Nathaniel Grimes, Christopher Costello, Andrew J. Plantinga
Fisheries are vulnerable to environmental shocks that impact stock health and fisher income. Index insurance is a promising financial tool to protect fishers from environmental risk. However, insurance may change fisher's behavior. It is imperative to understand the direction fishers change their behavior before implementing new policies as fisheries are vulnerable to overfishing. We provide the first theoretical application of index insurance on fisher's behavior change to predict if index insurance will incentivize higher or lower harvests in unregulated settings. We find that using traditional fishery models with production variability only originating through stock abundance leads fishers to increase harvest with index insurance. However, fishers are adaptable and experience multiple sources of risk. Using a more flexible specification of production shows that index insurance could raise or lower harvest depending on the risk mitigation strategies available for fishers and the design of the insurance contract. We demonstrate the magnitude of potential change by simulating from parameters estimated for three Norwegian fisheries. Fisheries with index insurance contracts protecting extraction risks may increase harvest by 10% or decrease by 2% depending on the risk effects of inputs. Insurance contracts protecting stock risk will lead to 6-20% increases in harvest. Before widespread adoption, careful consideration must be given to how index insurance will incentivize or disincentivize overfishing.
Economic policy uncertainty has been increasing globally, with consequences for financial sector stability. This paper investigates its influence on the risk-taking behavior of banks. The study examines the functional form of responses of banks to economic policy uncertainty and explores how regulatory quality and safety nets change bank behavior in periods of high uncertainty.
We utilize data from 1999 to 2023 of 796 banks in 21 countries, employing a quadratic two-step system GMM estimation technique to evaluate the impact of economic policy uncertainty on banks' risk-taking. Using the U-test, we confirm the nonlinear relationship and identify its threshold point. Finally, we show the consistency of the estimates by controlling for multiple major crisis periods during the sample period.
We find that economic policy uncertainty generally increases risk-taking among banks. However, beyond a certain point, further increases in economic policy uncertainty could lead to diminishing returns and heightened risk aversion, resulting in decreased risk-taking behavior. Stronger regulatory quality mitigates this effect; however, the reduction in risk-taking is less pronounced when economic policy uncertainty increases. Safetynets moderate the relationship by impacting bank risk-taking sensitivity. Additionally, we find cross-country heterogeneity in the size of economic policy uncertainty and risk-taking. Lastly, we find that the nonlinear effects are robust after controlling for major events like the global financial crisis, the eurozone crisis, COVID-19, and the Ukraine war.
We provide evidence of nonlinearity in the nexus of economic policy uncertainty, regulatory frameworks, safety nets, and bank risk-taking behavior. The findings underscore the significance of robust regulatory quality and safety nets in moderating banks' risk-taking behavior during economic policy uncertainty.
Pierre-Olivier Goffard, Pierrick Piette, Gareth W. Peters
This paper introduces a method for pricing insurance policies using market data. The approach is designed for scenarios in which the insurance company seeks to enter a new market, in our case: pet insurance, lacking historical data. The methodology involves an iterative two-step process. First, a suitable parameter is proposed to characterize the underlying risk. Second, the resulting pure premium is linked to the observed commercial premium using an isotonic regression model. To validate the method, comprehensive testing is conducted on synthetic data, followed by its application to a dataset of actual pet insurance rates. To facilitate practical implementation, we have developed an R package called IsoPriceR. By addressing the challenge of pricing insurance policies in the absence of historical data, this method helps enhance pricing strategies in emerging markets.
Risk aversion and insurance are two prominent and interconnected concepts in economics and finance. To explore their fundamental connection, we introduce risk-insurance parity, which associates various classes of insurance contracts with different notions of risk aversion. We show that the classic notions -- both weak and strong -- of risk aversion can be characterized by propensity to different classes of insurance contracts, generalizing recent results on propensity to full, proportional, and deductible-limit contracts in the literature. We obtain full characterizations of the classes of insurance indemnity functions that correspond to weak and strong risk aversion. Risk-insurance parity allows us to define two new notions of risk aversion, between weak and strong, characterized by insurance propensity to deductible-only and limit-only contracts respectively.
