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Consumer Debt and Default: A Macro Perspective

Authors: Exler, Florian; Tertilt, Michèle;

Consumer Debt and Default: A Macro Perspective

Abstract

Consumer debt is an important means for consumption smoothing. In the United States, 70% of households own a credit card, and 40% borrow on it. When borrowers cannot (or do not want to) repay their debts, they can declare bankruptcy, which provides additional insurance in tough times. Since the 2000s, up to 1.5% of households declared bankruptcy per year. Clearly, the option to default affects borrowing interest rates in equilibrium. Consequently, when assessing (welfare) consequences of different bankruptcy regimes or providing policy recommendations, structural models with equilibrium default and endogenous interest rates are needed. At the same time, many questions are quantitative in nature: the benefits of a certain bankruptcy regime critically depend on the nature and amount of risk that households bear. Hence, models for normative or positive analysis should quantitatively match some important data moments. Four important empirical patterns are identified: First, since 1950, consumer debt has risen constantly, and it amounted to 25% of disposable income by 2016. Defaults have risen since the 1980s. Interestingly, interest rates remained roughly constant over the same time period. Second, borrowing and default clearly depend on age: both measures exhibit a distinct hump, peaking around 50 years of age. Third, ownership of credit cards and borrowing clearly depend on income: high-income households are more likely to own a credit card and to use it for borrowing. However, this pattern was stronger in the 1980s than in the 2010s. Finally, interest rates became more dispersed over time: the number of observed interest rates more than quadrupled between 1983 and 2016. These data have clear implications for theory: First, considering the importance of age, life cycle models seem most appropriate when modeling consumer debt and default. Second, bankruptcy must be costly to support any debt in equilibrium. While many types of costs are theoretically possible, only partial repayment requirements are able to quantitatively match the data on filings, debt levels, and interest rates simultaneously. Third, to account for the long-run trends in debts, defaults, and interest rates, several quantitative theory models identify a credit expansion along the intensive and extensive margin as the most likely source. This expansion is a consequence of technological advancements. Many of the quantitative macroeconomic models in this literature assess welfare effects of proposed reforms or of granting bankruptcy at all. These welfare consequences critically hinge on the types of risk that households face—because households incur unforeseen expenditures, not-too-stringent bankruptcy laws are typically found to be welfare superior to banning bankruptcy (or making it extremely costly) but also to extremely lax bankruptcy rules. There are very promising opportunities for future research related to consumer debt and default. Newly available data in the United States and internationally, more powerful computational resources allowing for more complex modeling of household balance sheets, and new loan products are just some of many promising avenues.

Countries
Germany, Austria
Keywords

502009 Corporate finance, bankruptcy law, 330, ddc:330, 502018 Macroeconomics, O30, 502018 Makroökonomie, chapter 7, delinquency, unsecured debt, interest rates, charge-offs, C60, 502009 Finanzwirtschaft, bankruptcy, G20, credit cards, consumer debt, default, E20, Chapter 7

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
bronze