nep-hea New Economics Papers
on Health Economics
Issue of 2019‒08‒26
twenty papers chosen by
Nicolas R. Ziebarth
Cornell University

  1. A Model of a Randomized Experiment with an Application to the PROWESS Clinical Trial By Amanda Kowalski
  2. Who is Tested for Heart Attack and Who Should Be: Predicting Patient Risk and Physician Error By Sendhil Mullainathan; Ziad Obermeyer
  3. Effects of Direct Care Provision to the Uninsured: Evidence from Federal Breast and Cervical Cancer Programs By Marianne Bitler; Christopher Carpenter
  4. The Impact of the ACA on Insurance Coverage Disparities After Four Years By Charles J. Courtemanche; Ishtiaque Fazlul; James Marton; Benjamin D. Ukert; Aaron Yelowitz; Daniela Zapata
  5. The Opportunities and Limitations of Monopsony Power in Healthcare: Evidence from the United States and Canada By Jillian Chown; David Dranove; Craig Garthwaite; Jordan Keener
  6. Prenatal Exposure to Acute Diarrheal Diseases and Childhood Mortality By Patricia I. Ritter; Ricardo Sanchez
  7. Developmental Origins of Health Inequality By Conti, Gabriella; Mason, Giacomo; Poupakis, Stavros
  8. Uninsured by Choice? A Choice Experiment on Long Term Care Insurance By Faical Akaichi; Joan Costa-Font; Richard Frank
  9. Air Pollution and Infant Mortality: Evidence from Saharan Dust By Sam Heft-Neal; Jennifer Burney; Eran Bendavid; Kara Voss; Marshall Burke
  10. The impact of ambient air pollution on hospital admissions By Massimo Filippini; Giuliano Masiero; Sandro Steinbach
  11. Maternal Education and Infant Health Gradient: New Answers to Old Questions By Vinish Shrestha
  12. The Economic Impact of Healthcare Quality By Anne-Line Koch Helsø; Nicola Pierri; Adelina Yanyue Wang
  13. Are they coming for us? Industrial robots and the mental health of workers By Abeliansky, Ana Lucia; Beulmann, Matthias
  14. The retirement mortality puzzle: Evidence from a regression discontinuity design By Giesecke, Matthias
  15. Can Economic Policies Reduce Deaths of Despair? Working Paper #104-19 By Dow, Wiiliam H; Godoey, Anna; Lowenstein, Christopher A; Reich, Michael
  16. The Entertaining Way to Behavioral Change: Fighting HIV with MTV By Banerjee, Abhijit; La Ferrara, Eliana; Orozco, Victor
  17. Publication Bias and Editorial Statement on Negative Findings By Blanco-Perez, Cristina; Brodeur, Abel
  18. The impact of technological advancements on health spending: A literature review By Alberto Marino; Luca Lorenzoni
  19. Specification and testing of hierarchical ordered response models with anchoring vignettes By Greene, W.H.;; Harris, M.N.;; Knott, R.;; Rice, N.;
  20. The Effects of Primary Care Chronic-Disease Management in Rural China By Yiwei Chen; Hui Ding; Min Yu; Jieming Zhong; Ruying Hu; Xiangyu Chen; Chunmei Wang; Kaixu Xie; Karen Eggleston

  1. By: Amanda Kowalski
    Abstract: I develop a model of a randomized experiment with a binary intervention and a binary outcome. Potential outcomes in the intervention and control groups give rise to four types of participants. Fixing ideas such that the outcome is mortality, some participants would live regardless, others would be saved, others would be killed, and others would die regardless. These potential outcome types are not observable. However, I use the model to develop estimators of the number of participants of each type. The model relies on the randomization within the experiment and on deductive reasoning. I apply the model to an important clinical trial, the PROWESS trial, and I perform a Monte Carlo simulation calibrated to estimates from the trial. The reduced form from the trial shows a reduction in mortality, which provided a rationale for FDA approval. However, I find that the intervention killed two participants for every three it saved.
