This paper studies the role of job displacement in the household bankruptcy decision. Using an event-study methodology, I find that NLSY respondents are over three times more likely to file for bankruptcy immediately following a job loss. Using county-level data, I find similar magnitudes in the aggregate, with significant effects lasting two to three years. The results suggest that unemployment spells can have significant long-term consequences on households’ credit market outcomes.

This paper examines whether high-speed Internet affects students' college applications. Our analysis links the diffusion of residential broadband to the testing and application outcomes of millions of PSAT and SAT takers and reveals that students with broadband in their postal code perform better on the SAT and apply to a higher number and more expansive set of colleges. While the availability of broadband generally improved applications to college, the effects appear to be concentrated among high-SES students, suggesting that the new technology may have increased preexisting inequities.

We introduce a test of the rank invariance or rank similarity assumption common in treatment effects and instrumental variables models. The test probes the implication that the conditional distribution of ranks should be identical across treatment states using a regression-based test statistic. We apply the test to data from the Tennessee STAR class-size reduction experiment and show that systematic slippages in rank can be important statistically and economically.

We examine the housing market and residential mobility changes that occur soon after a Title 1 school fails to achieve adequate yearly progress (AYP) in Charlotte, North Carolina. Students within attendance zones of failing schools are given priority in lotteries for oversubscribed schools, potentially increasing the attractiveness of living in a failing school attendance zone. We find that housing prices, home buyer income, and the probability of attending a nonassigned school increase in the highest-quality neighborhoods within failing school attendance zones. Our results are driven largely by the behavior of new residents.

We formalize the optimal design of experiments when there is interference between units, i.e. an individual's outcome depends on the outcomes of others in her group. We focus on randomized saturation designs, two-stage experiments that first randomize treatment saturation of a group, then individual treatment assignment. We map the potential outcomes framework with partial interference to a regression model with clustered errors, calculate standard errors of randomized saturation designs, and derive analytical insights about the optimal design. We show that the power to detect average treatment effects declines precisely with the ability to identify novel treatment and spillover effects.

This paper presents a new approach to the measurement of the effects of spatial mismatch that takes advantage of matched employeremployee administrative data integrated with a person-specific job accessibility measure, as well as demographic and neighborhood characteristics. We focus on a group of job searchers for plausibly exogenous reasons: lower-income workers with strong labor force attachment separated during a mass layoff. Our results support the spatial mismatch hypothesis. We find that better job accessibility significantly decreases the duration of joblessness among lower-income displaced workers, especially for blacks, women, and older workers.