This paper analyzes optimal insurance design when the insurer internalizes the effect of coverage on third-party service prices. A monopolistic insurer contracts with risk-averse agents who have sequential two-dimensional private information and preferences represented by Yaari's dual utility. Insurance contracts shape service demand and, through a market-clearing condition, determine equilibrium third-party prices. We characterize the structure of optimal contracts and show they take simple forms: either full coverage after a deductible is paid or limited coverage with an out-of-pocket maximum, closely mirroring real-world insurance plans. Technically, we formulate the problem as a sequential screening model and solve it using tools from optimal transport theory.
Index insurance is often proposed to reduce protection gaps, especially for emerging risks. Unlike traditional insurance, it bases compensation on a measurable index, enabling faster payouts and lower claim management costs. This approach benefits both policyholders, through quick payments, and insurers, through reduced costs and better risk control due to reliable data and robust statistical estimates. An important difference with the concept of Cat Bonds is that the feasibility of such coverage relies on the possibility of mutualization. Mutualization, in turn, is achieved only if a sufficiently high number of policyholders agree to subscribe. The purpose of this paper is to introduce a model for the demand for index insurance and to provide conditions under which the solvency of the portfolio is achieved. From these conditions, we deduce a product that combines index and traditional indemnity insurance in order to benefit from the best of both approaches. We illustrate our results with a practical example involving the design of an index insurance product in the field of cyber insurance.
Abstract Background Ecological momentary assessment (EMA) has seen increasing application in mental health research. However, there is a challenge in applying EMA to assess daily suicide risk in community settings due to poor adherence to the complex protocol and high dropout rates. The aim of this study is to assess the feasibility and adherence to the EMA when monitoring the daily risk of suicide in community-dwelling adults with suicidal ideation. Methods This secondary analysis was based on primary data from an observational study. The study participants with suicidal ideation responded to a 28-day EMA online survey and pressed an event marker on an actigraphic device when feeling strong suicidal impulses. Feasibility was evaluated using the EMA response rate and actigraphic device adherence rate based on descriptive statistics. Mental health characteristics related to feasibility were assessed in self-reporting questionnaires, and nonparametric correlation coefficients were identified to assess the relevance to feasibility. Results A total of 22 participants were enrolled, with 20 remaining in the final sample (90.9%). The average EMA response rate was 82.05%, decreasing from 86.96% during the first 2 weeks to 76.31% in the second 2 weeks. The Actiwatch adherence rate was maintained at 98.1%. Actiwatch adherence and EMA response rates were moderately correlated (r =.53, p =.016). Higher depression and anxiety scores were associated with lower Actiwatch adherence, whereas a higher perceived stress score was associated with lower EMA response rates. The peak of suicidal impulse patterns in event button activations usually occurred between 9 to 10 pm, while activations were lowest in the early morning hours, particularly between 4 and 6 am. Discussion This study indicated that EMA using smartphones and actigraphic devices were feasible to monitor suicidal ideation and impulse for a month in community-dwelling adults; thus, it could be a complementary tool to assess daily suicide risk. However, there are still challenges to be overcome when EMA-based monitoring in the community is used for those with mental vulnerability. Thus, mental health professionals should carefully tailor the pros and cons of EMA based on our findings to enhance this vulnerable group’s participation and adherence to EMA for suicide prevention.
In recent years, quantum computation has been rapidly advancing, driving a technological revolution with significant potential across various sectors, particularly in finance. Despite this, the insurance industry, an essential tool for mitigating unforeseen risks and losses, has received limited attention. This paper provides an initial exploration into the realm of quantum computational insurance and actuarial science. After introducing key insurance models and challenges, we discuss quantum algorithms that can address insurance problems based on their mathematical nature. Our study includes experimental and numerical demonstrations of quantum applications in non-life insurance, life insurance, and reinsurance. Additionally, we explore the timeline for quantum insurance, the development of quantum-enhanced insurance products, and the challenges posed by quantum computational advancements. This work systematically constructs the connection between quantum computation and the insurance industry, enhancing the development of insurance while promoting the application of quantum computation to more realistic problems.
