A Model of Mortgage Default
By John Y. Campbell, João F. Cocco. Journal of Finance, 2015
448 citations recorded by the source corpus.
This paper solves a dynamic model of a household's decision to default on its mortgage, taking into account labor income, house price, inflation, and interest rate risk. Mortgage default is triggered by negative home equity, which results from declining house prices in a low inflation environment with large mortgage balances outstanding. Not all households with negative home equity default, however. The level of negative home equity that triggers default depends on the extent to which households are borrowing constrained. High loan-to-value ratios at mortgage origination increase the probability of negative home equity. High loan-to-income ratios also increase the probability of default by tightening borrowing constraints. Comparing mortgage types, adjustable-rate mortgage defaults occur when nominal interest rates increase and are substantially affected by idiosyncratic shocks to labor income. Fixed-rate mortgages default when interest rates and inflation are low, and create a higher probability of a default wave with a large number of defaults. Interest-only mortgages trade off an increased probability of negative home equity against a relaxation of borrowing constraints, but overall have the highest probability of a default wave.
Subfields: Accounting, Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/fab43496c7571a1a01553197d99985df50956dbc
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Citations in the corpus
- Predictably Unequal? The Effects of Machine Learning on Credit Markets (2020, unknown): “(5) 35An alternative approach is to suppose that lenders estimate a full structural model of borrower characteristics and behavior (e.g., Campbell and Cocco, 2015), and then to map its parameters into predicted default rates P (x,R).”
- Housing, Finance and the Macroeconomy (2014, unknown): “Similar to Campbell and Cocco (2003), the size of housing is fixed. The authors allow households each period to choose their downpayment (which then implies a particular fixed mortgage payment) and then solve for the zero-profit mortgage rate associated with each mortgage.(40) Similar to Li and Yao ”
- Mortgage Design in an Equilibrium Model of the Housing Market (2018, unknown): “Mian and Sufi (2015) advocate for modifications through principal reduction, while Eberly and Krishnamurthy (2014) advocate for monthly payment reductions. Greenwald (2016) advocates for payment-to-income constraints as macroprudential policy to reduce house price volatility.”
- The Mortgage Credit Channel of Macroeconomic Transmission (2016, unknown): “…of households, including Kaplan and Violante (2014) for a general asset; Laufer (2013) and Gorea and Midrigan (2015) for one-period debt; and Campbell and Cocco (2015), Chatterjee and Eyigungor (2015), Chen, Michaux, and Roussanov (2013), Guler (2014), Elenev, Landvoigt, and Van…”
- Noncognitive Abilities and Financial Delinquency: The Role of Self-Efficacy in Avoiding Financial Distress (2017, unknown): “High self-efficacy has been shown to predict better physical and mental health (Taylor and Seeman (2000)), better academic achievements (Kalil and Khalid (2010)), higher job satisfaction and job performance (Judge and Bono (2001)), and a less negative impact of encountering economic hardship or bein”
- Safer Ratios, Riskier Portfolios: Banks’ Response to Government Aid (2014, unknown): “This variable is available for both approved and denied applications and has been shown to be a good predictor of mortgage default (Campbell and Cocco, 2011).”
- Unemployment, Negative Equity, and Strategic Default (2013, background): “In a partial equilibrium setting, Campbell and Cocco [2011] modeled mortgage foreclosure structurally and found that: (i) negative equity alone; (ii) borrowing constraints in combination with negative equity; (iii) high debt to income ratios in combination with negative equity; (iv) remaining term a”
- Can't Pay or Won't Pay? Unemployment, Negative Equity, and Strategic Default (2018, background): “However, the magnitude of the interaction effect is sensitive to the points at which it is 28Examples include Corbae and Quintin (2009), Garriga and Schlagenhauf (2009), Chatterjee and Eyigungor (2011), Campbell and Cocco (2011), Hedlund (2011), Schelkle (2011), and Laufer (2012).”