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Losses on Dutch residential mortgage insurances

Losses on Dutch residential mortgage insurances Purpose – This paper aims to study the data on losses on mortgage insurance in the Dutch housing market to find the key drivers of the probability of loss. In 2013, 25 per cent of all Dutch homeowners were “under water”: selling the property will not cover the outstanding mortgage debt. The double-trigger theory predicts that being under water is a necessary but not sufficient condition to predict mortgage default. A loss for the mortgage insurer is the result of a default where the proceedings of sale and the accumulated savings for postponed repayment of the principal associated to the loan are not sufficient to repay the loan. Design/methodology/approach – For this study, the authors use a data set on losses on mortgage insurance at a national aggregate level covering the period from 1976 to 2012. They apply a discrete time hazard model with calendar time- and duration-varying covariates to analyze the relationship between year of issue of the insurance, duration, equity, unfortunate events like unemployment and divorce and affordability measures to identify the main drivers of the probability of loss. Findings – Although the number of losses increases over time, the number of losses relative to the active insurance is still low, despite the fact that the Dutch housing market is the world’s most strongly leveraged housing market. On average, the peak in loss probability lies around a duration of four years. The average loss probability is virtually zero for durations larger than 10 years. Mortgages initiated just prior to the beginning of the financial crisis have an increased loss probability. The most important drivers of the loss probability are home equity, unemployment and divorce. Affordability measures are less important. Research limitations/implications – Mortgage insurance is available for the lower end of the market only and is intended to decrease the impact of risk selection by banks. The analysis is based on aggregate data; no information on individual households, like initial loan-to-value and price-to-income ratios; current home equity; and unfortunate events, like unemployment and divorce, is available. The research uses averages of these variables per calendar year and/or duration. Information on repayments of insured mortgages is missing. Originality/value – This paper is the first to describe the main drivers of losses on insured mortgages in The Netherlands by using loss data covering two housing market crises, one in the early 1980s and the current crisis that started in 2008. Much has changed between the two crises. For instance, prices have risen steeply as has household indebtedness. Furthermore, alternative mortgage products have increased in popularity. Focusing a study on the drivers of mortgage losses exclusively on the current crisis could therefore be biased, given the time-specific circumstances on the housing market. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of European Real Estate Research Emerald Publishing

Losses on Dutch residential mortgage insurances

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References (30)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1753-9269
DOI
10.1108/JERER-01-2014-0008
Publisher site
See Article on Publisher Site

Abstract

Purpose – This paper aims to study the data on losses on mortgage insurance in the Dutch housing market to find the key drivers of the probability of loss. In 2013, 25 per cent of all Dutch homeowners were “under water”: selling the property will not cover the outstanding mortgage debt. The double-trigger theory predicts that being under water is a necessary but not sufficient condition to predict mortgage default. A loss for the mortgage insurer is the result of a default where the proceedings of sale and the accumulated savings for postponed repayment of the principal associated to the loan are not sufficient to repay the loan. Design/methodology/approach – For this study, the authors use a data set on losses on mortgage insurance at a national aggregate level covering the period from 1976 to 2012. They apply a discrete time hazard model with calendar time- and duration-varying covariates to analyze the relationship between year of issue of the insurance, duration, equity, unfortunate events like unemployment and divorce and affordability measures to identify the main drivers of the probability of loss. Findings – Although the number of losses increases over time, the number of losses relative to the active insurance is still low, despite the fact that the Dutch housing market is the world’s most strongly leveraged housing market. On average, the peak in loss probability lies around a duration of four years. The average loss probability is virtually zero for durations larger than 10 years. Mortgages initiated just prior to the beginning of the financial crisis have an increased loss probability. The most important drivers of the loss probability are home equity, unemployment and divorce. Affordability measures are less important. Research limitations/implications – Mortgage insurance is available for the lower end of the market only and is intended to decrease the impact of risk selection by banks. The analysis is based on aggregate data; no information on individual households, like initial loan-to-value and price-to-income ratios; current home equity; and unfortunate events, like unemployment and divorce, is available. The research uses averages of these variables per calendar year and/or duration. Information on repayments of insured mortgages is missing. Originality/value – This paper is the first to describe the main drivers of losses on insured mortgages in The Netherlands by using loss data covering two housing market crises, one in the early 1980s and the current crisis that started in 2008. Much has changed between the two crises. For instance, prices have risen steeply as has household indebtedness. Furthermore, alternative mortgage products have increased in popularity. Focusing a study on the drivers of mortgage losses exclusively on the current crisis could therefore be biased, given the time-specific circumstances on the housing market.

Journal

Journal of European Real Estate Research – Emerald Publishing

Published: Oct 28, 2014

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