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Modelling and Forecasting Mortgage Delinquency and Foreclosure in the UK

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  • Aron, Janine
  • Muellbauer, John

Abstract

In the absence of micro-data in the public domain, new aggregate models for the UK's mortgage repossessions and arrears are estimated using quarterly data over 1983-2014, motivated by a conceptual double trigger frame framework for foreclosures and payment delinquencies. An innovation to improve on the flawed but widespread use of loan-to-value measures, is to estimate difficult-to-observe variations in loan quality and access to refinancing, and shifts in lenders' forbearance policy, by common latent variables in a system of equations for arrears and repossessions. We introduce, for the first time in the literature, a theory-justified estimate of the proportion of mortgages in negative equity as a key driver of aggregate repossessions and arrears. This is based on an average debt-equity ratio, corrected for regional deviations, and uses a functional form for the distribution of the debt-equity ratio checked on Irish micro-data from the Bank of Ireland, and Bank of England snapshots of negative equity. We systematically address serious measurement bias in the 'months-in-arrears' measures, neglected in previous UK studies. Highly significant effects on aggregate rates of repossessions and arrears are found for the aggregate debt-service ratio, the proportion of mortgages in negative equity and the unemployment rate. Economic forecast scenarios to 2020 highlight risks faced by the UK and its mortgage lenders, illustrating the usefulness of the approach for bank stress-testing. For macroeconomics, our model traces an important part of the financial accelerator: the feedback from the housing market to bad loans and hence banks' ability to extend credit.

Suggested Citation

  • Aron, Janine & Muellbauer, John, 2016. "Modelling and Forecasting Mortgage Delinquency and Foreclosure in the UK," CEPR Discussion Papers 11236, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11236
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Bracke, Philippe & Hilber, Christian A.L. & Silva, Olmo, 2018. "Mortgage debt and entrepreneurship," Journal of Urban Economics, Elsevier, vol. 103(C), pages 52-66.
    2. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
    3. Muellbauer, John, 2016. "Macroeconomics and Consumption," CEPR Discussion Papers 11588, C.E.P.R. Discussion Papers.
    4. Irina Stanga & Razvan Vlahu & Jakob de Haan, 2017. "Mortgage arrears, regulation and institutions: Cross-country evidence," DNB Working Papers 580, Netherlands Central Bank, Research Department.

    More about this item

    Keywords

    credit risk stress testing; foreclosures; latent variables model; mortgage arrears; mortgage payment delinquencies; mortgage repossessions;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • 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
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R28 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Government Policy

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