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Does Credit Risk Vary with Economic Cycles? The Case of Finland

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Abstract

The significance of credit risk models has increased with the introduction of new Basel accord known as Basel II. The aim of this study is default rate modeling. This paper follows the two possible approaches of a macro credit risk modeling. First, empirical models are investigated. Second, a latent factor model based on Merton's idea is introduced. Both of these models are derived from individual default probability models. We employed data over the time period from 1988 to 2003 of the Finnish economy. First, linear vector autoregressive models were used in the case of dynamic empirical model. We examined how significant macroeconomic indicators determined the default rate in the economy. However these models cannot provide microeconomic foundation as latent factor models. A one-factor model was estimated using disaggregated industrial data. This estimation can help understand relation between credit risk and macroeconomic indicators. Models can be used for default rate prediction or stress testing by central authorities.

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  • Petr Jakubík, 2006. "Does Credit Risk Vary with Economic Cycles? The Case of Finland," Working Papers IES 2006/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2006.
    • Handle: RePEc:fau:wpaper:wp2006_11
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    1. Petr JAKUBÍK, 2007. "Macroeconomic Environment and Credit Risk (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(1-2), pages 60-78, March.
    2. Cornaglia, Anna & Morone, Marco, 2009. "Rating philosophy and dynamic properties of internal rating systems: A general framework and an application to backtesting," MPRA Paper 14711, University Library of Munich, Germany.
    3. Ptak-Chmielewska Aneta & Matuszyk Anna, 2019. "Macroeconomic Factors in Modelling the SMEs Bankruptcy Risk. The Case of the Polish Market," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(3), pages 40-49, September.
    4. Claudia Miani & Giulio Nicoletti & Alessandro Notarpietro & Massimiliano Pisani, 2012. "Banks� balance sheets and the macroeconomy in the Bank of Italy Quarterly Model," Questioni di Economia e Finanza (Occasional Papers) 135, Bank of Italy, Economic Research and International Relations Area.
    5. International Monetary Fund, 2009. "Cyprus: Financial Sector Assessment Program Update: Technical Note: Measuring Banking Stability in Cyprus," IMF Staff Country Reports 2009/171, International Monetary Fund.
    6. Guler Aras & Lale Aslan, 2011. "Capital structure and credit risk management: evidence from Turkey," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 3(1), pages 1-20.
    7. Nigmonov, Asror & Shams, Syed & Alam, Khorshed, 2022. "Macroeconomic determinants of loan defaults: Evidence from the U.S. peer-to-peer lending market," Research in International Business and Finance, Elsevier, vol. 59(C).
    8. Dietske Simons & Ferdinand Rolwes, 2009. "Macroeconomic efault Modeling and Stress Testing," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 177-204, September.
    9. Takashi Hashimoto, 2009. "Asset correlation for credit risk analysis -- Empirical study of default data for Japanese companies --," Bank of Japan Working Paper Series 09-E-3, Bank of Japan.
    10. Düllmann, Klaus & Koziol, Philipp, 2013. "Evaluation of minimum capital requirements for bank loans to SMEs," Discussion Papers 22/2013, Deutsche Bundesbank.
    11. Mustapha Ammari & Ghizlane Lakhnat, 2017. "Default-implied Asset Correlation: Empirical Study for Moroccan Companies," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 415-425.
    12. Salnikov, V. & Mogilat, A. & Maslov, I., 2012. "Stress Testing for Russian Real Sector: First Approach," Journal of the New Economic Association, New Economic Association, vol. 16(4), pages 46-70.
    13. Ming-Chin Hung & Yung-Kang Ching & Shih-Kuei Lin, 2021. "Impact of COVID-19 on the Robustness of the Probability of Default Estimation Model," Mathematics, MDPI, vol. 9(23), pages 1-13, November.

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    More about this item

    Keywords

    banking; credit risk; latent factor model; default rate;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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