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on Health Economics |
| By: | Benjamin R. Handel; Louis-Jonas Heizlsperger; Jonas Knecht; Jonathan T. Kolstad; Ulrike Malmendier; Filip Matějka |
| Abstract: | We study how situational fluctuations in cognitive capacity shape behavior in high-stakes, real-time decision-making. Drawing on recent advances in behavioral economics that revolve around inattention, cognition and complexity, we show that cognitive load influences how physicians in emergency departments allocate mental effort and attention when making diagnostic and treatment decisions. We use quasi-random variation in patient-physician pairings, along with granular electronic medical record and audit-log data from many clinical interactions, to show that, under higher cognitive load, physicians substitute mental deliberation with more numerous but less precise diagnostic actions. Specifically, we document that higher load (i) increases the total number of orders of diagnostic tests (ii) reduces the use of targeted, but more uncommon tests (iii) increases the use of common tests and (iv) increases uncertainty in diagnostic beliefs. Cognitive load impacts downstream inpatient admission from the emergency department: a physician in the highest cognitive load decile increases admissions by 28% relative to the same physician in the lowest cognitive load decile, for the exact same kind of patient. These results offer novel field-based evidence on the dynamics of attention and belief formation, and shed light on how cognitive constraints shape diagnostic behavior in complex, real-world environments. |
| JEL: | D83 D91 I11 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35034 |
| By: | D. Mark Anderson; Ron Diris; Raymond Montizaan; Daniel I. Rees |
| Abstract: | Using data on applicants to Dutch medical schools and their older relatives (i.e., parents, aunts, and uncles ages 60+), we estimate the effect of personal access to medical expertise on vaccine hesitancy. Leveraging variation in lottery outcomes that determine admission to medical schools, we find that having a physician in the family increases the likelihood of complying with government recommendations that anyone over the age of 59 receive a second booster dose of a COVID-19 vaccine. Our estimated effects are strongest for having a female physician in the family, suggesting important gender-based differences in how medical expertise is communicated. |
| JEL: | D83 I12 I18 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35019 |
| By: | Blundell, Richard; Britton, Jack; Dias, Monica Costa; French, Eric; Zou, Weijian |
| Abstract: | Using data from the Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA), we estimate the impact of health on employment for individuals close to retirement age. Estimating the model separately by race and gender, we find that racial differences in employment can be partly explained by the worse health of minorities as well as the larger impact of health on employment for minorities. |
| Keywords: | race; gender; health; employment |
| JEL: | R14 J01 |
| Date: | 2026–06–30 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:137779 |
| By: | Brenøe, Anne (University of Zurich); Stearns, Jenna (University of California, Davis); Martin, Richard (University of Bristol) |
| Abstract: | Using data from the only large-scale randomized controlled trial promoting prolonged exclusive breastfeeding, we study how the intervention affected child health and why. The intervention increased weight-for-age in infancy, with effects persisting through adolescence. We show that treated infants were breastfed more and received less water, juice, and other liquids, resulting in a more calorie-dense diet. A mediation analysis indicates that increased caloric intake explains a large share of the early weight gain, while reduced illness explains little. These findings suggest that, in this setting, the main benefits of breastfeeding promotion for physical growth came from improved nutrition. More broadly, the results highlight that the effects of breastfeeding promotion depend on the local alternatives to breast milk and may differ in settings where infant formula or other more nutritious substitutes are the main alternative. |
| Keywords: | breastfeeding, infant feeding, child health, the Promotion of Breastfeeding Intervention Trial (PROBIT) |
| JEL: | I10 J13 J24 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18495 |
| By: | Pierre Dubois; Ariel Pakes |
| Abstract: | Direct-to-consumer advertising (DTCA) of prescription drugs may expand treatment access but also risks promoting overuse and business stealing without generating welfare gains. Among developed nations, only the United States and New Zealand permit DTCA, whereas detailing - promotion aimed at prescribers - is widely practiced. This paper analyzes the impact of DTCA on profits by modeling a counterfactual environment in which DTCA is banned. This is implemented through a dynamic equilibrium framework that adapts the Experience-Based Equilibrium (Fershtman and Pakes, 2012) for empirical analysis. EBE incorporates constraints on the cognitive abilities of decision-makers and mitigates researchers’ computational concerns. Using data from four therapeutic markets, we first validate the EBE’s ability to replicate observed advertising patterns, then simulate counterfactual DTCA bans. Both the data and our empirical work indicate that DTCA and detailing are strong complements, and our results illuminate the need to account for this when evaluating the ban. The ban leads firms to reduce detailing and has a negative effect on profits in all markets, but the magnitude of the effect varies from under 5% in the market for Ulcer to 27.5% for Asthma medications. |
