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Assessing household credit risk: evidence from a household survey


  • Dániel Holló

    () (Magyar Nemzeti Bank)

  • Mónika Papp

    () (Magyar Nemzeti Bank)


This paper investigates the main individual driving forces of Hungarian household credit risk and measures the shockabsorbing capacity of the banking system in relation to adverse macroeconomic events. The analysis relies on survey evidence gathered by the Magyar Nemzeti Bank (MNB) in January 2007. Our study presents three alternative ways of modelling household credit risk, namely the financial margin, the logit and the neural network approaches, and uses these methods for stress testing. Our results suggest that the main individual factors affecting household credit risk are disposable income, the income share of monthly debt servicing costs, the number of dependants and the employment status of the head of the household. The findings also indicate that the current state of indebtedness is unfavourable from a financial stability point of view, as a relatively high proportion of debt is concentrated in the group of risky households. However, risks are somewhat mitigated by the fact that a substantial part of risky debt is comprised of mortgage loans, which are able to provide considerable security for banks in the case of default. Finally, our findings reveal that the shock-absorbing capacity of the banking sector, as well as individual banks, is sufficient under the given loss rate (LGD) assumptions (i.e. the capital adequacy ratio would not fall below the current regulatory minimum of 8 per cent) even if the most extreme stress scenarios were to occur.

Suggested Citation

  • Dániel Holló & Mónika Papp, 2008. "Assessing household credit risk: evidence from a household survey," MNB Occasional Papers 2008/70, Magyar Nemzeti Bank (Central Bank of Hungary).
  • Handle: RePEc:mnb:opaper:2008/70

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    References listed on IDEAS

    1. Afonso, Antonio & Strauch, Rolf, 2007. "Fiscal policy events and interest rate swap spreads: Evidence from the EU," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(3), pages 261-276, July.
    2. Heppke-Falk, Kirsten H. & Hüfner, Felix P., 2004. "Expected budget deficits and interest rate swap spreads - Evidence for France, Germany and Italy," Discussion Paper Series 1: Economic Studies 2004,40, Deutsche Bundesbank.
    3. John Kambhu, 2004. "Trading risk and volatility in interest rate swap spreads," Staff Reports 178, Federal Reserve Bank of New York.
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    More about this item


    financing stability; financial margin; logit model; neural network; stress test.;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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