Present-Biased Preferences and Credit Card Borrowing

By Stephan Meier, Charles D. Sprenger. Social Science Research Network, 2009

949 citations recorded by the source corpus.

Some individuals borrow extensively on their credit cards. This paper tests whether present-biased time preferences correlate with credit card borrowing. In a field study, we elicit individual time preferences with incentivized choice experiments, and match resulting time preference measures to individual credit reports and annual tax returns. The results indicate that present-biased individuals are more likely to have credit card debt, and have significantly higher amounts of credit card debt, controlling for disposable income, other socio-demographics, and credit constraints.

Subfields: Accounting, Economics and Econometrics, Gender Studies

View Paper: https://www.semanticscholar.org/paper/4c2f32751a87b6252b3eae9c44d63340f2ea85e8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

In Economics and Econometrics

In Gender Studies

Citations in the corpus

Under-Savers Anonymous: Evidence on Self-Help Groups and Peer Pressure as a Savings Commitment Device (2012, background): “3 Walsh et al. (1991) compare the effect of AA meetings to a hospital treatment.”
EXPONENTIAL-GROWTH BIAS AND LIFECYCLE CONSUMPTION (2015, positive): “has ranged between 1% and 4% during 2004–2010,1 and more than 40% of households are saving insufficiently to maintain their standard of living into retirement (Munnell et al., 2006). At the same time, revolving debt (predominantly credit card debt) in the United States reached $827 billion as of May”
Goal Setting and Energy Conservation (2014, background): “For example, Meier and Sprenger (2010) show that experimentally measured present bias is highly correlated with credit card borrowing, while Ikeda et al. (2010) find that procrastination is positively correlated with body mass index.”
Gender, Competitiveness and Career Choices (2012, neutral): “between education and competitiveness, which is an attribute for which large gender differences in the laboratory have been widely documented (see Croson and Gneezy, 2009 and Niederle and Vesterlund, 2011). Through in-class experiments we collected data on the competitiveness of high school students”
Financial Literacy and Retirement Planning in Switzerland (2013, neutral): “In line with evidence by Meier and Sprenger (2010) we find that impulsive households are more likely to have a consumer loan.”