Does public insurance reduce uninsured long-term care (LTC) risks in developing countries, where informal insurance predominates? This paper exploits the rollout of LTC insurance in China around 2016 to examine the impact of public LTC insurance on healthy workers' labor supply, a critical self-insurance channel. We find that workers eligible for public LTC insurance were less likely to engage in labor work and worked fewer weeks annually following the policy change, suggesting a mitigation of uninsured risks. However, these impacts were insignificant among those with strong informal insurance coverage. Parallel changes in anticipated formal care use corroborate these findings. While our results reveal that public LTC insurance provides limited additional risk-sharing when informal insurance predominates, they also underscore its growing importance.
Our homes are increasingly employing various kinds of Internet of Things (IoT) devices, leading to the notion of smart homes. While this trend brings convenience to our daily life, it also introduces cyber risks. To mitigate such risks, the demand for smart home cyber insurance has been growing rapidly. However, there are no studies on analyzing the competency of smart home cyber insurance policies offered by cyber insurance vendors (i.e., insurers), where `competency' means the insurer is profitable and smart home owners are not overly charged with premiums and/or deductibles. In this paper, we propose a novel framework for pricing smart home cyber insurance, which can be adopted by insurers in practice. Our case studies show, among other things, that insurers are over charging smart home owners in terms of premiums and deductibles.
An insurance company, as a risk bearer, is exposed to the likelihood of running into ruin. This is the situation where the initial surplus falls below zero. There is the need to find the required start-up capital to hedge against insolvency. Most researchers, irrespective of whether the test for claim dependency holds or not, assume claim independence in their computing of ruin probabilities to start up their initial capital. The objective of this study is to carry out comparative sensitivity analysis of ruin probability under both assumptions of dependence and independence, irrespective of whether the data exhibits independence or not, based on data from an insurance company in Ghana. Secondary data from an insurance company was obtained from the National Insurance Commission (NIC) for the period of 2013 to 2017. The study employed copulas to determine the claim dependence among the various insurance products and the company in general. The study concluded that when there is dependence in the claim data, computing the ruin probability based on the assumption of independence results in underestimation. Among the various insurance products, the most profitable insurance product was motor insurance, and Fire and Allied insurance exhibited the highest dependency. At a higher start-up capital, when claims are dependent, assuming independence in calculating the ruin probability results in a significant difference. Hence, it was recommended that insurance companies should adopt the assumption of dependence between the claims data as the initial reserves become larger, particularly for larger insurance companies, to avoid misleading results. Also, awareness of the perils and consequences of fire outbreaks and disasters should be raised to the general public to reduce the risk of frequent occurrence.
In economic analysis, rational decision-makers often take actions to reduce their risk exposure. These actions include purchasing market insurance and implementing prevention measures to modify the shape of the loss distribution. Under the assumption that the insureds' actions are fully observed by the insurer, this paper investigates the interaction between self-protection and insurance demand when insurance premiums are determined by convex premium principles within the framework of distortion risk measures. Specifically, the insured selects an optimal proportional insurance share and prevention effort to minimize the risk measure of their end-of-period exposure. We explicitly characterize the optimal combination of prevention effort and insurance demand in a self-protection model when the insured adopts tail value-at-risk or a subclass with strictly concave distortion functions. Additionally, we conduct comparative static analyses to illustrate our main findings under various premium structures, risk aversion levels, and loss distributions. Our results indicate that market insurance and self-protection are complementary, supporting classical insights from the literature regarding corner insurance policies (i.e., null and full insurance) in the absence of ex ante moral hazard. Finally, we consider the effects of moral hazard on the interaction between self-protection and insurance demand. Our findings show that ex ante moral hazard shifts the complementary effect into substitution effect.
