Demand For Non-life Insurance Research Articles

The Impact of Culture on the Demand for Non-life Insurance Penetration in Developing Countries: Panel Data Analysis

Purpose: The impact of insurance market activity within financial development is gaining more attention in academia, as the sector experiences growth within emerging markets. The paper aims to understand which macro-economic and social variables impact the growth or decline of the non-life insurance sector broadly across European countries with a view to provide recommendations to drive increased penetration across the region.
 Methodology: Using Fixed Effects Panel Data Regression and annual data from 1990 to 2021 on 10 countries, the study examines the explanatory factors of non-life insurance demand in European countries (Australia, France, Austria, Italy, Canada, Luxemburg, Denmark, Norway, Finland and Portugal).
 Findings: The study found that GDP, and urbanization and education rates have a significant negative impact on non-life insurance penetration and density; urbanization, religion, education level and rule of law can explain positively variation in non-life insurance density and penetration across countries. Countries with higher urbanization levels, higher education level, Christian or Buddhist beliefs and more effective rule of law spend more on non- life insurance than other countries. The control of corruption and government effectiveness explain negatively variance in non-life insurance.
 Unique Contribution to Theory, Practice and Policy: Notably, governments can develop the non-life insurance sector through policies that support urbanization.Similarly, ensuring an environment that promotes economic freedom (such as low tariff, high personal choice, low government spending and high security of property rights) could be an effective way of promoting non-life insurance demand. In contrast, policies that help to reduce the rate of urbanization may yield a double dividend: less population and congestion in cities and better opportunities for the development of non-life insurance markets. Also, countries with high level of education, can develop the development of non- life insurance demand. Among many socio-economic factors such as income, urbanization and education level, our analysis suggests that cultural dimensions such as beliefs and rule of law play a role.

The impact of economic policy uncertainty on insurance demand: the moderating effect of national culture

ABSTRACT We scrutinize the influence of economic policy uncertainty on the demand for insurance and delve into the moderating effect of national culture. Using an OLS model with two-way fixed effects, we find that heightened EPU engenders a decline in insurance demand, with discernible variances observed in the long-term and short-term effects on life and non-life insurance demand. Notably, uncertainty avoidance, power distance, and long-term orientation act as moderators, mitigating the adverse impact of EPU on insurance demand. Conversely, individualism exacerbates the negative consequences. Furthermore, our investigation uncovers that EPU primarily diminishes insurance demand by constraining residents’ income.

Demand for non-life insurance: A Sub-Saharan region panel data analysis

Demand for non-life insurance: A Sub-Saharan region panel data analysis

The threshold effect of climate risk and the non-linear role of climate policy uncertainty on insurance demand: Evidence from OECD countries

This paper investigates whether climate risk and climate policy uncertainty (CPU) have traditional linear or complicated non-linear impacts on insurance demand. We find evidence that both phenomena exist. Linear model shows positive effect of climate risk and negative effect of CPU on insurance demand. However, climate risk and CPU are interdependent, non-linear analysis demonstrates that CPU acts as a threshold. In particular, climate risk has a U-shaped relationship with life insurance demand and an inverse S-shaped relationship with non-life insurance demand, which provides insurance companies with a better understanding of how insurance demand fluctuates under climate risk.

FACTORS INFLUENCING NON-LIFE INSURANCE DEMAND: CASE OF LITHUANIA

This paper studies factors affecting non-life insurance demand in Lithuania. The study identified variables that are important in analyzing the demand for non-life insurance and were applied in estimating multivariate VAR, Classical Granger, and Toda-Yamamoto causalities. Lithuania’s case showed three significant causal relationships: positive - between non-life insurance demand and inflation and loss probability, negative - between density and short-term interest rate. Loss probability and short-term interest rate have been shown to be significant across all models. Inflation was deemed to be the effect of shift in demand rather than the cause.

Institutional determinants of insurance penetration in Africa.

This paper investigates the institutional determinants of insurance demand in Africa. We used a panel of 42 countries over the period 1996–2017. A system GMM approach was used for the estimations. Consistent with previous results, we find that institutional quality has positive and significant effects on insurance penetration in Africa. Specifically, regulatory quality, rule of law, control of corruption, political stability and absence of violence, and government effectiveness are the five institutional quality indicators that have positive and significant effects on the demand for total insurance and life insurance. However, only regulatory quality, control of corruption and government effectiveness are positively associated with non-life insurance demand. This indicates that governments should improve the business environment and strengthen the political environment to boost insurance development in Africa.Supplementary InformationThe online version contains supplementary material available at 10.1057/s41288-022-00278-2.

