性别包容的金融和人口扫盲:将性别死亡率差距货币化

IF 1.3 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Applied Stochastic Models in Business and Industry Pub Date : 2024-06-10 DOI:10.1002/asmb.2876
Giovanna Apicella, Enrico De Giorgi, Emilia Di Lorenzo, Marilena Sibillo
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引用次数: 0

摘要

长寿对养老金、保险产品和年金的需求有着至关重要的影响。一致的经验证据表明,女性的死亡率历来低于男性。在本文中,我们研究了死亡率性别差异的衡量标准,我们称之为 "性别差异比",涉及四个国家的多个年龄段:法国、意大利、瑞典和美国。我们从性别差距比的历史演变和未来预测两方面展示了其趋势的典型事实。我们以临时年金合同为例,给出了性别差距比的货币一致性。我们展示的证据表明,性别差距比介于 1.5 和 2.5 之间(取决于年龄),意味着女性从临时人寿年金合同中获得的收益比男性大幅减少 23%,而投资于人寿年金的金额相同。本文讨论的经验证据表明,在性别平等政策框架内,努力普及人口知识至关重要,例如,通过一系列工具和战略来提高个人和政策制定者的长寿意识。
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Gender-inclusive financial and demographic literacy: Monetizing the gender mortality gap

Longevity crucially affects demand for pensions, insurance products and annuities. Consistent empirical evidence shows that women have historically experienced lower mortality rates than men. In this article, we study a measure of the gender gap in mortality rates, we call “Gender Gap Ratio”, across a wide range of ages and for four countries: France, Italy, Sweden, and USA. We show the stylized facts that characterize the trend of the Gender Gap Ratio, both in its historical evolution and future projection. Focusing on an example temporary life annuity contract, we give a monetary consistency to the Gender Gap Ratio. We show evidence that a Gender Gap Ratio that ranges between 1.5 and 2.5, depending on age, translates into a significant reduction of up to 23% in the benefits from a temporary life annuity contract for women with respect to men, against the same amount invested in the life annuity. The empirical evidence discussed in this article documents the crucial importance of working toward a more widespread demographic literacy, for example, a range of tools and strategies to raise longevity consciousness among individuals and policy-makers, in the framework of gender equality policies.

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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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