Abstract Head trauma is a common reason for emergency department (ED) visits. Delayed intracranial hemorrhage (ICH) in patients with minor head trauma is a major concern, but controversies exist regarding the incidence of delayed ICH and discharge planning at the ED. This study aimed to determine the incidence of delayed ICH in adults who developed ICH after a negative initial brain computed tomography (CT) at the ED and investigate the clinical outcomes for delayed ICH. This nationwide population cohort study used data from the National Health Insurance Service of Korea from 2013 to 2019. Adult patients who presented to an ED due to trauma and were discharged after a negative brain CT examination were selected. The main outcomes were the incidence of ICH within 14 days after a negative brain CT at initial ED visit and the clinical outcomes of patients with and without delayed ICH. The study patients were followed up to 1 year after the initial ED discharge. Cox proportional hazard regression analysis was used to estimate the hazard ratio for all-cause 1-year mortality of delayed ICH. During the 7-year study period, we identified 626,695 adult patients aged 20 years or older who underwent brain CT at the ED due to minor head trauma, and 2666 (0.4%) were diagnosed with delayed ICH within 14 days after the first visit. Approximately two-thirds of patients (64.3%) were diagnosed with delayed ICH within 3 days, and 84.5% were diagnosed within 7 days. Among the patients with delayed ICH, 71 (2.7%) underwent neurosurgical intervention. After adjustment for age, sex, Charlson Comorbidity Index, and insurance type, delayed ICH (adjusted hazard ratio, 2.15; 95% confidence interval, 1.86–2.48; p < 0.001) was significantly associated with 1-year mortality. The incidence of delayed ICH was 0.4% in the general population, with the majority diagnosed within 7 days. These findings suggest that patient discharge education for close observation for a week may be a feasible strategy for the general population.
This study investigates how decentralization and transparency offered by blockchain technology could revolutionize traditional finance. Even with the rise of well-known cryptocurrencies such as Bitcoin and Ethereum, a general understanding of blockchain’s influence on the financial industry is still lacking. We identified five major application cases—transparent credit scoring, effective consumer identification, expedited insurance settlements, improved cybersecurity, and the emergence of decentralized finance—where blockchain technology is well positioned to tackle persistent issues. We show how blockchain technology may address problems such as opaque credit scoring, poor customer identity, convoluted insurance settlement procedures, and susceptibility to cyberattacks by thoroughly examining various use cases. According to our research, a greater number of traditional financial institutions need to embrace and integrate blockchain innovations into their functions to promote inclusivity, transparency, and decentralization.
Mai T. H. Nguyen, Yuki Sakamoto, Toshiki Maeda
et al.
Background This review aimed to quantify the impact of socioeconomic status on functional outcomes from stroke and identify the socioeconomic status indicators that exhibit the highest magnitude of association. Methods and Results We performed a systematic literature search across Medline and Embase from inception to May 2022, to identify observational studies (n≥100, and in English). Risk of bias was assessed using the modified Newcastle Ottawa Scale. Random effects meta‐analysis was used to pool data. We included 19 studies (157 715 patients, 47.7% women) reporting functional outcomes measured with modified Rankin Scale or Barthel index, with 10 assessed as low risk of bias. Measures of socioeconomic status reported were education (11 studies), income (8), occupation (4), health insurance status (3), and neighborhood socioeconomic deprivation (3). Pooled data suggested that low socioeconomic status was significantly associated with poor functional outcomes, including incomplete education or below high school level versus high school attainment and above (odds ratio [OR], 1.66 [95% CI, 1.40–1.95]), lowest income versus highest income (OR, 1.36 [95% CI, 1.02–1.83]), a manual job/being unemployed versus a nonmanual job/working (OR, 1.62 [95% CI, 1.29–2.02]), and living in the most disadvantaged socioeconomic neighborhood versus the least disadvantaged (OR, 1.55 [95% CI, 1.25–1.92]). Low health insurance status was also associated with an increased risk of poor functional outcomes (OR, 1.32 [95% CI, 0.95–1.84]), although this was association was not statistically significant. Conclusions Despite great strides in stroke treatment in the past decades, social disadvantage remains a risk factor for poor functional outcome after an acute stroke. Further research is needed to better understand causal mechanisms and disparities.
