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Childhood unexpected trauma casts a lifelong shadow on subsequent financial behaviours. The existing literature has mainly investigated stock or bond market participation, and few scholars focus on insurance decisions. Our paper enriches previous studies by testing the impact of childhood famine exposure on household life insurance demand in middle and older age groups. Using CHARLS, we discover that householders exposed to the 1959–1961 Great Chinese Famine as children were more inclined to own life insurance policies and pay higher premiums. Specifically, respondents who experienced the famine between 0–2 or 7–17 years old highly promoted their life insurance demand, whereas no statistically significant effects were observed for preschool famine experience. Additionally, women and people with three or more children were more likely to be influenced by the famine. Finally, risk and time preference were effective mediation factors, both channelling around 5% of the relationship. [ABSTRACT FROM AUTHOR]

Life insurance enhances households' capacity to absorb financial shocks and protects against personal risks that no one likes to contemplate. This is even more important in times of economic hardship such as now, when many Europe countries and particularly Spain are going through difficult times due to rising inflation, the war in Ukraine, and the ongoing COVID‐19 pandemic. Although previous studies have analysed the driving forces of life insurance demand, the influence of the individual's financial planning horizon, financial knowledge, and financial self‐control have been underexplored. This study analyses the influence of personal financial attributes on life insurance demand and, in so doing, explores whether the effects of such attitudes differ across different generational cohorts (i.e., the silent generation, baby boomers, Gen Xers, and millennials). The data, taken from the Survey of Financial Competences, comprises 7245 Spanish individuals. Evidence from multivariate analyses reflects the relevance of standard sociodemographic characteristics in explaining individuals' decisions to become life insurance holders. In contrast, evidence does not support a statistically significant relationship in the case of behavioural variables such as financial self‐control and the financial planning horizon. [ABSTRACT FROM AUTHOR]

We examined changes in personal life insurance purchase decisions after a public health event by incorporating perceived health risk and regret into the expected utility function. The model predicts that the epidemic will create incremental insurance demand. Based on the 2003 severe acute respiratory syndrome outbreak in China, we used a panel dataset of 30 provinces from 2000 to 2007 and applied the difference‐in‐differences method to confirm the prediction empirically. The results showed that the epidemic did not significantly impact the demand for life insurance in the short term but played a role in the long term. People increased their health‐care expenditure and premiums for new policies after the severe acute respiratory syndrome event, suggesting that the epidemic changed people's perceived risk and triggered anticipated regret, which increased life insurance demand. Some robustness checks also supported our findings. [ABSTRACT FROM AUTHOR]

Expanding life insurance prevents class gaps and poverty. The expansion of life insurance is closely related to the level of economic and social well-being in each country. For the purpose, in this study, the combined method of data panel was used. The method of estimating the model is based on a combination of time series data (from 1397 to 1393) and cross-sectional data of all provinces of Iran. Since our focus is on finding the relationship between welfare variables and insurance demand, educational welfare variables have been used to measure educational welfare and the per capita income variable as a physical welfare variable and the income inequality variable as a social welfare variable. Findings showed that the coefficients of variables of physical level and educational level of welfare were both positive and significant, but the coefficients of social level of welfare were negative and non-significant. There is also a significant and negative relationship between insurance rates and demand for life insurance. Management and policy recommendations of this research emphasize on controlling interest and insurance rates due to their effective relationship with life insurance demand. Since the results of the research confirm the existence of an effective relationship between interest and insurance rates with the life insurance demand, so controlling these rates while maintaining their favorable effects can lead to supporting life insurance and thus increase social welfare in society. The government can also increase the level of education and training of people in the community by supporting the public and university education sectors. This measure, according to the results of the research will increase the life insurance demand and increase social welfare. Therefore, paying attention to education and policies to control interest and life insurance rates can lead to an overall improvement in the welfare of society.

Life insurance in the Western Balkan Countries is underdeveloped, but it has huge potential for development in the future. The scope of this article is to examine whether and how economic, socio- demographic, and institutional factors determine the demand for life insurance in the Western Balkans, using life insurance density and life insurance penetration as indicators of life insurance demand during 2006-2019. In order to conduct a crosscountry analysis we use panel data regression models and a feasible generalised least squares regression model. The analysis reveals that the most significant factors are income per capita and changes in the urban population. The article contributes to the existing literature by identifying the variables that affect demand for life insurance in the Western Balkans and by providing evidence for insurance operators, authorities, and governments of the respective countries to find ways to further develop the insurance market.

