Search Results (20)

This study evaluates the utility derived by policyholders in a Danish pension company, from their life insurance coverages. We quantify the relative importance policyholders assign to their existing coverages versus a hypothetical complete coverage scenario, thereby measuring the implicit priority of their current coverage. By analyzing these implicit priorities based on individual attributes such as age, financial situation, and company agreement limitations, we gain a comprehensive understanding of policyholders’ evaluations of their current life insurance coverage. Utilizing a continuous-time life cycle model, we optimize consumption and life insurance decisions during the accumulation phase, applying well-established theoretical findings to actual data. Our analysis identifies trends, outliers, and insights that can inform potential improvements in life insurance coverage. This tool aims to assist policyholders in prioritizing their coverage according to their life situations and provides a foundation for advisory dialogues and product development. Full article

Public buildings are crucial to creating healthy and sustainable cities. These buildings promote social cohesion and enrich urban life by transforming existing facilities into hybrid models that integrate medical content. Historical developments highlight shifts in residential, economic, and healthcare infrastructure. The healthcare system aims to enhance public health while ensuring financial equity. Reforms in healthcare privatization, governed by public health and insurance policies, involve liberalizing service provision and are supported by the Ministry of Health and Finance. This study examines how public buildings can adapt to enhance health and social sustainability. Through case studies, it assesses architectural adaptability in analyzing spatial, economic, and social impacts. Diagrams illustrate spatial dynamics, while surveys compare efficiency, sustainability, and user experience. Statistical analysis highlights the role of spatial adaptability in fostering sustainable urban environments. The results, which express significant differences between means for different locations and citizens’ satisfaction, suggest that the hypothesis offers substantial results in every area. Besides commercial programs in commercial buildings, healthcare also gives satisfactory results. This study advocates for adaptive architecture as a key strategy, aligning with evolving societal and health demands. Hybridizing healthcare facilities and commercial spaces transforms shopping centers into sustainable models, enhancing social cohesion and economic viability. Full article

This study measured the risk aversion of nineteen selected countries using Szpiro’s approach and analyzed its effect on life insurance demand. Additionally, income and education were included as control variables and tested for their effects on life insurance demand and risk aversion. The results show a positive effect of risk aversion on life insurance demand, while income has a positive effect and education has a negative effect. We also find that income positively affects risk aversion, while education negatively affects it. These findings support the increasing relative risk aversion hypothesis and have significant implications for life insurance demand and pricing analysis. Full article

Income is often viewed as the main determinant of life insurance demand. However, in the last two decades, the world’s life insurance penetration has continued to decrease even as income grows. This study investigates the relationship between income and life insurance demand using panel data from forty-one countries from 2013 to 2022, along with education and life expectancy as control variables. The study finds a non-monotonic relationship between income and life insurance penetration and between education and life insurance penetration, while life expectancy shows a monotonic relationship with life insurance penetration. This study provides significant policy implications for insurers to predict life insurance demand and suggests that non-high-income countries emphasize the improvement of their life insurance sector development. Full article

Background/Objectives: Maintaining functional independence and minimizing disability among older adults living in the community is paramount for mitigating rising care demands. Our study focused on shopping as a critical instrumental activity of daily living (ADL) to explore the association between shopping assistance and functional decline among older individuals receiving support through long-term care insurance (LTCI). Methods: This retrospective, cross-sectional study included 6202 participants aged >65 years living in a Japanese regional town receiving LTCI support, suggesting that they required assistance with local community life. Logistic regression analysis identified several factors associated with shopping assistance among the participants, including physical and cognitive functions, functional ADL, and psychobehavioral symptoms. Results: In male participants, walking dysfunction, short-term memory decline, decreased frequency of going outdoors, and decreased engagement in personal grooming were significantly associated with requiring shopping assistance. Conversely, in female participants, reduced physical function and walking performance were significantly associated with requiring shopping assistance, whereas dependence on personal grooming was less pronounced than in male participants. Conclusions: These findings suggest that, in addition to direct shopping assistance, tailored interventions targeting physical, cognitive, and ADL functions—while considering gender-specific needs—may help older adults maintain independence in shopping activities as part of their daily community life. Full article

We address the effect of local financial conditions on the demand for non-life insurance. We consider the spread between the interest rates faced by the insured on the local credit market and the return rates earned by the insurer on national or international financial markets, sketching how it influences the present value of an insurance policy; we then use the local invariance of the insurer’s returns to identify the effect on demand. Drawing on a panel of Italian provinces with ample variability in insurance density as well as borrowing conditions, we show that the demand for non-life insurance decreases with the borrowing rate. We separate between different non-life insurance lines, finding a stronger effect for the lines prevailing in advanced economic systems. Credit conditions turn out to be an important factor of non-life insurance development, and they help to explain the underdevelopment of insurance markets in Southern Italy. Full article