Diseases of the circulatory (Cardiovascular) system
Cyber insurance is a complementary mechanism to further reduce the financial impact on the systems after their effort in defending against cyber attacks and implementing resilience mechanism to maintain the system-level operator even though the attacker is already in the system. This chapter presents a review of the quantitative cyber insurance design framework that takes into account the incentives as well as the perceptual aspects of multiple parties. The design framework builds on the correlation between state-of-the-art attacker vectors and defense mechanisms. In particular, we propose the notion of residual risks to characterize the goal of cyber insurance design. By elaborating the insurer's observations necessary for the modeling of the cyber insurance contract, we make comparison between the design strategies of the insurer under scenarios with different monitoring rules. These distinct but practical scenarios give rise to the concept of the intensity of the moral hazard issue. Using the modern techniques in quantifying the risk preferences of individuals, we link the economic impacts of perception manipulation with moral hazard. With the joint design of cyber insurance design and risk perceptions, cyber resilience can be enhanced under mild assumptions on the monitoring of insurees' actions. Finally, we discuss possible extensions on the cyber insurance design framework to more sophisticated settings and the regulations to strengthen the cyber insurance markets.
Fabio Maccheroni, Massimo Marinacci, Ruodu Wang
et al.
We provide a new foundation of risk aversion by showing that this attitude is fully captured by the propensity to seize insurance opportunities. Our foundation, which applies to all probabilistically sophisticated preferences, well accords with the commonly held prudential interpretation of risk aversion that dates back to the seminal works of Arrow (1963) and Pratt (1964). In our main results, we first characterize the Arrow-Pratt risk aversion in terms of propensity to full insurance and the stronger notion of risk aversion of Rothschild and Stiglitz (1970) in terms of propensity to partial insurance. We then extend the analysis to comparative risk aversion by showing that the notion of Yaari (1969) corresponds to comparative propensity to full insurance, while the stronger notion of Ross (1981) corresponds to comparative propensity to partial insurance.
Tajkia Nuri Ananna, Munshi Saifuzzaman, Mohammad Jabed Morshed Chowdhury
et al.
Health insurance plays a significant role in ensuring quality healthcare. In response to the escalating costs of the medical industry, the demand for health insurance is soaring. Additionally, those with health insurance are more likely to receive preventative care than those without health insurance. However, from granting health insurance to delivering services to insured individuals, the health insurance industry faces numerous obstacles. Fraudulent actions, false claims, a lack of transparency and data privacy, reliance on human effort and dishonesty from consumers, healthcare professionals, or even the insurer party itself, are the most common and important hurdles towards success. Given these constraints, this chapter briefly covers the most immediate concerns in the health insurance industry and provides insight into how blockchain technology integration can contribute to resolving these issues. This chapter finishes by highlighting existing limitations as well as potential future directions.
By improving its total factor productivity, China may attain higher quality and more sustainable economic growth. As a key market-based incentive for environmental regulation, does environmental protection tax increase total factor productivity and provide a win-win situation for both economic and environmental performance? It is a debate-worthy topic. Based on data of Chinese listed companies, this paper uses the triple difference method to analyze China’s environmental protection tax reform as a natural experiment. The results show that the environmental protection tax can significantly boost the firm’s total factor productivity by encouraging technological innovation and enhancing resource allocation. Based on analysis of heterogeneity, it appears that state-owned enterprises, larger corporations, and regions with more strict environmental enforcement are more responsive to environmental protection tax policies. This report provides critical empirical evidence for upgrading China’s tax framework to protect the environment.