    Date: 2019–08
  2. By: Sendhil Mullainathan; Ziad Obermeyer
    Abstract: In deciding whether to test for heart attack (acute coronary syndromes), physicians implicitly judge risk. To assess these decisions, we produce explicit risk predictions by applying machine learning to Medicare claims data. Comparing these on a patient-by-patient basis to physician decisions reveals more about low-value care than the usual approach of measuring average testing results. It more precisely quantifies over-use: while the average test is marginally cost-effective, tests at the bottom of the risk distribution are highly cost-ineffective. But it also reveals under- use: many patients at the top of the risk distribution go untested; and they go on to have frequent adverse cardiac events, including death, in the next 30 days. At standard clinical thresholds, these event rates suggest they should have been tested. In aggregate, 42.8% of the potential welfare gains of improving testing would come from addressing under-use. Existing policies though are too blunt: when testing is reduced, for example, both low-value and high-value tests fall. Finally, to understand physician error we build a separate algorithm of the physician and find evidence of bounded rationality as well as biases such as representativeness. We suggest models of physician moral hazard should be expanded to include ‘behavioral hazard’.
    JEL: D8 D84 D9 I1 I13
    Date: 2019–08
  3. By: Marianne Bitler; Christopher Carpenter
    Abstract: Much research has studied the health effects of expanding insurance coverage to low-income people, but there is less work on the direct provision of care to the uninsured. We study the two largest federal programs aimed at reducing breast and cervical cancer among uninsured women in the US: one that paid for cancer screenings with federal funds and one that paid for cancer treatments under state Medicaid programs. Using variation in rollout of each program across states from 1991-2005, we find that funding for cancer treatment did not significantly increase most types of cancer screenings for uninsured women. In contrast, funding for cancer detection significantly increased breast and cervical cancer screenings among 40-64 year old uninsured women, with much smaller effects for insured women (who were not directly eligible). Moreover, we find that these program-induced screenings significantly increased detection of early stage pre-cancers and cancers of the breast but had no significant effect on early stage or other cancers of the cervix. Our results suggest that direct provision can significantly increase healthcare utilization among vulnerable populations.
    JEL: I1
    Date: 2019–08
  4. By: Charles J. Courtemanche; Ishtiaque Fazlul; James Marton; Benjamin D. Ukert; Aaron Yelowitz; Daniela Zapata
    Abstract: The purpose of this paper is to estimate the impact of the major components of the ACA (Medicaid expansion, subsidized Marketplace plans, and insurance market reforms) on disparities in insurance coverage after four years. We use data from the 2011–2017 waves of the American Community Survey (ACS), with the sample restricted to nonelderly adults. Our methods feature a difference-in-difference-in-differences model, developed in the recent ACA literature, which separately identifies the effects of the nationwide and Medicaid expansion portions of the law. The differences in this model come from time, state Medicaid expansion status, and local area pre-ACA uninsured rate. We stratify our sample separately by income, race/ethnicity, marital status, age, gender, and geography in order to examine access disparities. After four years, we find that the fully implemented ACA eliminated 44 percent of the coverage gap across income groups, with the Medicaid expansion accounting for this entire reduction. The ACA also reduced coverage disparities across racial groups by 26.7 percent, across marital status by 45 percent, and across age groups by 44 percent, with these changes being partly attributable to both the Medicaid expansion and nationwide components of the law.
    JEL: H51 I13 I14
    Date: 2019–08
  5. By: Jillian Chown; David Dranove; Craig Garthwaite; Jordan Keener
    Abstract: Perhaps more than any other sector of the economy, healthcare depends on government resources. As a result, many healthcare systems rely on the use of government monopsony power to decrease spending. The United States is a notable exception, where prices in large portions of the healthcare sector are set without government involvement. In this paper we examine the economic implications of a greater use of monopsony power in the United States. We present a model of monopsony power and test its predictions using price differences between the United States and Canada – a country that represents an example of a “Medicare for All” style system. Overall, we find that wage differences for medical providers across the two countries are primarily driven by the broader labor market while price difference for prescription drugs are more directly the result of buyer power. We discuss theoretical reasons why a Canadian monopsonist may be more willing to exploit its buyer power over prescription drugs rather than provider wages and why a U.S. monopsonist might not be willing to do the same
    JEL: H0 H4 I0 I1
    Date: 2019–07
  6. By: Patricia I. Ritter (University of Connecticut); Ricardo Sanchez (Ministerio de Educacion del Peru)
    Abstract: There is a large body of evidence that shows the effect of diarrheal diseases on childhood mortality. Nevertheless, most of this literature focuses on post-natal exposure to diarrheal diseases. This study ex-ploits the Cholera Epidemic in Peru, finding that a 1% point increase in cholera incidence in the third trimester in-utero increases average childhood mortality rate by 0.2% points or 14%. This study suggests that public programs that aim to reduce diarrheal diseases should tar-get not just children but also pregnant women and raises the question of whether pregnant women should take vaccines to prevent diarrheal diseases in poor countries.