| JEL: | I0 I1 L2 M37 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35025 |
| By: | R. Bawack (Audencia Business School); D. Dennehy; C. A. Kumi; W. Boutchouang |
| Abstract: | This study explores the impact of Artificial Intelligence Analytics (AIA) capability, supported by wearable technology, on patient-centered care in the healthcare systems of low- and middle-income countries (LMICs). Focusing on Cameroon and Ghana, a cross-country survey assessed how these digital health tools influence perceptions of effective patient-professional communication, empathy, patient involvement, and access to essential healthcare. Using big data analytics capability theory adapted to healthcare and structural equation modeling, the findings reveal that AIA capability significantly improves perceptions of patient-centered care, particularly regarding communication and empathy, with differences between the two countries. Although eHealth literacy enhances positive perceptions of care, it does not significantly moderate the relationship between AIA capability and patient-centered care. This study highlights the importance of context-specific approaches in adopting wearable health devices in LMICs and adds to the growing literature on AI-powered wearables in underrepresented regions. |
| Keywords: | Artificial Intelligence, analytics, wearable, patient-centered care, eHealth literacy, big data analytics capability |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05563830 |
| By: | Andreas Stoller; Martin Huber |
| Abstract: | We estimate the effect of cigarette price and tax increases on smoking rates using Eurobarometer survey data from 27 European Union countries between 2012 and 2020. Following a difference-in-differences approach, we compare individuals exposed to large price and tax increases with those in stable price and tax environments. Estimation is based on a difference-in-differences estimator with double machine learning, which relaxes the functional form assumptions typically imposed by parametric approaches such as two-way fixed effects. Our results indicate that tax increases reduce smoking rates among individuals who smoke at least once per month and among daily smokers. The reduction is primarily driven by individuals aged 15-24. We examine the sensitivity of our findings to functional form assumptions and treatment definitions. While estimates are robust to alternative functional form assumptions, they are sensitive to whether the treatment is defined as binary or continuous. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.05841 |
| By: | Hirsch, Michael (RWTH Aachen University); Grund, Christian (RWTH Aachen University) |
| Abstract: | In this study, we examine the influence of air pollution, measured by particulate matter concentration (PM_10 and PM_2.5), on sabotage in rank order tournaments. To achieve this, we use player-level data from German Soccer Bundesliga players between 2009 and 2024, which we link with hourly pollution values on the exact match location and kick-off time. This research design addresses key identification problems in estimating the effect of air pollution on non-health outcomes. Our results suggest that an increase in particulate matter concentration has a statistically significant effect on destructive efforts (i.e. competitive sabotage), measured in fouls committed by a player. If particulate matter pollution measured in PM_10 (PM_2.5) increases by 10 μg/m^3, the number of fouls committed increases by 0.6% (0.9%). We also find strong evidence that this effect is driven primarily by players from weaker teams (underdogs). |
| Keywords: | air pollution, sabotage, tournaments |
| JEL: | M5 Q53 L83 J83 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18512 |
| By: | Cylus, Jonathan; Thomson, Sarah; Habicht, Triin; Evetovits, Tamás |
| Abstract: | Global and regional commitments to universal health coverage emphasize reducing financial hardship due to out-ofpocket payments for health care. Despite this, many countries continue to rely on user charges—either to raise revenue or reduce demand—especially under fiscal pressure. We conducted a narrative review of academic literature on the theoretical basis for and empirical effects of user charges in health systems. This was complemented by recent case studies from Slovenia, Estonia, and Cyprus, selected to illustrate diverse approaches to user charge policy under fiscal constraints. Common arguments in favour of user charges are that they can mitigate excess health care consumption and generate revenues. However, evidence suggests they often deter necessary care and lead to financial hardship, especially for low-income groups. Country case studies reveal varied approaches towards user charges in the context of fiscal pressure: Estonia increased co-payments despite prior efforts to improve financial protection; Slovenia eliminated user charges by introducing a flat levy to generate additional revenue; and Cyprus dramatically reduced its reliance on out-of-pocket payments by increasing public spending on health. Growing fiscal pressure may tempt countries to implement or increase user charges. However, doing so without adequate protective mechanisms can increase financial hardship, poverty and unmet health needs. Policymakers should prioritize pre-payment mechanisms and equity-oriented safeguards to ensure sustainable, fair and affordable access to health care. Continuous monitoring of financial hardship remains essential to inform policy decisions. |
