Research

Increasing use of biofuels increases the demand for agricultural land. Credible empirical evidence supports the common-sense judgment that this will lead to the conversion of forests and other habitats to generate more cropland, particularly in the tropics, where land conversion is cheapest. However, when analyzing the effects of biofuels on land use, governments frequently use a particular class of economic models, including the popular “GTAP” model, to justify a finding that biofuels will cause little additional land conversion. We argue that the GTAP model does not provide a credible scientific basis for this conclusion because it lacks an econometric basis for its economic parameters, generates physically impossible results by a wide margin, and incorporates several unsupported assumptions that guarantee little land use change, such as constraints on international trade and a failure to account for unmanaged forests.

We analyze the economic consequences of rising US health care prices. By increasing the cost of employer-sponsored health insurance, rising prices serve as a de facto payroll tax on labor. Using exposure to hospital mergers as an instrument, we estimate that a 1% increase in health care prices lowers payroll and employment at non-health-care employers by 0.4%. At the county level, a 1% increase in health care prices reduces labor income by 0.27%, increases flows into unemployment by 1%, and lowers federal income tax receipts by 0.4%. The disemployment effects of rising prices are concentrated among lower- and middle-income workers.

Importance  There is increased interest in public reporting of, and linking financial incentives to, the performance of organizations on health equity metrics, but variation across organizations could reflect differences in performance or selection bias.

Objective  To assess whether differences across health plans in sex- and age-adjusted racial disparities are associated with performance or selection bias.

Design, Setting, and Participants  This cross-sectional study leveraged a natural experiment, wherein a southern US state randomly assigned much of its Medicaid population to 1 of 5 plans after shifting to managed care in 2012. Enrollee-level administrative claims and enrollment data from 2011 to 2015 were obtained for self-identified Black and White enrollees. The analyses were limited to Black and White Medicaid enrollees because they accounted for the largest percentages of the population and could be compared with greater statistical power than other groups. Data were analyzed from June 2021 to September 2024.

Exposures  Plan enrollment via self-selection (observational population) vs random assignment (randomized population).

Main Outcomes and Measures  Annual counts of primary care visits, low-acuity emergency department visits, prescription drug fills, and total spending. For observational and randomized populations, models of each outcome were fit as a function of plan indicators, indicators for race, interactions between plan indicators and race, and age and sex. Models estimated the magnitude of racial differences within each plan and tested whether this magnitude varied across plans.

Results  Of 118 101 enrollees (mean [SD] age, 9.3 [7.5] years; 53.0% female; 61.4% non-Hispanic Black; and 38.6% non-Hispanic White), 70.2% were included in the randomized population, and 29.8% were included in the observational population. Within-plan differences in primary care visits, low-acuity emergency department visits, prescription drug use, and total spending between Black and White enrollees were large but did not vary substantially and were not statistically significantly different across plans in the randomized population, suggesting minimal effects of plans on racial differences in these measures. In contrast, in the observational population, racial differences varied substantially across plans (standard deviations 2-3 times greater than in the randomized population); this variation was statistically significant after adjustment for multiple testing, except for emergency department visits. Greater between-plan variation in racial differences in the observational population was only partially explained by sampling error. Stratifying by race did not bring observational estimates of plan effects meaningfully closer to randomized estimates.

Conclusions and Relevance  This cross-sectional study showed that selection bias may mischaracterize plans’ relative performance on measures of health care disparities. It is critical to address disparities in Medicaid, but adjusting plan payments based on disparity measures may have unintended consequences.

Importance  Work requirements are a controversial feature of US safety-net programs, with some policymakers seeking to expand their use. Little is known about the demographic, clinical, and socioeconomic characteristics of individuals most likely to be negatively impacted by work requirements.

Objective  To examine the association between work requirements and safety-net program enrollment.

Design, Setting, and Participants  This cohort study included Medicaid and Supplemental Nutrition Assistance Program (SNAP) enrollees in Connecticut. The impact of SNAP work requirements for able-bodied adults without dependents—the target population—was estimated using a triple-differences research design comparing outcomes before and after the policy (first difference) in affected and exempted towns (second difference) between the targeted population and untargeted parents and caregivers (third difference). SNAP and Medicaid enrollment trends were assessed for a 24-month period, and the characteristics of individuals most likely to lose coverage were examined. Data were collected from August 2015 to April 2018, and data were analyzed from August 2022 to September 2024.

Exposures  The reintroduction of SNAP work requirements in 2016.

Main Outcomes and Measures  Proportion of enrollees disenrolled from SNAP and Medicaid.

Results  Of 81 888 Medicaid enrollees in Connecticut, 46 872 (57.2%) were female, and the mean (SD) age was 36.6 (7.0) years. Of these, 38 344 were able-bodied adults without dependents, of which 19 172 were exposed to SNAP work requirements, and 43 544 were parents or caregivers exempted from SNAP work requirements. SNAP coverage declined 5.9 percentage points (95% CI, 5.1-6.7), or 25%, following work requirements. There were no statistically significant changes in Medicaid coverage (0.2 percentage points; 95% CI, −1.4 to 1.0). Work requirements disproportionately affected individuals with more chronic illnesses, targeted beneficiaries who were older, and beneficiaries with lower incomes. Individuals with diabetes were 5 percentage points (95% CI, 0.8-9.3), or 91%, likelier to lose SNAP coverage than those with no chronic conditions; older SNAP beneficiaries (aged 40 to 49 years) with multiple comorbidities were 7.3 percentage points (95% CI, 4.3-11.3), or 553%, likelier to disenroll than younger beneficiaries (aged 25 to 29 years) without chronic conditions; and households with the lowest incomes were 18.6 percentage points (95% CI, 11.8-25.4), or 204%, likelier to lose coverage than the highest income SNAP beneficiaries.

Conclusions and Relevance  In this cohort study, SNAP work requirements led to substantial reductions in SNAP coverage, especially for the most clinically and socioeconomically vulnerable. Work requirements had little effect on Medicaid coverage, suggesting they did not lead to sufficient increases in employment to transition beneficiaries off the broader safety net.

This paper asks whether universal pre-kindergarten (UPK) raises parents' earnings and how much these earnings effects matter for evaluating the economic returns to UPK programs. Using a randomized lottery design, we estimate the effects of enrolling in a full-day UPK program in New Haven, Connecticut on parents' labor market outcomes as well as educational expenditures and children's academic performance. During children's pre-kindergarten years, UPK enrollment increases weekly childcare coverage by 11 hours. Enrollment has limited impacts on children's academic outcomes between kindergarten and 8th grade, likely due to a combination of rapid effect fadeout and substitution away from other programs of similar quality but with shorter days. In contrast, parents work more hours, and their earnings increase by 21.7%. Parents' earnings gains persist for at least six years after the end of pre-kindergarten. Excluding impacts on children, each dollar of net government expenditure yields $5.51 in after-tax benefits for families, almost entirely from parents' earnings gains. This return is large compared to other labor market policies. Conversely, excluding earnings gains for parents, each dollar of net government expenditure yields only $0.46 to $1.32 in benefits, lower than many other education and children's health interventions. We conclude that the economic returns to investing in UPK are high, largely because of full-day UPK's effectiveness as an active labor market policy.