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This paper studies how better access to public health insurance affects infant mortality during pandemics. The analysis combines cross-state variation in mandated eligibility for Medicaid with two influenza pandemics that arrived shortly before and after the program's introduction in 1965. We find that better access to public health insurance in high-eligibility states substantially reduced pandemic infant mortality. The reductions in pandemic infant mortality are too large to be attributable solely to new Medicaid recipients, suggesting that expanded access to public health insurance helped mitigate disease transmission among the broader population.

SummaryBackgroundPublic health efforts to determine population infection rates from coronavirus disease 2019 (COVID-19) have been hampered by limitations in testing capabilities and the large shares of mild and asymptomatic cases. We developed a methodology that corrects observed positive test rates for non-random sampling to estimate population infection rates across U.S. states from March 31 to April 7.MethodsWe adapted a sample selection model that corrects for non-random testing to estimate population infection rates. The methodology compares how the observed positive case rate vary with changes in the size of the tested population, and applies this gradient to infer total population infection rates. Model identification requires that variation in testing rates be uncorrelated with changes in underlying disease prevalence. To this end, we relied on data on day-to-day changes in completed tests across U.S. states for the period March 31 to April 7, which were primarily influenced by immediate supply-side constraints. We used this methodology to construct predicted infection rates across each state over the sample period. We also assessed the sensitivity of the results to controls for state-specific daily trends in infection rates.ResultsThe median population infection rate over the period March 31 to April 7 was 0.9% (IQR 0.64 1.77). The three states with the highest prevalence over the sample period were New York (8.5%), New Jersey (7.6%), and Louisiana (6.7%). Estimates from mod-els that control for state-specific daily trends in infection rates were virtually identical to the baseline findings. The estimates imply a nationwide average of 12 population infections per diagnosed case. We found a negative bivariate relationship (corr. = -0.51) between total per capita state testing and the ratio of population infections per diagnosed case.InterpretationThe effectiveness of the public health response to the coronavirus pandemic will depend on timely information on infection rates across different regions. With increasingly available high frequency data on COVID-19 testing, our methodology could be used to estimate population infection rates for a range of countries and subnational districts. In the United States, we found widespread undiagnosed COVID-19 infection. Expansion of rapid diagnostic and serological testing will be critical in preventing recurrent unobserved community transmission and identifying the large numbers individuals who may have some level of viral immunity.FundingSocial Sciences and Humanities Research Council.

Despite well-meaning intentions, people rarely allocate their charitable donations in the most cost-effective way possible. The manner in which cost-effectiveness information is presented can be a contributing factor. In four studies (N = 2,725), when we inform participants of the cost of a unit of impact (e.g. the cost of a mosquito net), they perversely donate less when the cost is cheaper. This result arises because people want their donation to have a tangible impact, and when the cost of such an impact is lower, people can achieve it with a smaller donation. A remedy for this inefficiency is to express cost-effectiveness in terms of “units per dollar amount” (e.g. 5 nets provided per $10 donated), thus leaving the cost of providing one tangible item unstated and rendering it less salient as a target donation amount. Across Studies 2 and 3, we demonstrate both the inefficient use of cost-effectiveness information and the effectiveness of this remedy using incentive-compatible donations decisions about providing meals, oral rehydration therapy, deworming medication, and measles vaccines.

Electrification among American farm households increased from less than 10 percent to nearly 100 percent over a three decade span, 1930–1960. We exploit the historical rollout of the U.S. power grid to study the short- and long-run impacts of rural electrification on local economies. In the short-run, rural electrification led to increases in agricultural employment, rural farm population, and rural property values, but there was little impact on the local non-agriculture economy. Benefits exceeded historical costs, even in rural areas with low population density. As for the long run, rural counties that gained early access to electricity experienced increased economic growth that persisted for decades after the country was fully electrified. In remote rural areas, local development was driven by an expansion in the agricultural sector. Meanwhile in rural counties near metropolitan areas, long-run population growth coincided with increases in housing costs and decreases in agricultural employment, suggesting that rural electrification stimulated suburban expansion.