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An empirical model of household arrears

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  • John Whitley
  • Richard Windram
  • Prudence Cox
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    Abstract

    Household arrears on payment obligations are one of the most direct measures of household sector financial stress. In this paper a time series approach is used to model two of the key components of aggregate UK household arrears: those on mortgages and credit cards. Mortgages are the main component of secured borrowing by households and credit cards are a key element in unsecured borrowing. Recent data show that both secured and unsecured debt have risen substantially, both absolutely and as a proportion of income since 1997. Unsecured debt has increased more rapidly over this period and so has become more important in overall household debt. During this period of rapid debt accumulation, the proportion of mortgage loans in arrears has fallen but the value of credit card arrears relative to the value of active card balances has risen. These differences in the behaviour of arrears are explained by reference to the underlying driving forces identified in previous empirical work. In particular the level of housing equity appears to be more important in explaining mortgage arrears, and the role of supply factors is highlighted for credit card arrears. Although the estimated models confirm that both income and interest repayments (and therefore income gearing) are important factors in explaining both forms of arrears, unemployment only plays an additional role for mortgage arrears. Joint testing of the two models suggests a role for the ratio of the value of the mortgage loan to the value of housing equity for both kinds of arrears, but with opposing effects. In the case of mortgage arrears this might reflect the lenders' perceptions of the quality of the borrower. Credit card arrears appear to contain some information about future mortgage arrears although the reverse does not hold. Both equations adjust relatively quickly to any shocks, typically in around two years. The significance of the income-gearing term for both types of arrears underlines the importance of the path of interest rates for the financial position of the UK household sector.

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    Bibliographic Info

    Paper provided by Bank of England in its series Bank of England working papers with number 214.

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    Date of creation: Mar 2004
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    Handle: RePEc:boe:boeewp:214

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    References

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    1. David B. Gross & Nicholas S. Souleles, 1999. "An Empirical Analysis of Personal Bankruptcy and Delinquency," Center for Financial Institutions Working Papers 98-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Donald P. Morgan & Ian Toll, 1997. "Bad debt rising," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 3(Mar).
    3. Lambrecht, Bart & Perraudin, William & Satchell, Stephen, 1997. "Time to default in the UK mortgage market," Economic Modelling, Elsevier, vol. 14(4), pages 485-499, October.
    4. Brookes, Martin & Dicks, Mike & Pradhan, Mahmood, 1994. "An empirical model of mortgage arrears and repossessions," Economic Modelling, Elsevier, vol. 11(2), pages 134-144, April.
    5. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    6. David B. Gross & Nicholas S. Souleles, 2001. "Do Liquidity Constraints and Interest Rates Matter for Consumer Behavior? Evidence from Credit Card Data," NBER Working Papers 8314, National Bureau of Economic Research, Inc.
    7. Sandra Black & Donald Morgan, 1998. "Risk and the democratization of credit cards," Research Paper 9815, Federal Reserve Bank of New York.
    8. Lucia Dunn & TaeHyung Kim, 1999. "Empirical Investigation of Credit Card Default," Working Papers 99-13, Ohio State University, Department of Economics.
    9. Elizabeth Laderman, 1996. "What's behind problem credit card loans?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue jul19.
    10. Kremers, Jeroen J M & Ericsson, Neil R & Dolado, Juan J, 1992. "The Power of Cointegration Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 325-48, August.
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    Cited by:
    1. Aron, Janine & Muellbauer, John, 2010. "Modelling and Forecasting UK Mortgage Arrears and Possessions," CEPR Discussion Papers 7986, C.E.P.R. Discussion Papers.
    2. Reamonn Lyndon & Yvonne McCarthy, 2013. "What Lies Beneath? Understanding Recent Trends in Irish Mortgage Arrears," The Economic and Social Review, Economic and Social Studies, vol. 44(1), pages 117–150.
    3. Giarda, Elena, 2013. "Persistency of financial distress amongst Italian households: Evidence from dynamic models for binary panel data," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3425-3434.
    4. Rodriguez, Adolfo & Trucharte, Carlos, 2007. "Loss coverage and stress testing mortgage portfolios: A non-parametric approach," Journal of Financial Stability, Elsevier, vol. 3(4), pages 342-367, December.
    5. Kelly, John & Reilly, Aisling, 2005. "Credit Card Debt in Ireland," Quarterly Bulletin Articles, Central Bank of Ireland, pages 85-100, February.
    6. Petr Kadeřábek & Aleš Slabý & Josef Vodička, 2008. "Stress testing of probability of default of individuals," Prague Economic Papers, University of Economics, Prague, vol. 2008(4), pages 340-355.

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