| JEL: | J1 |
| Date: | 2026–03–20 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:137838 |
| By: | Erik Heitfield |
| Abstract: | This paper examines how model uncertainty affects the price of homeowners insurance in Florida. We use unique data on expected loss rate projections from seven hurricane risk models approved by regulators for use in Florida property insurance rate filings to quantify model uncertainty. By combining these data with newly published information on local property insurance markets, we are able to empirically test the relationship between model uncertainty and insurance premiums across Florida ZIP codes and over time. Controlling for confounding variables and time-invariant latent factors that may be correlated with observed variables, we find strong empirical support for the hypothesis that greater dispersion among model forecasts leads to higher homeowners insurance premiums. Our findings suggest that, had model dispersion been ten percent lower than that observed 2021, a typical Florida homeowner would have saved $50 to $90 on her annual homeowners insurance premium. |
| Keywords: | Model uncertainty; Natural hazards; Risk management; Insurance |
| JEL: | D81 G22 G32 G41 |
| Date: | 2026–03–23 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:102998 |
| By: | Ying, Xiangji; Li, Tianjing; McKenzie, Joanne; Page, Matthew James (Monash University); Ninan, Kiran; Oberste, Jean-Pierre; Vorland, Colby J.; Brown, Andrew William (Indiana University School of Public Health-Bloomington); Qureshi, Riaz; DeVito, Nicholas J |
| Abstract: | Defining outcomes completely before conducting clinical trials helps to mitigate reporting biases; however, there is limited guidance to help investigators define outcomes completely. We aimed to develop a structured approach for defining trial outcomes completely and consistently. We reviewed literature, developed preliminary rules for defining outcomes, and refined them iteratively. We randomly selected randomized controlled trials (RCTs) on ClinicalTrials.gov that registered before their start dates and posted results by January 4, 2024. The 225 included RCTs evaluated 3, 424 outcomes. Two raters independently applied preliminary rules to define each outcome. When raters encountered outcomes they could not define, we refined the rules. We continued this process until no further changes were needed. We discussed and finalized our approach in a consensus meeting. We define an “outcome” as a value for each participant that will be used in analysis to generate study results. A complete outcome definition includes six elements: outcome domain, specific measurement, specific metric, cutoff, variable type, and timepoint. We developed rules for naming specific measurements for both subjective and objective outcomes. We expanded on prior work by developing more comprehensive categories for specific metrics. We introduced "cutoff" as a distinct element with three subelements. To clarify the boundary between outcome definitions and statistical methods, we replaced a previously described element, "method of aggregation, " with "variable type, " which refers to whether the value for each individual is continuous or categorical. Trialists and sponsors could use this approach alongside other guidelines to define outcomes in trial registrations, protocols, and result reports. |
| Date: | 2026–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:osf:metaar:5wrsm_v1 |
| By: | Selin Ozdamar |
| Abstract: | Pandemics cause severe shocks that hit vulnerable groups the hardest, yet there is still limited research on how public health spending can help mitigate these unequal impacts. This paper investigates the dynamic impact of pandemic shocks on inclusive growth (conceptualized through GDP per capita, disposable-income inequality, and household consumption) across low and high public health spending environments. Utilizing the local projections method on a balanced panel of 114 countries from 2000 to 2019, we analyze public health spending effect on inclusive growth indicators. Our findings reveal that pandemics trigger significant and persistent losses in output and consumption, particularly in low-income economies. Notably, while disposable-income inequality shows insignificant responses, sharp declines in consumption uncover substantial welfare deterioration that aggregate income metrics often miss. Crucially, we demonstrate that high public health expenditure acts as a critical automatic stabilizer; countries with robust health financing exhibit minimal economic scarring, whereas low-spending regimes suffer deep, lasting contractions. These results position public health expenditure as a strategic investment in economic resilience rather than a mere social cost and emphasize the need for a multidimensional policy focus on health-sector financing to protect inclusive growth against future systemic shocks. |
| Keywords: | Pandemics, Inclusive Growth, Public Health Expenditure, Inequality, Poverty, Local Projections. |
| JEL: | I15 I18 O47 E62 H51 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:ise:remwps:wp04122026 |