sweden).
  10. González-Aguado, Carlos & Suarez, Javier, 2011. "Interest Rates and Credit Risk," CEPR Discussion Papers 8398, C.E.P.R. Discussion Papers.
  11. Quiroz, Matias & Villani, Mattias, 2013. "Dynamic mixture-of-experts models for longitudinal and discrete-time survival data," Working Paper Series 268, Sveriges Riksbank (Central Bank of Sweden).
  12. Ferreira Filipe, Sara & Grammatikos, Theoharry & Michala, Dimitra, 2014. "Forecasting Distress in European SME Portfolios," MPRA Paper 53572, University Library of Munich, Germany.

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