We use a novel data set from a private online marketplace to estimate the demand for individual health insurance among a set comprising many high-income households across 18 states. Households earning more than four times the federal poverty level (FPL) are willing to pay $30 to $135 per month to increase the actuarial value of their insurance by 10 percentage points, much less than households earning less than 2.5 times FPL. Higher-income households are also less likely to forgo insurance because of a premium increase. These results are important for understanding the effect of health reform proposals targeting higher-income populations.
{"title":"The Demand for Individual Insurance","authors":"Conor Ryan, R. Feldman, Stephen L. Parente","doi":"10.1086/718161","DOIUrl":"https://doi.org/10.1086/718161","url":null,"abstract":"We use a novel data set from a private online marketplace to estimate the demand for individual health insurance among a set comprising many high-income households across 18 states. Households earning more than four times the federal poverty level (FPL) are willing to pay $30 to $135 per month to increase the actuarial value of their insurance by 10 percentage points, much less than households earning less than 2.5 times FPL. Higher-income households are also less likely to forgo insurance because of a premium increase. These results are important for understanding the effect of health reform proposals targeting higher-income populations.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49248579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study analyzes the effect of test-hour particulate matter (PM10) on the college entrance test performance of 290,000 high school seniors. The data are drawn from Seoul, the capital city of South Korea, where each of the 25 districts has at least one PM10 monitoring station. The study finds that reading test scores decrease when the test-hour PM10 concentration increases. Specifically, when the one-hour average PM10 concentration is ≥75 μg/m3, reading test scores decrease by 0.13 standard deviations relative to when the concentration is lower than 25 μg/m3. The effect size is equivalent to increasing class size by six or seven students. In addition, the one-hour average concentrations measured before and after the reading test have no significant effects on the test scores, meaning that it is unlikely that other factors drive the result.
{"title":"Does Particulate Matter Affect Cognitive Performance?","authors":"Hyunkuk Cho","doi":"10.1086/717922","DOIUrl":"https://doi.org/10.1086/717922","url":null,"abstract":"This study analyzes the effect of test-hour particulate matter (PM10) on the college entrance test performance of 290,000 high school seniors. The data are drawn from Seoul, the capital city of South Korea, where each of the 25 districts has at least one PM10 monitoring station. The study finds that reading test scores decrease when the test-hour PM10 concentration increases. Specifically, when the one-hour average PM10 concentration is ≥75 μg/m3, reading test scores decrease by 0.13 standard deviations relative to when the concentration is lower than 25 μg/m3. The effect size is equivalent to increasing class size by six or seven students. In addition, the one-hour average concentrations measured before and after the reading test have no significant effects on the test scores, meaning that it is unlikely that other factors drive the result.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48030290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Helmut Farbmacher, Maximilian C. Hartmann, Heinrich Kögel
The Supplemental Nutrition Assistance Program (SNAP) distributes vouchers for grocery shopping to around 43 million individuals across the United States to counteract food insecurity. In this study, we take advantage of the random interview day assignment of the American Time Use Survey (ATUS) and the variation in voucher issuance dates across states to identify changes in self-rated health and sleep over the monthly SNAP payment cycle. We find that the economic hardship experienced at the end of the payout period causes a significant and sizable negative effect on self-assessed physical health and sleep quality. SNAP recipients were 18 percent more likely to report fair or poor physical health at the end of the payment cycle compared with the rest of the month. During this period of scarcity, recipients were also 50 percent more likely to report sleeplessness, with the number of minutes being sleepless more than doubling while total sleep duration remained unchanged. Drawing upon information on time use in the ATUS, we discuss evidence suggesting that higher levels of stress, changed eating patterns, and reduced sleep quality may be potential mechanisms of the adverse health effects. Our findings extend the literature on sleep quality as a mediator between low socioeconomic status and self-rated health in the short run.
