International Journal of Health Economics and Management最新文献

In the United States as in other developed countries, the take-up of Long-Term Care (LTC) insurance remains very low, suggesting that many individuals underestimate their future needs for professional LTC services. This paper examines the relationship between subjective expectations and LTC insurance demand, with a particular focus on miscalibration of survival beliefs. Using 12 waves of the Health and Retirement Study (1996-2018), we estimate various random effects linear probability models of LTC insurance take-up among individuals aged 50-75 years. We rely on two self-reported expectation measures: the probability of survival and the probability of nursing home entry. We then classify individuals into three groups - consistent, positive deviation, and negative deviation - based on the difference between subjective survival beliefs and life-table benchmarks. Robustness analyses are carried using alternative miscalibration measures, age groups and control variables. Our findings reveal strong heterogeneity. Individuals whose beliefs are consistent with life-table probabilities purchase more LTC insurance when they expect to live longer, in line with higher anticipated old-age expenditures. By contrast, individuals who substantially overestimate survival ("positive deviation" group) display no systematic response to either type of expectation, which could be related to cognitive difficulties in projecting future needs. Those who underestimate survival ("negative deviation" group) are responsive to nursing home expectations but less so to survival, indicating that they may anticipate short-term care needs but not long-term expenditures. Taken together, these results suggest that miscalibration of survival beliefs is an important determinant of insurance demand. They highlight that underestimation and overestimation reflect different mechanisms - potential private health information in the former case and cognitive limitations in the latter - ultimately contributing to the persistently low take-up of LTC insurance in the U.S.

French legislation requires large and medium-sized hospitals to publicly report their greenhouse gas (GHG) emissions. Yet, many hospitals fail to comply with this regulation, while others report voluntarily. The organizational drivers behind this behavior remain underexplored. This study examines whether hospitals disclose their GHG emissions as part of a broader strategy to differentiate themselves-similar to how they report patient satisfaction scores to signal quality. We explore whether carbon reporting is used as a vertical differentiation strategy in the French healthcare system. We used a mixed-methods approach. First, we analyzed national administrative data to test whether reporting GHG emissions is associated with reporting patient satisfaction scores. Second, we conducted semi-structured interviews with hospital managers to understand the motivations behind emissions reporting. Quantitatively, we found no significant association between the two types of reporting. Hospitals do not appear to use GHG emissions disclosure and patient satisfaction scores as part of the same signaling strategy. Qualitative findings confirmed that GHG reporting is primarily driven by internal factors such as executive leadership, process improvement, and organizational values, rather than external differentiation or patient demand. Carbon reporting in French hospitals is not currently used as a differentiation strategy. Stronger regulatory enforcement is needed to ensure compliance. In addition, hospitals require support-through methodological guidance, training, and the development of dedicated sustainability roles-to integrate environmental performance into their management systems and contribute meaningfully to healthcare decarbonization.

This study applies econometric methodologies to conduct a quantitative assessment of the overall impact of occupational accidents on changes in firms' labor productivity. In particular, it examines whether the magnitude of this impact varies according to the technological intensity required for production and further explores the mechanisms through which occupational accidents affect productivity, as well as the duration of these effects. The empirical results demonstrate that increases in occupational accident rates are significantly associated with declines (1%p increase in the accident rate reduces 3.9% in the average labor productivity) in labor productivity, with such adverse effects evident in both very low- and very high-technology firms. Moreover, the analysis identifies a self-reinforcing vicious cycle for approximately 3 to 4 years, wherein higher accident rates lead to productivity deterioration, exacerbating accident incidence. The findings also indicate that a substantial period (about 2 to 3 years) is required for firms to recover from productivity losses attributable to occupational accidents. Our findings catalyze firms to undertake proactive and voluntary measures to prevent occupational accidents and will provide an empirical foundation for policy interventions targeting vulnerable groups that are disproportionately affected by productivity losses resulting from such incidents.

This research conducts the first comprehensive analysis of how prenatal economic fluctuations affect postpartum depression and documents its counter-cyclicality. Using population-based claims data, we examine outpatient utilization related to mental disorders among women in Taiwan during the six-month, nine-month, and one-year postpartum periods from 1998 to 2012. The results indicate that medical utilization for postpartum depression within the six-month and nine-month postpartum periods is influenced by economic conditions during the second trimester of pregnancy. This study also aims to understand the mediating channels behind the relationship between postpartum depression and prenatal economic activity. We find that negative prenatal economic shocks lead to higher outpatient expenses for conditions such as excessive weight gain, nutritional deficiency, depressive disorders, hypertension, and sleep disorders during pregnancy, all of which can deteriorate maternal postpartum mental health. Furthermore, our study highlights that postpartum depression medical utilization among low-income mothers is particularly sensitive to prenatal economic fluctuations. These findings suggest that low-income mothers, who may have limited resilience and fewer resources during economic downturns, are more likely to experience nutritional deficiencies and increased maternal stress, ultimately leading to a deterioration in postpartum mental health.