    Keywords: acute diarrheal diseases; cholera; clean water; in-utero
    JEL: I15 I18 O10
    Date: 2019–08
  7. By: Conti, Gabriella (University College London); Mason, Giacomo (University College London); Poupakis, Stavros (University College London)
    Abstract: Building on early animal studies, 20th-century researchers increasingly explored the fact that early events – ranging from conception to childhood – affect a child's health trajectory in the long-term. By the 21st century, a wide body of research had emerged, incorporating the original 'Fetal Origins Hypothesis' into the 'Developmental Origins of Health and Disease'. Evidence from OECD countries suggests that health inequalities are strongly correlated with many dimensions of socio-economic status, such as educational attainment; and that they tend to increase with age and carry stark intergenerational implications. Different economic theories have been developed to rationalize this evidence, with an overarching comprehensive framework still lacking. Existing models widely rely on human capital theory, which has given rise to separate dynamic models of adult and child health capital, within a production function framework. A large body of empirical evidence has also found support for the developmental origins of inequalities in health. On the one hand, studies exploiting quasi-random exposure to adverse events have shown long-term physical and mental health impacts of exposure to early shocks, including pandemics or maternal illness, famine, malnutrition, stress, vitamin deficiencies, maltreatment, pollution and economic recessions. On the other hand, studies from the 20th century have shown that early interventions of various content and delivery format improve life course health. Further, given that the most socioeconomically disadvantaged groups show the greatest gains, such measures can potentially reduce health inequalities. However, studies of long-term impacts, as well as the mechanisms via which shocks or policies affect health, and the dynamic interaction amongst them, are still lacking. Mapping the complexities of those early event dynamics is an important avenue for future research.
    Keywords: developmental origins, health inequalities, early interventions, health production function, health economics
    JEL: I14 J13 J24
    Date: 2019–06
  8. By: Faical Akaichi; Joan Costa-Font; Richard Frank
    Abstract: We examine evidence from two unique discrete choice experiments (DCE) on long term care insurance and several of its relevant attributes, and more specifically, choices made by 15,298 individuals in the United States with and without insurance. We study the valuation of the following insurance attributes, namely daily insurance benefit, insurance coverage, the compulsory and voluntary nature of the insurance policy design, alongside the costs (insurance premium) and health requirements. This paper investigates respondents’ preferences and willingness to pay (WTP) for these care insurance’s attributes using a random parameter logit model, and assess the heterogeneity of choice responses using demographic, socioeconomic and attitudinal motivations to segment response to insurance choices. We find that an increase in the insurance premium by an additional $100 would reduce insurance uptake by 1pp. Insurance policy uptake is higher when it provides benefits for the lifetime (the monthly marginal WTP being $178.64), and voluntary (the monthly marginal WTP increases by an extra $74.71) as opposed to universal, and when it forgoes health checks (the monthly marginal WTP increases by an extra 28US$).
    JEL: I13 I18 I31
    Date: 2019–07
  9. By: Sam Heft-Neal; Jennifer Burney; Eran Bendavid; Kara Voss; Marshall Burke
    Abstract: Accurate estimation of air quality impacts on health outcomes is critical for guiding policy choices to mitigate such damages. Estimation poses an empirical challenge, however, because local economic activity can simultaneously generate changes in both air quality and in health impacts that are independent of air quality, confounding pollution-health estimates. To address this challenge, we leverage plausibly exogenous variation in local particulate matter exposure across sub-Saharan Africa due to dust export from the Bodele Depression, a remote Saharan region responsible for a substantial share of global atmospheric dust. Large scale transport of this dust is uncorrelated with local emissions sources and allows us to isolate the causal impact of air quality on infant mortality across Sub-Saharan Africa. Combining detailed information on nearly 1 million births with satellite measures of aerosol particulate matter, we find that a 10mg/m3 increase in local ambient PM2.5 concentration driven by distant dust emission causes a 22% increase in infant mortality across our African sample (95% CI: 10-35%), an effect comparable to quasi-experimental pollution-infant mortality estimates from wealthier countries. We also show that rainfall over the Bodele is a significant control on PM2.5 export and thus child health, and that future climate-change driven changes in Saharan rainfall could generate very large impacts on African child health through this pathway alone. We calculate that seemingly exotic proposals to pump and apply groundwater to the Bodele to reduce dust emission could be cost competitive with leading interventions aimed at improving child health.
