Health economics最新文献

This paper demonstrates how optimal policy learning can inform the targeted allocation of Indonesia's two subsidized health insurance programmes. Using national survey data, we develop policy rules aimed at minimizing “catastrophic health expenditure” among enrollees of APBD or APBN, the two government-funded schemes. Employing a super learner ensemble approach, we use regression and machine learning methods of varying complexity to estimate conditional average treatment effects and construct policy rules to optimize program benefits, both with and without budget constraints. We find that the financial impact of APBD enrollment over APBN differs with household characteristics, particularly demographic composition, socioeconomic status, and geography. Households assigned to APBD under the policy rule are typically urban-based with better facilities, whereas rural households with less accessible healthcare are assigned to APBN—a pattern intensified under budget constraints. Both constrained and unconstrained optimal policy assignments show lower expected catastrophic expenditure risk than the current assignment strategy. This study contributes to the literature on heterogeneous treatment effects, optimal policy leaning, and health financing in developing countries, showcasing data-driven solutions for more equitable resource allocation in public health insurance contexts.

This study investigates the impact of transportation infrastructure financed by Chinese aid on child health in 11 sub-Saharan African countries using Demographic and Health Survey data matched with the precise geospatial features of transportation infrastructure. We find that an additional year of exposure to transportation infrastructure significantly increases children's height-for-age z-scores by 0.041 standard deviations and reduces the likelihood of stunting by 1.6 percentage points among urban households without migration experience, relative to children in the control group. Our analysis, which employs mother fixed-effects specifications, yields consistent results. Notably, we find that the positive effects of transportation infrastructure are primarily attributable to exposure during the construction phase of aid projects. The increased likelihood of mothers securing paid employment during this period may serve as a critical mechanism driving the observed effects of exposure to transportation infrastructure.

The vast majority of youth e-cigarette users consume flavored e-cigarettes, raising concerns from public health advocates that flavors may drive youth initiation and continued use of e-cigarettes. Flavors drew further notice from the public health community following the sudden outbreak of lung injury among vapers in 2019, prompting several states to enact sweeping bans on flavored e-cigarettes. In this study, we examine the effects of these comprehensive bans on e-cigarette use and potential spillovers into other tobacco use by youth, young adults, and adults. We utilize both standard difference-in-differences (DID) and synthetic DID methods, in conjunction with four national data sets. We find evidence that young adults decrease their use of e-cigarettes by about two to three percentage points, while increasing cigarette use. For youth, there is some suggestive evidence of increasing cigarette use, though these results are undermined by pre-trend differences between treatment and control units. The bans have no effect on e-cigarette and smoking participation among adults 25 and over. Our findings suggest that statewide comprehensive flavor bans may have generated an unintended consequence by encouraging substitution toward traditional smoking in some populations.

Noneconomic damage caps are controversial because they seek to balance uncertain benefits through reductions in physician precautionary costs, against uncertain harms to patient welfare. Opposing policy actions at the state-level reflect this controversy as some states have enacted noneconomic damage caps over the past few decades while others repealed their caps. Our difference-in-differences analyses suggest that repeals increase premiums. These increases are larger after State Supreme Court decisions, affecting all cases in a state, compared with State Circuit Court decisions affecting only specific cases. Magnitudes differ by physician specialty, with larger effects observed in obstetrics/gynecology and general surgery, compared with internal medicine. Our estimates of these repeals are larger than estimates on enactments reported in the literature, suggesting a potential asymmetry between enacting and repealing damage caps.

This paper examines the effect of robots on workplace injury benefits paid in South Korea. Using the administrative data on worker's compensation, I found that the increase in robot exposure contributes to the significant decline in the average benefit amount per covered worker, mainly driven by the reduction in the number of claims, rather than the size of claims. The effects are stronger, especially for serious cases such as permanent disability.

This article examines the Online Elicitation of Personal Utility Functions (OPUF) method as a novel approach for health state valuation. While OPUF offers a structured, modular alternative to traditional methods, it also presents notable challenges. Chief among these is its reliance on compositional trade-offs between health dimensions (e.g., pain, mobility, anxiety), which may inadequately reflect how individuals experience health holistically. Additionally, OPUF's use of numerical rating scales does not guarantee that resulting utility values exhibit interval properties—a requirement for robust interpretation in economic evaluations. To contextualize OPUF within the broader landscape of valuation methods, this article introduces a classification scheme outlining alternative approaches and their respective trade-offs in terms of precision, cognitive burden, and feasibility.