What 'Triggers' Mortgage Default?

Elul, Ronel; Souleles, Nicholas S.; Chomsisengphet, Souphala; Glennon, Dennis; Hunt, Robert M.

doi:10.2139/ssrn.1596707

Cited by 137 publications

(166 citation statements)

References 13 publications

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“…At higher levels of negative home equity, default rates increase and the di¤erence in …nancial distress between defaulters and non-defaulters disappears. Bajari et al (2008), Bhutta et al (2010), Elul et al (2010), and Foote et al (2008) …nd patterns consistent with these predictions in recent US data. Li et al (2010) argue that the reform of the US bankruptcy code in 2005 made it harder for borrowers to escape non-housing debt through bankruptcy; by tightening constraints on indebted borrowers, the bankruptcy reform decreased the trigger level of negative home equity and increased defaults in the late 2000s.…”

Section: Defaultsupporting

confidence: 81%

Mortgage Market Design

Campbell¹

2012

119

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This paper explores the causes and consequences of cross-country variation in mortgage market structure. It draws on insights from several fields: urban economics, asset pricing, behavioral finance, financial intermediation, and macroeconomics. It discusses lessons from the credit boom, the challenges of mortgage modification in the aftermath of the boom, consumer financial protection, and alternative mortgage forms and funding models. The paper argues that the US has much to learn from mortgage finance in other countries, and specifically from the Danish implementation of the European covered bonds system.

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Section: Defaultsupporting

confidence: 81%

Mortgage Market Design

Campbell¹

2012

119

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“…The big jump in the default rate comes when the loan has both low affordability and large negative equity: the joint effect seems much bigger than the sum of the two individual effects. This conforms to Foote's (2008) dual-trigger model of default, and supports the US-based findings of Bhutta et al (2010) and Elul et al (2010). The probit model which we use below also captures this empirical feature.…”

Section: Estimation Of the Modelsupporting

confidence: 88%

“…(7) in Section 3.2). The results are suggestive, but not definitive, regarding a convex nonlinearity in the link between loan-to-value and loan default; see Elul et al (2010) for related evidence for the US market using different estimation methods (step-wise linearity over intervals in a logit model). The coefficient estimates for the other five variables (for which the linearity assumption is maintained) are shown in the supplementary tables in the unpublished appendix (Connor and Flavin, 2014).…”

Section: Estimation Of the Modelmentioning

confidence: 88%

“…Towe and Lawley (2010) also find that social interactions play a significant role in the decision to default, in that having a neighbor in foreclosure increases the probability of default by 28%. Elul et al (2010) use an econometric framework somewhat similar to our own. They define default as accumulated arrears of 60 days or more, and estimate a logit model of binary default outcomes based on individualcredit-record data, together with nationwide quarterly interest rate data and quarterly US state-level unemployment rate changes.…”

Section: Default Behavior Of Mortgage Borrowersmentioning

confidence: 99%

“…Lydon and McCarthy (2011) provide an analysis of Irish mortgage market default based on data collected from four Irish banks during the Central Bank of Ireland's 2010 stresstesting review of the domestic banking sector. Like Elul et al (2010) and this paper they use a static probit model of mortgage default based on individual loan characteristics. They argue that their static probit model results support a dualtrigger model of default in which both unaffordability and strategic motives (i.e.…”

Section: Default Behavior Of Mortgage Borrowersmentioning

confidence: 99%

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Strategic, unaffordability and dual-trigger default in the Irish mortgage market

Connor

Flavin

2015

Journal of Housing Economics

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a b s t r a c tA mortgage holder whose property is worth less than the repayment value of the mortgage may decide to strategically default, i.e., renege on the cash flow liability of the mortgage loan and surrender the property to the mortgage issuer. In other circumstances a mortgage holder may default due to personal income decline which makes payment infeasible (unaffordability default) or for a combination of strategic and affordability causes (dual-trigger default). This paper utilizes a database of troubled Irish mortgages to model the default decisions of Irish mortgage holders. We include both affordabilityrelated and strategic-related explanatory variables. We find that both types of explanatory variables play a role in the explosive growth in Irish mortgage default after the Irish banking crisis and temporary legal prohibition of property repossession. We find that a dual-trigger model of default best fits the Irish data. Given the unusual features of the Irish market, our findings both complement and strengthen existing empirical findings from other national mortgage markets.

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Systemic Financial Risk Arising from Residential Flood Losses

Thomson

Zeff

Kleiman

et al. 2022

Preprint

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Flood impacts to residential properties threaten the resilience of communities and the institutions that support them. These events can cause negative impacts to property-level balance sheets through uninsured damage and property value decreases, which in turn can increase the likelihood of mortgage default and property abandonment. To date, there have been limited attempts to quantify the magnitude and distribution of additional financial consequences that could arise from these processes following flood events. In this work, property-scale financial data, including property sales, mortgage originations, and insurance claims, are used within an analytical framework to quantify flood-related uninsured damages and property value decrease in order to estimate the financial risk that property owners, mortgage lenders, and local governments are exposed to via recovery decisions (i.e., default and/or abandonment). This framework is applied to residential properties in eastern North Carolina following Hurricane Florence (2018). Within the study area, Hurricane Florence generated $366M in observed insured losses and we estimate an additional $1.77B in balance sheet losses (i.e., uninsured damage and property value decrease). In addition, property owners, mortgage lenders, and local governments were exposed to an estimated $562M of risk from the increased likelihood of mortgage default and property abandonment. Areas with lower pre-event property values and lower rates of insurance purchase experienced significantly higher risk of mortgage default and abandonment. The method described provides more highly resolved estimates of how floods can drive systemic financial risk, information that can be useful in developing improved flood resilience strategies.

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What 'Triggers' Mortgage Default?

Cited by 137 publications

References 13 publications

Mortgage Market Design

Mortgage Market Design

Strategic, unaffordability and dual-trigger default in the Irish mortgage market

Systemic Financial Risk Arising from Residential Flood Losses

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