In a world where externalities are rife, transactions take time, and information is imperfect, market mechanisms alone will not guarantee efficiency. Trust in others' competence and decency, and concern for their well-being, can help economic actors to coordinate their behavior and achieve better outcomes.It is of some concern, then, that Americans feel a decreasing level of trust and increasing hostility along party lines. Gentzkow (2016) reports that, as of 2008, nearly half of Americans classified members of the other party as "selfish", up from around 20% in 1960. The same report shows that 20%-30% of Americans would be upset if their son or daughter married a member of the other party, up from around 5% in 1960. The difference in individual's warmth toward their own party and their warmth toward the other party, each on a scale of 0-100, has increased from around 25 points in 1980 to 45 points today . This hostility may be particularly problematic when members of different parties have to work together to combat a crisis, as has recently occurred during the COVID-19 pandemic. Social distancing poses a classic collective action problem: while the costs of preventative behavior accrue entirely to the individual, the benefits are diffused across a large number of people. It is in precisely this situation that social preferences might help to restore more efficient outcomes. If individuals are altruistic, they internalize some of the utility costs their actions have on other people. When altruism breaks down, society's ability to overcome the collective action problem may be compromised. While this argument has been made in the context of ethnic fractionalization (e.g., Poterba, 1997; Vigdor, 2004), until recently there has been little empirical work examining the consequences of political fragmentation for public goods provision. 1 In this paper, we fill this gap by examining whether political polarization has undermined the response to the COVID-19 pandemic in the United States.A simple comparison of social distancing across more or less polarized individuals or states will not identify the impact of polarization, because both polarization and willingness to comply with social distancing may be related to other, unobserved

We estimate racial differences in longevity using records from cohorts of Union Army veterans. Since veterans received pensions based on proof of disability at medical exams, estimates of the causal effect of income on mortality may be biased, as sicker veterans received larger pensions. To circumvent endogeneity bias, we propose an exogenous source of variation in pension income: the judgment of the doctors who certified disability. We find that doctors appeared to discriminate against black veterans. The discrimination we observe is acute-we would not observe any racial mortality differences had physicians not been racially biased in determining pension awards. The effect of income on health was indeed large enough to close the black-white mortality gap in the period. Our work emphasizes that the large effects of physicians' attitudes on racial differentials in health, which persist today amongst both veterans and the civilian population, were equally prominent in the past.

This study provides comparisons of inequalities in mortality between the United States, Canada and France using the most recent available data. The period between 2010 and 2018 saw increases in mortality and in inequality in mortality for most age and gender groups in the United States. The main exceptions were children under 5 and adults over 65. In contrast, Canada saw a further flattening of mortality gradients in most groups, as well as further declines in overall mortality. The sole exception was Canadian women over 80 years old, who saw small increases in mortality rates. France saw continuing improvements in mortality rates in all groups. Both Canada and France have distributions of mortality that are much more equal than those in the United States, demonstrating the importance of public policy in the achievement of equality in health.

ObjectivesTo determine death occurrences of Puerto Ricans on the mainland USA following the arrival of Hurricane Maria in Puerto Rico in September 2017.DesignCross-sectional study.ParticipantsPersons of Puerto Rican origin on the mainland USA.ExposuresHurricane Maria.Main outcomeWe use an interrupted time series design to analyse all-cause mortality of Puerto Ricans in the USA following the hurricane. Hispanic origin data from the National Vital Statistics System and from the Public Use Microdata Sample of the American Community Survey are used to estimate monthly origin-specific mortality rates for the period 2012–2018. We estimated log-linear regressions of monthly deaths of persons of Puerto Rican origin by age group, gender, and educational attainment.ResultsWe found an increase in mortality for persons of Puerto Rican origin during the 6-month period following the hurricane (October 2017 through March 2018), suggesting that deaths among these persons were 3.7% (95% CI 0.025 to 0.049) higher than would have otherwise been expected. In absolute terms, we estimated 514 excess deaths (95% CI 346 to 681) of persons of Puerto Rican origin that occurred on the mainland USA, concentrated in those aged 65 years or older.ConclusionsOur findings suggest an undercounting of previous deaths as a result of the hurricane due to the systematic effects on the displaced and resident populations in the mainland USA. Displaced populations are frequently overlooked in disaster relief and subsequent research. Ignoring these populations provides an incomplete understanding of the damages and loss of life.

Studies have shown that reducing out‐of‐pocket costs can lead to higher medication initiation rates in childhood. Whether the cost of such initiatives is inflated by moral hazard issues remains a question of concern. This paper looks to the implementation of a public drug insurance program in Québec, Canada, to investigate potential low‐benefit consumption in children. Using a nationally representative longitudinal sample, we harness machine learning techniques to predict a child's risk of developing a mental health disorder. Using difference‐in‐differences analyses, we then assess the impact of the drug program on children's mental health medication uptake across the distribution of predicted mental health risk. Beyond showing that eliminating out‐of‐pocket costs led to a 3 percentage point increase in mental health drug uptake, we show that demand responses are concentrated in the top two deciles of risk for developing mental health disorders. These higher‐risk children increase take‐up of mental health drugs by 7–8 percentage points. We find even stronger effects for stimulants (8–11 percentage point increases among the highest risk children). Our results suggest that reductions in out‐of‐pocket costs could achieve better uptake of mental health medications, without inducing substantial low‐benefit care among lower‐risk children.