Demographic aging results in a growing number of older people in need of care in many regions all over the world. Germany has witnessed steady population aging for decades, prompting policymakers and other stakeholders to discuss how to fulfill the rapidly growing demand for care workers and finance the rising costs of long-term care. Informed decisions on this matter to ensure the sustainability of the statutory long-term care insurance system require reliable knowledge of the associated future costs. These need to be simulated based on well-designed forecast models that holistically include the complexity of the forecast problem, namely the demographic transition, epidemiological trends, concrete demand for and supply of specific care services, and the respective costs. Care risks heavily depend on demographics, both in absolute terms and according to severity. The number of persons in need of care, disaggregated by severity of disability, in turn, is the main driver of the remuneration that is paid by long-term care insurance. Therefore, detailed forecasts of the population and care rates are important ingredients for forecasts of long-term care insurance expenditures. We present a novel approach based on a stochastic demographic cohort-component approach that includes trends in age- and sex-specific care rates and the demand for specific care services, given changing preferences over the life course. The model is executed for Germany until the year 2050 as a case study. Full article

This study examines the determinants of life insurance ownership with a focus on rural areas and farming households in the United States. Utilizing data from online surveys conducted in 2019 and 2021, this paper explores how psychological factors, financial knowledge, and household characteristics influence life insurance ownership. Traditional indicators like wealth, income, and age were evaluated alongside less frequently discussed variables such as farm loans and rural residency. Machine learning techniques, including neural networks, Support Vector Machine modeling, Gradient Boosting, and logistic regression, were employed to identify the most robust predictors of life insurance demand. The findings reveal that farming-associated factors, particularly holding a farm loan and living in a farming household, significantly predict life insurance ownership. The study also highlights the complexity of life insurance demand, showing that financial education and management practices are critical determinants. This research underscores the need for tailored financial risk management strategies for rural and farming households and contributes to a nuanced understanding of life insurance demand in varying contexts. Full article

This study presents a novel approach to analyzing the present value of total profit for non-participating and participating insurance policies in order to determine the optimal profitability of non-participating and participating insurance policies based on applying the approach used in operations research to the field of finance. As such, a comprehensive insurance product evaluation model was developed using both mathematical models and numerical analysis to evaluate the demand for non-participating and participating life insurance policies in response to changes in interest rates. The findings indicate that non-participating life insurance policies offer greater solvency for insurance companies compared to participating policies. The study also highlights the significance of spontaneous and induced demand in determining the total profit of both types of policies. The study concludes that life insurance companies should focus on generating spontaneous consumer demand, reducing induced demand, and implementing the optimal pricing strategy to achieve maximum profits. Full article

Based on the cross-sectional data of the China household finance survey (CHFS) in 2017, this paper aims to empirically examine the effects of the family life cycle, financial status, and asset portfolio on commercial health insurance demand (breadth and depth) by constructing Probit and Tobit models, respectively. Based on all of the samples, it has been found that family life cycle, family financial status, and family asset portfolio have different influences on the breadth and the depth of health insurance. In terms of the family life cycle, there is an “inverted U-shaped” relationship with the breadth and the depth of health insurance, and the effect is obvious. In terms of family financial status, total household consumption has positive and significant effects on the breadth and depth of health insurance. Total household income and total household debt only have a significant positive impact on health insurance breadth. The total household asset portfolio is only positively correlated with health insurance depth. In terms of the family asset portfolio, the share of real estate assets has a crowding out effect on the breadth and the depth of health insurance. The share of savings assets has no significant effect on the breadth and the depth of health insurance but is positively correlated with the former and negatively correlated with the latter. Both the share of vehicle assets and the share of investment assets only have a significant impact on the breadth of health insurance; however, the positive and negative correlation is different. Based on the sub-samples, it has been found that the breadth and the depth of health insurance vary greatly in the regions and household registration characteristics. Full article

The rapid growth of the aging population and the rate of disabled people with physical and mental disorders is increasing the demand for long-term care. The decline in family care could lead to social and economic collapse. In order to reduce the burden of long-term care, long-term care insurance has become one of the most competitive products in the life insurance industry. In the previous literature review, few scholars engaged in the research on this topic with data mining technology, which was motivated to trigger the formation of this study and hoped to increase the different aspects of academic research. The purpose of this study is to develop the long-term insurance business from the original list of insurance clients, to predict whether the sustainable financial management clients will buy the long-term care insurance policies, and to establish a feasible prediction model to assist life insurance companies. This study aims to establish the classified prediction models of Models I~X, to dismantle the data with the percentage split and 10-fold cross validation, plus the application of two kinds of technology as feature selection and data discretization, for the data mining of twenty-three kinds of algorithms in seven different categories (Bayes, Function, Lazy, Meta, Misc, Rule, and Decision Tree) through the data collected from the insurance company database, and to select 20 conditional attributes and 1 decisional attribute (whether to buy the long-term insurance policy or not). The decision attribute is binary classification method for empirical data analysis. The empirical results show that: (1) the marital status, total number of policies purchased, and total amount of policies (including long-term care insurance) are found to be the three important factors affecting the decision attribute; (2) the most stable models are the advanced hybrid Models V and X; and (3) the best classifier is Decision Tree J48 algorithm for the study data used. Full article