    JEL: O12 Q53
    Date: 2019–07
  10. By: Massimo Filippini (Department of Management, Technology and Economics (D-MTEC), Swiss Federal Institute of Technology in Zurich (ETH Zurich), Switzerland; Institute of Economics (IdEP), Università della Svizzera Italiana (USI), Lugano, Switzerland); Giuliano Masiero (Department of Management, Information and Production Engineering, University of Bergamo, Italy; Institute of Economics (IdEP), Università della Svizzera italiana, Switzerland); Sandro Steinbach (Department of Management, Technology and Economics (D-MTEC), Swiss Federal Institute of Technology in Zurich (ETH Zurich), Switzerland)
    Abstract: Ambient air pollution is the environmental factor with the most significant impact on human health. Several epidemiological studies provide evidence for an association between ambient air pollution and human health. However, the recent economic literature has challenged the identification strategy used in these studies. This paper contributes to the ongoing discussion by investigating the association between ambient air pollution and morbidity using hospital admission data from Switzerland. Our identification strategy rests on the construction of geographically explicit pollution measures derived from a dispersion model that replicates atmospheric conditions and accounts for several emission sources. The reduced form estimates account for location and time fixed effects and show that ambient air pollution has a substantial impact on hospital admissions. In particular, we show that SO2 and NO2 are positively associated with admission rates for coronary artery and cerebrovascular diseases while we find no similar correlation for PM10 and O3. Our robustness checks support these findings and suggest that dispersion models can help in reducing the measurement error inherent to pollution exposure measures based on station-level pollution data. Therefore, our results may contribute to a more accurate evaluation of future environmental policies aiming at a reduction of ambient air pollution exposure.
    Keywords: Ambient air pollution, dispersion model, hospital admissions, count panel data
    JEL: I10 Q51 Q53
    Date: 2019–07
  11. By: Vinish Shrestha (Department of Economics, Towson University)
    Abstract: Recent studies have highlighted the importance of locality on well-being indicators such as health, later-life income, formation of human capital and fertility outcomes. By using data from the National Vital Statistics System, this paper provides an in-depth investigation of the well-documented relationship between mother's education and in- fant health. The study focuses on differential effects of mother's education on infant health outcomes across localities based on income status by using birthweight and low birthweight as measures for infant health. I find substantial non-linear effects of mothers' high school completion on infants' health outcomes and such effects are masked when specifying mother's education as a linear variable. More importantly, mother's education and infant health relationship is concentrated in relatively poorer geographic areas. This can partially be explained by drastic improvements in utilization of health services among educated mothers residing in poorer areas compared to mothers with lower levels of education. The overall findings imply that mother's education can act as a substitute for lack of external health inputs and provides cushion against adverse environmental factors in poorer areas.
    Keywords: Returns to Education, Infant Health, Birthweight, Poverty.
    JEL: I10 I30
    Date: 2019–08
  12. By: Anne-Line Koch Helsø; Nicola Pierri; Adelina Yanyue Wang
    Abstract: We study the costs of hospitalizations on patients’ earnings and labor supply, using the universe of hospital admissions in Denmark and full-population tax data. We evaluate the quality of treatment based on its ability to mitigate the labor market consequences of a given diagnosis and propose a new measure of hospital quality, the "Adjusted Earning Losses" (AEL). We find a 4 percentage points difference in lost earnings between the best and worst large Danish hospitals, all else equal. We show that AEL contains significant additional information relative to traditional measures and does not suffer from worse selection issues. We also document a large decline in the labor cost of hospitalizations over time, with large variations across diseases. We find that the average post-hospitalization reduction in labor earnings declined by 25 percent (50 percent) on the intensive (extensive) margin between 1998 and 2012.
