This paper examines the implicit health insurance that households receive from the ability to declare bankruptcy. Exploiting multiple sources of variation in asset exemption law, I show that uninsured households with a greater financial cost of bankruptcy make higher out-of-pocket medical payments, conditional on the amount of care received. In turn, I find that households with greater wealth at risk are more likely to hold health insurance. The implicit insurance from bankruptcy distorts the insurance coverage decision. Using a microsimulation model, I calculate that the optimal Pigovian penalties are three-quarters as large as the average penalties under the Affordable Care Act.

Many organizations have budgets that expire at the end of the fiscal year and may face incentives to rush to spend resources on low-quality projects at year's end. We test these predictions using data on procurement spending by the US federal government. Spending in the last week of the year is 4.9 times higher than the rest-of-the-year weekly average, and year-end information technology projects have substantially lower quality ratings. We also analyze the gains from allowing agencies to roll over unused funds into the next fiscal year. (JEL H57, H61)

Abstract Two in five Americans have medical debt, nearly half of whom owe at least $2,500. Concerned by this burden, governments and private donors have undertaken large, high-profile efforts to relieve medical debt. We partnered with RIP Medical Debt (now Undue Medical Debt) to conduct two randomized experiments that relieved medical debt with a face value of $169 million for 83,401 people between 2018 and 2020. Our experiments focused on downstream medical debt that had been sold to debt collectors, and one of our experiments straddled an industry-wide pullback in the reporting of medical debt to the credit bureaus, allowing us to estimate the effects of debt relief with and without counterfactual reporting. We track outcomes using credit reports, collections account data, and a multimodal survey. There are three sets of results. First, we find a modest improvement in credit access when there is counterfactual credit reporting, but no impact on credit report outcomes when there is not. Second, we estimate that debt relief causes a moderate but statistically significant reduction in payments of existing medical bills. Third, we find no effects on survey measures of mental and physical health, healthcare utilization, and financial wellness. Taken together, our results indicate that the strong correlations documented in prior research do not translate into causal effects for downstream medical debt relief.

Policies to correct market power and selection can be misguided when these forces coexist. We build a model of symmetric imperfect competition in selection markets that parameterizes the degree of market power and selection. We use graphical price-theoretic reasoning to characterize the interaction between these forces. Using a calibrated model of health insurance, we show that the risk adjustment commonly used to offset adverse selection can reduce coverage and social surplus. Conversely, in a calibrated model of subprime auto lending, realistic levels of competition can generate an oversupply of credit, implying that greater market power is desirable.

We use credit report data to study consumer financial distress in America. We report large, persistent disparities in financial distress across regions. To understand these patterns, we conduct a “movers” analysis. For collections and default, there is only weak convergence following a move, suggesting these types of distress are not primarily caused by place-based factors (e.g., local economic conditions and state laws) but instead reflect person-based characteristics (e.g., financial literacy and risk preferences). In contrast, for personal bankruptcy, we find a sizable place-based effect, which is consistent with anecdotal evidence on how local legal factors influence personal bankruptcy.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

ABSTRACT We study the financial and labor market impacts of bad credit reports. Using difference‐in‐differences variation from the staggered removal of bankruptcy flags, we show that bankruptcy flag removal leads to economically large increases in credit limits and borrowing. Using administrative tax records linked to personal bankruptcy records, we estimate economically small effects of flag removal on employment and earnings outcomes. We rationalize these contrasting results by showing that, conditional on basic observables, “hidden” bankruptcy flags are strongly correlated with adverse credit market outcomes but have no predictive power for measures of job performance.

We study one benefit to firms of selling subscriptions: the prospect that consumers will continue to pay for subscriptions they no longer value. We use comprehensive data from a large payment card network to document that months during which cards are replaced, when active renewal is required, are associated with much higher rates of cancellation. Using two stylized models of consumer inertia—driven by inattention or switching costs—we estimate that these cancellation frictions roughly double seller revenues on average, holding fixed initial subscribers. We use the estimated models to explore the impact of possible regulatory remedies. (JEL D12, D18, L81, L88)

A central question in the debate over privatized Medicare is whether increased government payments to private Medicare Advantage (MA) plans generate lower premiums for consumers or higher profits for producers. Using difference‑in‑differences variation brought about by a sharp legislative change, we find that MA insurers pass through 45 percent of increased payments in lower premiums and an additional 9 percent in more generous benefits. We show that advantageous selection into MA cannot explain this incomplete pass‑through. Instead, our evidence suggests that market power is important, with premium pass‑through rates of 13 percent in the least competitive markets and 74 percent in the most competitive.

The ability of web-based retailers to learn about and provide targeted consumer experiences is touted as an important distinction from traditional retailers. In principal, web-based insurance exchanges could benefit from these advantages. Using data from a large-scale experiment by a private sector health insurance exchange we estimate the returns to experimentation and targeted messaging. We find significant improvements in conversions in one treatment tested. Underlying the average impact were both intertemporal and demographic heterogeneity. We estimate that learning and targeted messaging could increase insurance applications by approximately 13 percent of the baseline conversion rate.

We develop a stylized model that allows us to estimate a value-added measure for nursing homes ("SNFs") which accounts for patient selection both into and out of a SNF. We use the model, together with detailed data on the physical and mental health of about 6 million Medicare SNF patients between 2011 and 2016, to estimate the value added for about 14,000 distinct SNFs. We document substantial heterogeneity in value added. Nationwide, compared to a 10th percentile SNF, a 90th percentile SNF is able to discharge a patient at the same health level almost a week sooner, or one quarter of the median length of stay. Heterogeneity in value added within a market is almost as large as it is nationwide. Our results point to the potential for substantial gains through policies that encourage reallocation of patients to higher-quality SNFs within their market.