{"title":"Economic Hardship, Sleep, and Self-Rated Health","authors":"Helmut Farbmacher, Maximilian C. Hartmann, Heinrich Kögel","doi":"10.1086/717811","DOIUrl":"https://doi.org/10.1086/717811","url":null,"abstract":"The Supplemental Nutrition Assistance Program (SNAP) distributes vouchers for grocery shopping to around 43 million individuals across the United States to counteract food insecurity. In this study, we take advantage of the random interview day assignment of the American Time Use Survey (ATUS) and the variation in voucher issuance dates across states to identify changes in self-rated health and sleep over the monthly SNAP payment cycle. We find that the economic hardship experienced at the end of the payout period causes a significant and sizable negative effect on self-assessed physical health and sleep quality. SNAP recipients were 18 percent more likely to report fair or poor physical health at the end of the payment cycle compared with the rest of the month. During this period of scarcity, recipients were also 50 percent more likely to report sleeplessness, with the number of minutes being sleepless more than doubling while total sleep duration remained unchanged. Drawing upon information on time use in the ATUS, we discuss evidence suggesting that higher levels of stress, changed eating patterns, and reduced sleep quality may be potential mechanisms of the adverse health effects. Our findings extend the literature on sleep quality as a mediator between low socioeconomic status and self-rated health in the short run.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42078715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine the effects of must-access prescription drug monitoring programs (PDMPs) and recent regulations limiting the duration of initial opioid prescriptions on care received by patients with work-related injuries, focusing on opioid utilization and medical care related to pain management. We find that must-access PDMPs contributed to declines in opioid utilization, while regulations limiting duration of initial opioid prescriptions had little effect on whether workers receive opioids, but reduced opioid use among those with prescriptions. We find some evidence that must-access PDMPs affected utilization of other medical care—most interestingly, in light of high opioid use, towards non-opioid pain medication and interventional pain management services for neurologic spine pain. We find that must-access PDMPs and limits on initial prescriptions had little impact on the duration of temporary disability benefits captured at 12 months of maturity.
{"title":"Effects of Opioid-Related Policies on Opioid Utilization, Nature of Medical Care, and Duration of Disability","authors":"D. Neumark, Bogdan Savych","doi":"10.1086/722981","DOIUrl":"https://doi.org/10.1086/722981","url":null,"abstract":"We examine the effects of must-access prescription drug monitoring programs (PDMPs) and recent regulations limiting the duration of initial opioid prescriptions on care received by patients with work-related injuries, focusing on opioid utilization and medical care related to pain management. We find that must-access PDMPs contributed to declines in opioid utilization, while regulations limiting duration of initial opioid prescriptions had little effect on whether workers receive opioids, but reduced opioid use among those with prescriptions. We find some evidence that must-access PDMPs affected utilization of other medical care—most interestingly, in light of high opioid use, towards non-opioid pain medication and interventional pain management services for neurologic spine pain. We find that must-access PDMPs and limits on initial prescriptions had little impact on the duration of temporary disability benefits captured at 12 months of maturity.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44338747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sandra L. Decker, M. Dworsky, T. Gibson, R. Henke, K. McDermott
Amid rising opioid-related deaths and hospital use, the 2010 Patient Protection and Affordable Care Act (ACA) was signed into law, with the central coverage provisions implemented in 2014. We leverage these ACA coverage expansions (including Medicaid expansion and Marketplaces) to study the impact of health insurance on opioid-related emergency department (ED) visits while accounting for potentially confounding changes in relevant state-level policies. We use zip code–level ED utilization data from the 2010–18 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) and State Emergency Department Databases (SEDD) for 29 states. In difference-in-difference-in-differences (DDD) models that compared low- and high-uninsurance areas within states, we found evidence of a dose-response relationship between pre-ACA uninsurance and changes in ED visit rates in both expansion and non-expansion states: areas with higher uninsurance rates prior to the ACA saw larger reductions in opioid-related ED visits after the ACA took effect. Effects were also time-varying, with no significant dose-response relationship emerging until the third year of ACA implementation. These estimates suggest that increasing insurance coverage among the uninsured may help mitigate harms of the opioid crisis.