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. [ABSTRACT FROM AUTHOR]

This paper aims to find the relationship between key determinants such as income, education, life expectancy, employment and life insurance demand in the countries of the Visegrad Group (V4). This article makes use of OECD data and applies linear and panel data regressions. We find that with increasing income and higher educational attainment, people demonstrate more demand for investment in pension funds but less for life insurance. Furthermore, unemployment appears to have a strongly negative effect in all presented models, and with higher life expectancy, people demand more life insurance products and less pension fund assets. [ABSTRACT FROM AUTHOR]

This paper presents a framework‐based systematic review of existing research to understand the purchase behaviour of consumers for life insurance products. The TCM framework is adopted to provide an organized review of the theory, context and methods used in the articles under review. Antecedents, decisions and outcomes in the context of consumers' life insurance purchase behaviour are also discussed in detail using the ADO framework. The review aggregates 136 unique antecedents derived from 76 relevant articles and classifies them into eight broad categories. Further, the reasons for obtaining a positive or negative effect of a particular antecedent on life insurance purchase decisions or outcomes are also fully explored. Finally, TCM and ADO frameworks are used to identify the research gaps in the extant life insurance literature. Some of the important future avenues of the research, especially from the perspective of behavioural economics and pandemic scenarios such as COVID‐19, are then explored. [ABSTRACT FROM AUTHOR]

Life insurance protects individuals against their own risks and helps to increase their savings. Life insurance as a component of insurance business have part in maintaining economic growth of a country. Despite the fact that life insurance has importance for countries and individuals, it is known that developing countries show low life insurance consumption. Detecting life insurance determinants is important for explaining development of life insurance industry. The aim of the study is to detect economic, financial and demographic determinants of life insurance demand in Turkey. The literature includes Turkey in panel data or cross section samples with different countries. However, research which focus on Turkey in particular has beenshown limited attention. In this context, time series analysis was carried out on quarterly data between 2009-2019 periods. Determinants of the study are income, real interest rate, inflation, financial deepening, complexity of financial structure and population dependency ratio. As a result of model estimation, all variables were found to have significant effect. The income variable as an economic variable had positive effect. As expected, economic variables which are inflation and real interest rates negatively affects life insurance demand. It has been determined that financial deepening has a positive effect. The complexity of the financial structure factor was negative. Finally, the population dependency ratio, which is considered as a demographic variable, was not statistically significant. [ABSTRACT FROM AUTHOR]

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.

The present questionnaire-based study combines and expands technology acceptance and behavioural (risk and loss aversion) variables in explaining the demand for life insurance products. Loss aversion is inversely related to the proxy for life insurance demand and two technology acceptance related factors (usefulness of online technology and acceptance of smart devices) have a significant positive influence. [ABSTRACT FROM AUTHOR]

The article analyzes the interconnectedness and gaps between two interrelated streams of literature, evolving in different time periods, by employing bibliometric tools. The research on the factors of life insurance demand started in the late 1960s and early 1970s, while more intensive works on the drivers of lapses in life insurance appeared during the 2000s. We map the research fields using our own criteria to create clusters and visualize the flow of knowledge within and between the clusters employing citation network analysis (CNA). We contribute by providing the most comprehensive systematic review that integrates both fields, additionally encapsulating studies on the demand for policy loans. The article detects the most important drivers of life insurance policyholder behavior during his/her lifetime and opens new horizons for future research. [ABSTRACT FROM AUTHOR]

Copyright of Research Papers of the Wroclaw University of Economics / Prace Naukowe Uniwersytetu Ekonomicznego we Wroclawiu is the property of Uniwersytet Ekonomiczny we Wroclawiu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this paper is to summarize a large number of economic and demographic determinants that are used to predict the demand for life insurance into a smaller number of component variables (components) and to determine which component has a stronger influence on demand for life insurance. Data are collected for 150 countries during the period 2005-2010. Final cross-country database is consisted of six-year average values on variables for selected countries. The methodology includes techniques of multivariate analysis: principal component analysis (PCA) and multiple linear regression. Results show that initial determinants of demand for life insurance can be summarized into two components: economic and demographic. Both components have a statistically significant positive influence on the demand for life insurance. On the basis of standardized regression coefficients it can be concluded that economic component is stronger determinant of demand for life insurance in comparison with demographic. [ABSTRACT FROM AUTHOR]

We investigate the influence of institutional factors upon life insurance demand for 32 European countries, considering the socio-demographic and economic determinants as control variables. Using a panel data approach, we find that life insurance demand is influenced differently by institutional indicators from the Worldwide Governance Indicators database, in emerging and transition markets compared to developed ones. The sound legal environment of developed countries, where the level of the rule of law is very homogeneous and very high, makes it non-significant for life insurance demand. For developing countries the enforceability of contracts, the independence of justice and the time efficiency of the judicial process positively influence the decision of citizens to buy life insurance contracts. The effect of income distribution over life insurance density varies across these two categories of countries. For transition and emerging markets we find a positive relationship between life insurance density, income distribution and level of urbanisation. In developed countries, because of the high levels of income, life insurance became a common good, not a luxury one, which makes income distribution an insignificant factor. For emerging and transition countries policymakers should concentrate more on strengthening trust in the insurance sector for reducing the gap with developed countries. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)