    Date: 2019–08–16
  13. By: Abeliansky, Ana Lucia; Beulmann, Matthias
    Abstract: We investigate how an increase in the robot intensity (the ratio of industrial robots over employment) affects the self-reported mental health of workers in Germany. To do so, we combine individual mental health data from the German Socioeconomic Panel with the deliveries of robots to 21 German manufacturing sectors provided by the International Federation of Robotics for the period 2002-2014 (every two years). Controlling for a range of individual and sectoral characteristics, and employing individual-, time- and sectoral fixed effects, we find that an increase in robot intensity of 10% is associated with an average decrease of 0.59% of the average mental health standard deviation. This suggests that in a fast automating sector (i.e. rubber and plastics), where the robot intensity increased by approximately 2000%, mental health would have decreased by 118% of one standard deviation. This effect seems to be driven by job security fears of individuals working in noninteractive jobs and the fear of a decline in an individual's economic situation. Moreover, further sample divisions into low, middle and high occupational groups shows that the negative effects are affecting mostly the middle-level occupational group. Splitting the sample according to different age groups shows that the mental health of younger workers is the most vulnerable to an increase in automation. Results are also robust to instrumenting the stock of robots, and to different changes in the sample.
    Keywords: Mental Health,Industrial Robots,Germany,Job Loss Fear,Job Polarization
    JEL: I10 O30 I31 J6
    Date: 2019
  14. By: Giesecke, Matthias
    Abstract: I estimate the effect of retirement on mortality, exploiting two discontinuities at age-based eligibility thresholds for pension claiming in Germany. The analysis is based on unique social security records that document the age at death for the universe of participants in the German public pension system. Using variation from bunching of retirements at age-based eligibility thresholds, I demonstrate that retirement can have both mortality-decreasing and mortality-increasing effects, depending on the group of retirees who comply to eligibility at each threshold. To reconcile heterogeneous effects with likewise mixed results from the literature I provide evidence that the retirement-mortality nexus is driven by the activity change at retirement.
    Keywords: retirement,mortality,age-based eligibility thresholds,regression discontinuity design
    JEL: H55 I12 J14 J26
    Date: 2019
  15. By: Dow, Wiiliam H; Godoey, Anna; Lowenstein, Christopher A; Reich, Michael
    Abstract: Midlife mortality has risen steadily in the U.S. since the 1990s for non-Hispanic whites without a bachelor’s degree, and since 2013 for Hispanics and African-Americans who lack a bachelor’s degree. These increases largely reflect increased mortality from alcohol poisoning, drug overdose and suicide. We investigate whether these “deaths of despair” trends have been mitigated by two key policies aimed at raising incomes for low wage workers: the minimum wage and the earned income tax credit (EITC). To do so, we leverage state variation in policies over time to estimate difference-in-differences models of drug overdose deaths and suicides, using data on cause-specific mortality rates from 1999-2015. Our causal models find no significant effects of the minimum wage and EITC on drug-related mortality. However, higher minimum wages and EITCs significantly reduce non-drug suicides. A 10 percent increase in the minimum wage reduces non-drug suicides among adults with high school or less by 3.6 percent; a 10 percent increase in the EITC reduces suicides among this group by 5.5 percent. Our estimated models do not find significant effects for a college-educated placebo sample. Event-study models confirm parallel pre-trends, further supporting the validity of our causal research design. Our estimates suggest that increasing both the minimum wage and the EITC by 10 percent would likely prevent a combined total of around 1230 suicides each year.
    Keywords: Social and Behavioral Sciences, MINIMUM WAGE, LIVING WAGE
    Date: 2019–04–01
  16. By: Banerjee, Abhijit; La Ferrara, Eliana; Orozco, Victor
    Abstract: We test the effectiveness of an entertainment education TV series, MTV Shuga, aimed at providing information and changing attitudes and behaviors related to HIV/AIDS. Using a simple model we show that "edutainment" can work through an `individual' or a `social' channel. We conducted a randomized controlled trial in urban Nigeria where young viewers were exposed to MTV Shuga or to a placebo TV series. Among those exposed to MTV Shuga, we created additional variation in the `social messages' they received and in the people with whom they watched the show. We find significant improvements in knowledge and attitudes towards HIV and risky sexual behavior. Treated subjects are twice as likely to get tested for HIV eight months after the intervention. We also find reductions in STDs among women. These effects are stronger for viewers who report being more involved with the narrative, consistent with the psychological underpinnings of "edutainment". Our experimental manipulations of the social norm component did not produce significantly different results from the main treatment. The `individual' effect of edutainment thus seems to have prevailed in the context of our study.
