In the U.S., nearly 11% of school-age children have been diagnosed with ADHD, and approximately 10% of children suffer from asthma. In the last decade, the number of children diagnosed with these conditions has inexplicably been on the rise. This paper proposes a novel explanation of this trend. First, the increase is concentrated in the Medicaid caseload nationwide. Second, nearly 80% of states transitioned their Medicaid programs from fee-for-service (FFS) reimbursement to managed care (MMC) by 2016.

We propose a model of job search with reference-dependent preferences, with loss aversion relative to recent income (the reference point). In this model, newly unemployed individuals search hard since consumption is below their reference point. Over time, though, they get used to lower income and thus reduce their search effort. In anticipation of a benefit cut, their search effort rises again, then declines once they get accustomed to the lower postcut benefit level. The model fits the typical pattern of exit from unemployment, even with no unobserved heterogeneity.

This paper analyzes the non-market benefits of education and ability. Using a dynamic model of educational choice we estimate returns to education that account for selection bias and sorting on gains. We investigate a range of non-market outcomes including incarceration, mental health, voter participation, trust, and participation in welfare. We find distinct patterns of returns that depend on the levels of schooling and ability. Unlike the monetary benefits of education, the benefits to education for many non-market outcomes are greater for low-ability persons.

We examine multi-generational impacts of positive in utero and early life health interventions. We focus on the 1980s Medicaid expansions, which targeted low-income pregnant women, and were adopted differently across states and over time. We use Vital Statistics Natality files to create unique data linking individuals’ in utero Medicaid exposure to the next generation’s health outcomes at birth.

Women who graduate from university are less likely than men to specialize in science, technology, engineering, or math (STEM). We use detailed administrative data for a recent cohort of high school students in Ontario, Canada, combined with data from the province's university admission system to analyze the dynamic process leading to this gap. We show that entry to STEM programs is mediated through an index of STEM readiness based on end-of-high-school courses in math and science.