{"title":"The Impact of the Affordable Care Act Insurance Expansions on Opioid-Related Emergency Department Visits","authors":"Sandra L. Decker, M. Dworsky, T. Gibson, R. Henke, K. McDermott","doi":"10.1086/722928","DOIUrl":"https://doi.org/10.1086/722928","url":null,"abstract":"Amid rising opioid-related deaths and hospital use, the 2010 Patient Protection and Affordable Care Act (ACA) was signed into law, with the central coverage provisions implemented in 2014. We leverage these ACA coverage expansions (including Medicaid expansion and Marketplaces) to study the impact of health insurance on opioid-related emergency department (ED) visits while accounting for potentially confounding changes in relevant state-level policies. We use zip code–level ED utilization data from the 2010–18 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) and State Emergency Department Databases (SEDD) for 29 states. In difference-in-difference-in-differences (DDD) models that compared low- and high-uninsurance areas within states, we found evidence of a dose-response relationship between pre-ACA uninsurance and changes in ED visit rates in both expansion and non-expansion states: areas with higher uninsurance rates prior to the ACA saw larger reductions in opioid-related ED visits after the ACA took effect. Effects were also time-varying, with no significant dose-response relationship emerging until the third year of ACA implementation. These estimates suggest that increasing insurance coverage among the uninsured may help mitigate harms of the opioid crisis.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43265547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We estimate the impact of information disclosure on consumer knowledge in an important context: the calorie content of restaurant food. We conduct a randomized controlled experiment of calorie labels on restaurant menus, and find that information disclosure improves consumer knowledge but does not eliminate the problem of imperfect information. Calorie labels improve consumers’ post-meal estimates of the number of calories they ordered by 4.0 percent and reduce by 28.9 percent the probability that consumers underestimate the calories in their meal by half or more. However, even after information disclosure, the absolute value of percent error averages 34.2 percent.
{"title":"Does Information Disclosure Improve Consumer Knowledge?","authors":"J. Cawley, Alex M. Susskind, Barton Willage","doi":"10.1086/714987","DOIUrl":"https://doi.org/10.1086/714987","url":null,"abstract":"We estimate the impact of information disclosure on consumer knowledge in an important context: the calorie content of restaurant food. We conduct a randomized controlled experiment of calorie labels on restaurant menus, and find that information disclosure improves consumer knowledge but does not eliminate the problem of imperfect information. Calorie labels improve consumers’ post-meal estimates of the number of calories they ordered by 4.0 percent and reduce by 28.9 percent the probability that consumers underestimate the calories in their meal by half or more. However, even after information disclosure, the absolute value of percent error averages 34.2 percent.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/714987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43201555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We exploit the discontinuity in health insurance coverage rates at the Medicare eligibility age of 65 to investigate the impact of Medicare on health-care utilization and spending among the elderly. We find that the discrete change in insurance coverage rates at age 65 leads to a significant increase in office-based physician and outpatient visits, which is mainly driven by those who were not insured before age 65. We also document that Medicare eligibility at age 65 is associated with up to 36.5 percent decrease in out-of-pocket spending for physician and outpatient visits. On the other hand, we find that Medicare eligibility does not have a significant impact on the utilization of inpatient or emergency department services.
{"title":"The Effects of Medicare on Health-Care Utilization and Spending Among the Elderly","authors":"Pinka Chatterji, Tu Nguyen, Barış K. Yörük","doi":"10.1086/716544","DOIUrl":"https://doi.org/10.1086/716544","url":null,"abstract":"We exploit the discontinuity in health insurance coverage rates at the Medicare eligibility age of 65 to investigate the impact of Medicare on health-care utilization and spending among the elderly. We find that the discrete change in insurance coverage rates at age 65 leads to a significant increase in office-based physician and outpatient visits, which is mainly driven by those who were not insured before age 65. We also document that Medicare eligibility at age 65 is associated with up to 36.5 percent decrease in out-of-pocket spending for physician and outpatient visits. On the other hand, we find that Medicare eligibility does not have a significant impact on the utilization of inpatient or emergency department services.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/716544","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44096377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The number of disability beneficiaries has doubled in the past two decades. It is difficult to determine how much is explained by changes in health, as we lack a counterfactual. We use undocumented immigrants to form the counterfactual, as they cannot claim benefits. Using data from the National Health Interview Survey, we show that the relationship between health and disability is stronger for the legal population than for the undocumented. Much of the difference in disability rates between the populations is due to different labor supply responses to underlying health impairments and demographic differences, rather than to differences in the impairments or demographic variables themselves.