    Date: 2019–07
  17. By: Blanco-Perez, Cristina (University of Ottawa); Brodeur, Abel (University of Ottawa)
    Abstract: In February 2015, the editors of eight health economics journals sent out an editorial statement which aims to reduce the extent of specification searching and reminds referees to accept studies that: "have potential scientific and publication merit regardless of whether such studies' empirical findings do or do not reject null hypotheses". Guided by a pre-analysis, we test whether the editorial statement decreased the extent of publication bias. Our differences-in-differences estimates suggest that the statement decreased the proportion of tests rejecting the null hypothesis by 18 percentage points. Our findings suggest that incentives may be aligned to promote more transparent research.
    Keywords: publication bias, specification searching, pre-analysis plan, research in economics, incentives to publish
    JEL: A11 C13 C44 I10
    Date: 2019–07
  18. By: Alberto Marino; Luca Lorenzoni
    Abstract: The measurement of the impact of technology as a driver of health care expenditure is complex since technological effects are closely interlinked with other determinants such as income and the composition and health status of a population. Furthermore, the impact of the supply of advances in technology on health expenditure cannot be considered in isolation from demand and the policy context and the broader institutional context governing the adoption of new technologies. Hence, it is the interaction of supply and demand factors and the context that determine the ultimate level of technology use. There are also important quality changes that come with technological progress that also have monetary costs and benefits attached. Modelling quality improvements, both in terms of benefits within the health system and outside (e.g. its impact on life expectancy, ageing populations, productivity and GDP), is a challenging task, and no macroeconomic models to date have tried to capture them. This paper presents a comprehensive literature review of the impact of technological advances on health expenditure growth, the ‘cost’ side of the equation.
    JEL: H51 I11 O33
    Date: 2019–08–22
  19. By: Greene, W.H.;; Harris, M.N.;; Knott, R.;; Rice, N.;
    Abstract: Anchoring vignettes have been proposed as a way to correct for differential item functioning when individuals self-assess their health, or other aspects of their circumstances on an ordered categorical scale. The model relies on two key underlying assumptions of response consistency and vignette equivalence. Adopting a modified specification of the boundary equations in the compound hierarchical ordered probit model this paper develops joint and separate tests of these assumptions based on a score approach. Monte Carlo simulations show that the tests have good size and power properties in finite samples. We provide an application of the test to data from the Survey of Health, Aging and Retirement in Europe (SHARE, using self-reported data on pain. The tests are easy to implement, only requiring estimation of the restricted model under the null hypothesis.
    Keywords: ordered response models; anchoring vignettes; differential item functioning; self-assessments; score test; CHOPIT;
    Date: 2019–08
  20. By: Yiwei Chen; Hui Ding; Min Yu; Jieming Zhong; Ruying Hu; Xiangyu Chen; Chunmei Wang; Kaixu Xie; Karen Eggleston
    Abstract: Health systems globally face increasing morbidity and mortality from chronic disease, yet many—especially in low- and middle-income countries—lack strong primary care. We analyze China’s efforts to promote primary care management for insured rural Chinese with chronic disease, analyzing unique panel data for over 70,000 rural Chinese 2011-2015. Our study design uses variation in management intensity generated by administrative and geographic boundaries—regression analyses based on 14 pairs of villages within two kilometers of each other but managed by different townships. Utilizing this plausibly exogenous variation, we find that patients residing in a village within a township with more intensive primary care management, compared to neighbors with less intensive management, had more primary care visits, fewer specialist visits, fewer hospital admissions, and lower inpatient spending. No such effects are evident in a placebo treatment year. Exploring the mechanism, we find that patients with more intensive primary care management exhibited better drug adherence as measured by filled prescriptions. A back-of-the-envelope estimate of welfare suggests that the resource savings from avoided inpatient admissions substantially outweigh the costs of the program.
    JEL: I11 I18
    Date: 2019–07

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