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. 2013 Jul 9;110(28):11267-71.
doi: 10.1073/pnas.1220568110. Epub 2013 Jun 24.

Numerical ability predicts mortgage default

Kristopher Gerardi  1 , Lorenz Goette, Stephan Meier
Affiliations

Numerical ability predicts mortgage default

Kristopher Gerardi et al. Proc Natl Acad Sci U S A. .

Abstract

Unprecedented levels of US subprime mortgage defaults precipitated a severe global financial crisis in late 2008, plunging much of the industrialized world into a deep recession. However, the fundamental reasons for why US mortgages defaulted at such spectacular rates remain largely unknown. This paper presents empirical evidence showing that the ability to perform basic mathematical calculations is negatively associated with the propensity to default on one's mortgage. We measure several aspects of financial literacy and cognitive ability in a survey of subprime mortgage borrowers who took out loans in 2006 and 2007, and match them to objective, detailed administrative data on mortgage characteristics and payment histories. The relationship between numerical ability and mortgage default is robust to controlling for a broad set of sociodemographic variables, and is not driven by other aspects of cognitive ability. We find no support for the hypothesis that numerical ability impacts mortgage outcomes through the choice of the mortgage contract. Rather, our results suggest that individuals with limited numerical ability default on their mortgage due to behavior unrelated to the initial choice of their mortgage.

Keywords: consumer finance; foreclosure; limited rationality; subprime loans.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
The evolution of subprime mortgage defaults in the United States. The graphs show the cumulative default rates, measured by the issuance of a foreclosure petition, across different years on a quarterly basis. Source: own calculations using the Corelogic dataset.
Fig. 2.
Fig. 2.
Numerical ability (NA) and mortgage default. Simple relationship (solid line) along with two regression-adjusted relationships between the NA index (1 is bottom and 4 top group in terms of NA) and measure of mortgage default is shown. The dashed line shows the regression-adjusted relationship controlling for borrower characteristics [age, sex, ethnicity, education, marital status, the size of the household, time and risk preference parameters, labor market status over the previous 5 y, the household’s income, the subjective measure of income volatility, FICO score, and dummy variables for whether the borrower is an investor (owner occupant as the reference group), as well as whether the mortgage is for a home purchase]. The dotted line shows the regression-adjusted relationship controlling for borrower characteristics and mortgage characteristics (fixed-rate mortgage vs. adjustable-rate mortgage, mortgage amount, presence of prepayment penalties, documentation status, initial interest rate, loan-to-value ratio, debt-to-income ratio). SEs (gray) overlap for the three models. A shows the probability of delinquency, and B shows the incidence of foreclosure. Source: own calculations.
See this image and copyright information in PMC

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