Health economics最新文献

We use data from the National Longitudinal Study of Adolescent to Adult Health to investigate whether the quality of tertiary education -measured by college selectivity-causally affects obesity prevalence in the medium run (by age 24–34) and in the longer run (about 10 years later). We use partial identification methods, which allow us, while relying on weak assumptions, to overcome the potential endogeneity of college selectivity as well as the potential violation of the stable unit treatment value assumption due to students interacting with each other, and to obtain informative identification regions for the average treatment effect of college selectivity on obesity. We find that attending a more selective college causally reduces obesity, both in the medium and in the longer run. We provide evidence that the mechanisms through which the impact of college selectivity on obesity operates include an increase in income, a reduction in physical inactivity and in the consumption of fast food and sweetened drinks.

Federal authorities banned nursing home visitation in the early days of the coronavirus disease 2019 (COVID-19) pandemic. However, there was growing concern that physical isolation may have unintended harms on nursing home residents. Thus, nursing homes and policymakers faced a tradeoff between minimizing COVID-19 outbreaks and limiting the unintended harms. Between June 2020 and January 2021, 17 states implemented Essential Caregiver policies (ECPs) allowing nursing home visitation by designated family members or friends under controlled circumstances. Using the Nursing Home COVID-19 Public File and other relevant data, we analyze the effects of ECPs on deaths among nursing home residents. We exploit variation in the existence of ECPs across states and over time, finding that these policies effectively reduce both non-COVID-19 and COVID-19 deaths, resulting in a decrease in total deaths. These effects are larger for states that implemented policies mandatorily or without restrictions, indicating a dose-response relationship. These policies reduce non-COVID-19 deaths in facilities with higher quality or staffing levels, while reducing COVID-19 deaths in facilities with lower quality or staffing levels. Our findings support the use and expansion of ECPs to balance resident safety and the need for social interaction and informal care during future pandemics.

There are growing concerns about the impact of pollution on maternal and infant health. Despite an extensive correlational literature, observational studies which adopt methods that seek to address potential biases due to unmeasured confounders draw mixed conclusions. Using a population database of births in Northern Ireland (NI) linked to localized geographic information on pollution in mothers' postcodes (zipcodes) of residence during pregnancy, we examine whether prenatal exposure to PM_2.5 is associated with a comprehensive range of birth outcomes, including placental health. Overall, we find little evidence that particulate matter is related to infant outcomes at the pollution levels experienced in NI, once we implement a mother fixed effects approach that accounts for time-invariant factors. This contrasts with strong associations in models that adjust for observed confounders but without fixed effects. While reducing ambient air pollution remains an urgent public health priority globally, our results imply that further improvements in short-run levels of prenatal PM_2.5 exposure in a relatively low-pollution, higher-income country context, are unlikely to impact on birth outcomes at the population level.

Improving access to primary care physicians' services may help reduce hospitalizations due to Ambulatory Care Sensitive Conditions (ACSCs). Ontario, Canada's most populous province, introduced blended payment models for primary care physicians in the early- to mid-2000s to increase access to primary care, preventive care, and better chronic disease management. We study the impact of payment models on avoidable hospitalizations due to two incentivized ACSCs (diabetes and congestive heart failure) and two non-incentivized ACSCs (angina and asthma). The data for our study came from health administrative data on practicing primary care physicians in Ontario between 2006 and 2015. We employ a two-stage estimation strategy on a balanced panel of 3710 primary care physicians (1158 blended-fee-for-service (FFS), 1388 blended-capitation models, and 1164 interprofessional team-based practices). First, we account for the differences in physician practices using a generalized propensity score based on a multinomial logit regression model, corresponding to three primary care payment models. Second, we use fractional regression models to estimate the average treatment effects on the treated outcome (i.e., avoidable hospitalizations). The capitation-based model sometimes increases avoidable hospitalizations due to angina (by 7 per 100,000 patients) and congestive heart failure (40 per 100,000) relative to the blended-FFS-based model. Switching capitation physicians into interprofessional teams mitigates this effect, reducing avoidable hospitalizations from congestive heart failure by 30 per 100,000 patients and suggesting better access to primary care and chronic disease management in team-based practices.

