How persistent is financial distress? We answer this question using data on the proximity to debt limits, household debt-income ratios, and the probability that given a past default, a household experiences repayment difficulties. We show that all of these measures indicate that household financial distress is an extremely persistent phenomenon. To what extent can standard theory, as represented by a basic incomplete-markets model in which consumers face state contingent borrowing limits, arising from default risk capture this observed persistence of financial distress? We show that the answer is "not well": None of a wide array of model variants is capable of capturing this aspect of consumer credit use. This is important, as these baseline models have informed policy discussions on how best to provide debt relief to mitigate consumer financial distress. We then show that a plausible extension of standard approach yields a better account for the persistence of financial distress [TBC].

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Using proprietary panel data, we show that many U.S. consumers experience financial distress (35% when distress is defined by having debt in severe delinquency, e.g.) at some point in their lives. However, most distress events are concentrated on a much smaller proportion of consumers in persistent trouble: fewer than 10% of borrowers account for half of all distress events. These facts can be largely accounted for in a straightforward extension of a workhorse model of unsecured debt with informal default that accommodates a simple form of heterogeneity in time preference. Received November 10, 2017; editorial decision November 12, 2018 by Editor Stijn Van Nieuwerburgh.

A t any time, wages differ dramatically across U.S. workers. Some differences in workers' hourly wages may be due to differences in observable characteristics such as age, sex, race, or education level. But substantial dispersion in wages across individuals persists after accounting for these differences. This wage dispersion prompts a range of questions. What is the source of this dispersion and does it matter where it comes from? Are hourly wages more dispersed today than in the past? In this article, we investigate the sources of wage dispersion for different demographic groups as well as how these sources have changed over time. To do so, we decompose residual wage dispersion-the variation in wages that is unexplained by standard demographic characteristics-to discover how much of the dispersion is due to "who you are" (also known as the permanent component) versus "where you work" (also known as the match-specific component). Our analysis of individual-level data from the Survey of Income and Program Participation (SIPP) suggests that the match-specific component is responsible for a substantial fraction of residual wage differences across individuals. Upon switching jobs, some individuals land more lucrative matches, while others earn less for the same work. We also find that residual wage dispersion is similar across sexes and education levels.