Expected longevity is an important factor influencing older individuals' decisions such as consumption, savings, purchase of life insurance and annuities, claiming of Social Security benefits, and labor supply. It has also been shown to be a good predictor of actual longevity, which in turn is highly correlated with health status. A relatively new literature on health investments under uncertainty, which builds upon the seminal work by Grossman (1972), has directly linked longevity with characteristics, behaviors, and decisions by utility maximizing agents. Our empirical model can be understood within that theoretical framework as estimating a production function of longevity. Using longitudinal data from the Health and Retirement Study, we directly incorporate health dynamics in explaining the variation in expected longevities, and compare two alternative measures of health dynamics: the self-reported health change, and the computed health change based on selfreports of health status. In 38% of the reports in our sample, computed health changes are inconsistent with the direct report on health changes over time. And another 15% of the sample can suffer from information losses if computed changes are used to assess changes in actual health. These potentially serious problems raise doubts regarding the use and interpretation of the computed health changes and even the lagged measures of self-reported health as controls for health dynamics in a variety of empirical settings. Our empirical results, controlling for both subjective and objective measures of health status and unobserved heterogeneity in reporting, suggest that self-reported health changes are a preferred measure of health dynamics.
As the global population increases and cities expand, increasing social needs and ecosystem degradation generally coexist, especially in China’s urban agglomerations. Identifying ecological security patterns (ESPs) for urban agglomerations serves as an effective way to sustain regional ecological security and promote harmonious ecological conservation and economic development. Focusing on the Fujian Delta Urban Agglomeration (FDUA) as an example, this study aims to present a framework for linking the supply and demand of ecosystem services (ESs) to identify ESPs in 2020. First, the ecological sources are delimited by coupling the supply and demand of four critical ESs (carbon storage, water provision, grain production, and outdoor recreation). Afterward, the resistance coefficient is modified using nighttime light intensity data and the ecological risk index, the second of which combines the effects of the soil erosion sensitivity index, the geological disaster risk index, and the land desertification risk index. Then, ecological corridors are determined by employing the minimum cumulative resistance method. With the integration of ecological sources and corridors, the ESPs of the FDUA can be identified. The results show a distinct supply–demand mismatch for ESs, with supply exhibiting an upward gradient from coastal cities to inland mountain cities and demand showing the opposite trend. The ESPs consist of 8359 km2 of ecological sources that are predominantly forests, 171 ecological corridors with a total length of 789.04 km, 34 pinch points, 26 barriers, and 48 break points. This paper presents a realizable approach for constructing ESPs for urban agglomerations, which will help decision makers optimize ecological sources and ecological protection policies.
This article investigates the impact of Certificate of Need (CON) laws on competition in the inpatient care market. One of the major criticisms of these laws is that it may hinder competition in the health care market, which can lead to higher prices. However, from a theoretical standpoint, CON laws could also promote competition by limiting excessive expansion from incumbents. Our main conclusion is that CON laws by and large enhanced competition in the inpatient market during the period of our study. This indicates that the effects of CON laws to hinder predatory behavior could dominate its effects of preventing new entrants into the inpatient care market. We do not find statistically significant evidence to reject the exogeneity assumption of either CON laws or their stringency in our study. We also find factors such as proportion of population aged 18-44, proportion of Asian American population, obesity rate, political environment, etc., in a state significantly impact competition. Our findings could shed some light to public policy makers when deciding the appropriate health programs or legislative framework to promote health care market competition and thereby facilitate quality health care.
Traditional course teaching evaluation models face increasing challenges in higher education due to their limitations in measuring qualitative indicators. To address this issue, this study constructs a classroom teaching quality evaluation system based on YOLOv5 object detection technology and the five major processes of course teaching management. Here, Fermatean fuzzy set (FFS) is introduced to express the uncertainty in the evaluation process. The core of this study is to establish a scientifically effective comprehensive evaluation model for university classroom teaching quality. Specifically, this model utilizes the minimum discriminative information principle and combines the order relation analysis method (G1 method) and the FFS entropy weighting method to determine attribute weights for weighted attribution. Thereafter, the proposed generalized distance measurement formula is utilized to enhance the technique for order preference by similarity to ideal solution (TOPSIS) for assessing similarity, thereby achieving the objective of evaluating classroom teaching. Eventually, the effectiveness and practicality of the evaluation model are validated through case studies and comparisons with other methods.
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