We examine variation in US hospital quality across ownership, chain membership, and market concentration. We propose a new measure of quality derived from penalties imposed on hospitals under the flagship Hospital Readmissions Reduction Program, and use regression models to risk-adjust for hospital characteristics and county demographics. While the overall association between for-profit ownership and quality is negative, there is evidence of substantial heterogeneity. The quality of for-profit relative to non-profit hospitals declines with increasing market concentration. Moreover, the quality gap is primarily driven by for-profit chains. While the competition result mirrors earlier findings in the literature, the chain result appears to be new: it suggests that any potential quality gains afforded by chains are mostly realized by not-for-profit hospitals.

The provision of unconditional cash transfers may be one effective policy strategy for improving mental health, but causal evidence on their efficacy is rare in high-income countries. This study investigates the mental health consequences of the 2021 child tax credit (CTC) expansion, which temporarily provided unconditional and monthly cash support to most families with children in the United States. Using data from the Behavioral Risk Factor Surveillance System, we exploit differences in CTC benefit levels for households with younger versus older children. More generous CTC transfers are associated with a decrease in the number of bad mental health days reported by the parents. The effect materializes after the third monthly payment and disappears when the benefits are withdrawn. The CTC's improvement of mental health is larger for more credit-constrained individuals, including low-income households, women, and younger respondents.

Social media is viewed to be a key contributor to worsening mental health in adolescents, as most recently reflected in a public health advisory by the US Surgeon General. We provide new evidence on the causal effects of social media on mental health of college students during the Covid-19 pandemic, exploiting unique, longitudinal data collected before the Covid-19 pandemic began and at two points during the pandemic. We find small insignificant effects of social media 4 months into the pandemic during a period of social distancing, but large statistically significant negative effects 18 months into the pandemic when colleges were mostly back to normal operations. Using rich data on substance use, exercise, sleep, stress, and social support, we find some evidence of substitution away from activities that better support mental health at later stages of the pandemic but not at early stages. We find that the negative effects of social media are mostly concentrated among socially-isolated students. Both social support and resilience protect students from the negative effects of social media use. Policy implications include regulating social media while also bolstering social support and resilience as important protective factors.

Is healthcare employment recession-proof? We examine the long-standing hypothesis that healthcare employment is stable across the business cycle. We explicitly distinguish between negative aggregate demand and supply shocks in studying how healthcare employment responds to recessions, and show that this response depends largely on the type of the exogenous shock triggering the recession. First, aggregate healthcare employment responds procyclically during demand-induced recessions but remains stable during supply-induced recessions. Second, healthcare utilization drops significantly during demand-induced recessions, explaining the decline in healthcare employment during these periods. Finally, there is significant heterogeneity in the employment responses of the healthcare sub-sectors. While healthcare employment in most sub-sectors responds procyclically during recessions caused by both negative demand and supply shocks, it responds countercyclically in nursing-dominant sectors. Importantly, by isolating the recessionary impact of negative aggregate demand shocks from supply shocks on healthcare employment, we provide new empirical evidence that healthcare employment, in general, is not recession-proof.

We investigate how a local restaurant restriction aimed at containing the COVID-19 pandemic influenced population movement and COVID-19 prevalence within and outside the restricted districts. Using data on restaurant location and hourly population at the 500-m-mesh level and on COVID-19 prevalence at both prefecture and municipality level in Japan, we employ a triple-difference approach and a difference-in-differences approach with fixed effects. While the policy decreased population movement to restaurant areas in the restricted districts, it caused spillovers of increasing population movement to restaurant areas in the neighboring nonrestricted districts. Consequently, COVID-19 prevalence worsened in the neighboring nonrestricted districts but improved in the restricted districts. Our findings suggest that imposing such local restrictions in the context of the pandemic may contain the pandemic only in the restricted districts while sacrificing economic activities within these districts and public health in neighboring nonrestricted districts.

The side effects of technological progress on the economy have been discussed frequently, but little is known regarding its health consequences. By combining the national individual-level panel data of alcohol drinking with the prefecture-level robot exposure rate in China, we find that one more robot exposure rate could induce up to 2.2% points increase in the probability of problem drinking. Such a pattern of problem drinking is explained by negative emotions, which can be ascribed to job loss due to substitution, higher income vulnerability, and reduced organization participation. Further, we provide evidence that automation can incur health costs, particularly for easily substituted workers, which would exacerbate health inequality in China. This paper sheds light on the impact of automation and the social incentives of problem drinking, emphasizing the possibly heterogeneous health cost accompanied by the automation process.