Due to the low demand for conventional annuities, alternative retirement products are sought. Quite recently, tontines have been frequently brought up as a promising option in this respect. Inspired by unit-linked life insurance and retirement products, we introduce unit-linked tontines in this article, where the tontine payoffs are directly linked to the development of the underlying financial market. More specifically, we consider two different tontine payoff structures differing in the (non-)inclusion of guaranteed payments. We first price the unit-linked tontines by using the risk-neutral pricing approach. Consequently, we study the attractiveness of these products for a utility-maximizing policyholder and compare them with non-unit-linked tontines. Our numerical analysis sheds light on the design challenges and gives explanations why similar products might not be widely adopted already. Full article

The life insurance industry has experienced phenomenal growth over the years. The broad aim of this study was to establish the variables that influence the demand for life insurance in the BRICS countries (Brazil, Russia, India, China and South Africa). Although many studies have investigated the determinants of life insurance demand, little research has considered the supply-side factors such as financial regulation. Therefore, this study also contemplated the effect of the financial regulation variable on life insurance demand. The inquiry employed a panel of the BRICS bloc of countries as a unit of analysis for 1999–2020 and applied panel data econometric techniques. The study found that the life insurance demand variable (proxied by life insurance density and alternatively by life insurance penetration) was negatively affected by income, unemployment, interest rates and inflation variables. Furthermore, the study documented a positive relationship between life insurance demand and the economic growth and financial freedom variables. This study implies that regulatory authorities should deregulate the life insurance sector to foster financial freedom. Full article

Background: While Chinese cities are pursuing economic development, meeting citizen demand for medical treatment has only gradually been put on the agenda. Theoretically, in the second half of a person’s life, demand for medical treatment will rise sharply. Given limited medical resources, the match between demand and supply becomes more difficult. We conducted questionnaires in Shanghai to describe whether there are obvious group differences in the elderly population’s medical treatment options and provide empirical evidence on the determinants. Method: We collected 439 Shanghai Elderly Medical Demand Characteristics Questionnaires, which included five parts: personal information, health status, elderly person’s medical preference and expectation, satisfaction level for hospitals services, and medical insurance. We set up virtual explanatory variables according to the different medical behaviours of the elderly, and control variables composed of individual characteristics, socioeconomic characteristics, medical needs, medical resource availability, and medical expenditure. We used the MLR model to investigate medical treatment behaviour choice. Results: The medical treatment behaviour of the elderly population in Shanghai is affected by multiple factors. When experiencing physical discomfort, most of them choose to go to the hospital (64.69%). Age, income, household registration, and medical insurance reimbursement policy play a role in their decision-making. For general diseases, the proportion choosing specialist hospitals or community clinics is the highest (40.78%). Age, marital status, residential status, physical state, objective distance, medical expenses, and other factors have a significant impact. For severe diseases, they are more inclined (71.07%) to visit general hospitals, with the individual’s physical condition, living status, and accessibility to hospital resources more likely to affect their behaviour. Conclusion: Firstly, the importance of each factor varies depending on the conditions. Secondly, it may be more appropriate for China’s elderly health insurance system to set reimbursement rates based on the patient’s condition and disease type. Thirdly, medical behaviour has a distance friction effect, but the allocation of public service resources shows a strong centripetal concentration. It is necessary for the government to show due care about the regional distribution of the elderly population and to promote the rational distribution of medical resources in Shanghai. Full article

The rising aging population contributes to increased caregiver burden and a greater need for long-term care services, thereby posing stronger financial burden. The current study aimed to examine the effect of income, risk-taking propensity, personality traits, and life experience on the ownership of and intention to own private long-term care insurance (LTCI). Primary data were collected from 1373 registered nurses with a minimum of two years of full-time working experience. Multinomial logistic regression was used to examine the relationships between ownership of LTCI and personal discretionary income, risk propensity, openness to experience, and life experience. Personal discretionary income was a crucial positive indicator in predicting ownership of LTCI. Higher risk-taking propensity was found to be negatively related to both currently own and future intention to own private LTCI. Participants who currently live with elders and who agree to caregiving responsibilities with government-provided cash allowance showed future intention to purchase LTCI. Little evidence was found for an association between life experience and future intention to own LTCI. Income, risk-taking propensity, and personality traits differ in their impact on ownership of and future intention to own LTCI. Our results provide policy makers with a better understanding of the forces driving demand in the private LTCI market, as well as the accompanying implications for public LTCI. Full article