{"title":"Health, Employment, and Disability","authors":"G. Borjas, David J. G. Slusky","doi":"10.1086/716465","DOIUrl":"https://doi.org/10.1086/716465","url":null,"abstract":"The number of disability beneficiaries has doubled in the past two decades. It is difficult to determine how much is explained by changes in health, as we lack a counterfactual. We use undocumented immigrants to form the counterfactual, as they cannot claim benefits. Using data from the National Health Interview Survey, we show that the relationship between health and disability is stronger for the legal population than for the undocumented. Much of the difference in disability rates between the populations is due to different labor supply responses to underlying health impairments and demographic differences, rather than to differences in the impairments or demographic variables themselves.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44432309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Betsy Q Cliff, Sarah Miller, Jeffrey T. Kullgren, J. Ayanian, R. Hirth
Recent expansions of Medicaid eligibility have come with increased experimentation with enrollee cost-sharing. In this paper, we exploit a discontinuous premium increase at the federal poverty level in Michigan’s Medicaid expansion program to test low-income individuals’ sensitivity to premiums using linked enrollment and claims data. At the cutoff, average premiums increase by $3.15 and the probability of disenrollment increases by 2.3 percentage points. Increased disenrollment occurs among those with fewer documented medical needs at baseline, but not among those with greater medical needs. These results suggest that healthier low-income individuals may be sensitive to even modest health insurance premiums, and that premiums may induce adverse selection in Medicaid plans.
{"title":"Adverse Selection in Medicaid","authors":"Betsy Q Cliff, Sarah Miller, Jeffrey T. Kullgren, J. Ayanian, R. Hirth","doi":"10.1086/716464","DOIUrl":"https://doi.org/10.1086/716464","url":null,"abstract":"Recent expansions of Medicaid eligibility have come with increased experimentation with enrollee cost-sharing. In this paper, we exploit a discontinuous premium increase at the federal poverty level in Michigan’s Medicaid expansion program to test low-income individuals’ sensitivity to premiums using linked enrollment and claims data. At the cutoff, average premiums increase by $3.15 and the probability of disenrollment increases by 2.3 percentage points. Increased disenrollment occurs among those with fewer documented medical needs at baseline, but not among those with greater medical needs. These results suggest that healthier low-income individuals may be sensitive to even modest health insurance premiums, and that premiums may induce adverse selection in Medicaid plans.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45039045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sumedha Gupta, Thuy Nguyen, Shyam Raman, Byungkyu Lee, Felipe Lozano-Rojas, A. Bento, K. Simon, Coady Wing
This paper examines the determinants of social distancing during the shutdown phase of the COVID-19 epidemic. We classify state and local government actions, and we study multiple proxies for social distancing based on data from smart devices. Mobility fell substantially in all states, even ones that did not adopt major distancing mandates. Most of the fall in mobility occurred prior to the most stringent sanctions against movement, such as stay-at-home laws. However, we find evidence suggesting that state and local policies did have an independent effect on mobility even after the large initial reductions occurred. Event studies show that early and information-focused actions such as first case announcements, emergency declarations, and school closures reduced mobility by 1–5 percent after five days. Between March 1 and April 14, average time spent at home grew from 9.1 hours to 13.9 hours. We find, for example, that without state emergency declarations, hours at home would have been 11.3 hours in April, suggesting that 55 percent of the growth is associated with policy and 45 percent is associated with (non-policy) trends. State and local government actions induced changes in mobility on top of a large and private response across all states to the prevailing knowledge of public health risks.
{"title":"Tracking Public and Private Responses to the COVID-19 Epidemic","authors":"Sumedha Gupta, Thuy Nguyen, Shyam Raman, Byungkyu Lee, Felipe Lozano-Rojas, A. Bento, K. Simon, Coady Wing","doi":"10.1086/716197","DOIUrl":"https://doi.org/10.1086/716197","url":null,"abstract":"This paper examines the determinants of social distancing during the shutdown phase of the COVID-19 epidemic. We classify state and local government actions, and we study multiple proxies for social distancing based on data from smart devices. Mobility fell substantially in all states, even ones that did not adopt major distancing mandates. Most of the fall in mobility occurred prior to the most stringent sanctions against movement, such as stay-at-home laws. However, we find evidence suggesting that state and local policies did have an independent effect on mobility even after the large initial reductions occurred. Event studies show that early and information-focused actions such as first case announcements, emergency declarations, and school closures reduced mobility by 1–5 percent after five days. Between March 1 and April 14, average time spent at home grew from 9.1 hours to 13.9 hours. We find, for example, that without state emergency declarations, hours at home would have been 11.3 hours in April, suggesting that 55 percent of the growth is associated with policy and 45 percent is associated with (non-policy) trends. State and local government actions induced changes in mobility on top of a large and private response across all states to the prevailing knowledge of public health risks.","PeriodicalId":45056,"journal":{"name":"American Journal of Health Economics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41508534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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