Demand for non-life insurance under habit formation

This paper studies the optimal non-life insurance for an individual exhibiting internal habit formation in a life-cycle model. We show that the optimal indemnity is deductible under the expected premium principle. Under the additional assumption of exponential utility functions, we obtain the optimal strategies explicitly and find that habit formation reduces insurance coverage. Our model offers a potential explanation for global underinsurance phenomenon. Some numerical examples and sensitivity analysis are presented to highlight our theoretical results.

Does financial literacy make the difference in non-life insurance demand among European countries?

While risk aversion and affordability of insurance are considered as the most important determinants of non-life insurance demand, understanding and knowledge of complex non-life insurance products are less researched. Studies on insurance demand conducted at the cross-section level, which include education, usually use it as a proxy for risk aversion and to a limited extent as a measure of financial literacy. Moreover, the general level of education does not accurately reflect the level of understanding of sophisticated insurance instruments. Consequently, the main aim of this research is to analyse the impact of financial literacy on the demand for non-life insurance by applying a more precise measure of financial literacy. The empirical analysis is based on the dataset of 38 European countries in the period from 2010 to 2016 and is done using the panel data analysis technique. Research findings confirm that financial literacy makes the difference in non-life insurance demand among European countries, while controlling for other economic, social/cultural, market structure and institutional determinants of non-life insurance demand. The paper contributes to the literature on non-life insurance demand, especially the one on the relationship between financial literacy and the demand for non-life insurance.

Factors affecting the demand for insurance in China

China, the largest developing country in the world, has achieved rapid development of insurance market since the reform and opening up, and the demand for insurance has significantly increased in recent years. Using the provincial data between 2000 and 2012, this article attempts to examine the factors that affect the demand for overall insurance, life insurance and nonlife insurance in China. Empirical results indicate that level of income, development of insurance market and level of marketization are the common factors; level of education, development of social security pension, children dependency ratio and elderly dependency ratio mainly affect the demand for life insurance; and inflation mainly affects the demand for nonlife insurance. Furthermore, we particularly investigate the regional differences in the effects of affecting factors between Eastern China, Central China and Western China.

Life and non-life insurance demand: the different effects of influence factors in emerging countries from Europe and Asia

Urbanisation, incomes and their distributions, and the population degree of education are relevant factors for the development of insurance sector. This study estimates the different effects of the previously mentioned factors for life and non-life sector. We used the econometrics of panel data on 17 emerging economies from Asia and Europe over a 10-year period. We showed that urbanisation influenced significantly the life insurance demand in Asia, but not in Europe. Also, education was found to be significant only for the non-life sector in both regions and income was non-significant in Asia for non-life sector.

A preliminary assessment of the impact of climate change on non-life insurance demand in the BRICS economies

Over the past decade, the increase in insurance demand in the BRICS has been a key driver of global non-life premium growth. Current forecasts suggest that these markets will continue to be areas of significant expansion. For example, based on a simple model, we project that gross premium volumes in the BRICS economies could increase at a rate of between 5.4 and 12.3% per year over the coming decade, depending on the country. We consider how climate change may influence these trends in the period to 2030. We argue that the influence of climate change will be more multifaceted, complex and regionally variable than portrayed in the past. We suggest five pathways of influence: wealth; willingness to pay for insurance; policy and regulation; changes to the supply of insurance; and new opportunities associated with adaptation and mitigation. We conclude that, with the exception of policy and regulation, the influence of climate change on insurance demand to 2030 is likely to be small when compared with the expected growth due to rising incomes, but is not insignificant. For example, we expect the impact on premium volumes mediated through wealth to be small; less than a 0.4% adjustment in the annual growth rate to 2030. But, we also conclude that the scale of the risks and opportunities will depend partly on (re)insurer responses to the challenges of climate change. We outline five actions that could pave the way for future opportunities.

Does Social Capital Reduce Moral Hazard? A Network Model for Non-Life Insurance Demand

We study is the effect of moral hazard involved in non market contracts on the demand for marketed contracts. We extend Arnott and Stiglitz model on the coexistence of market and non-market insurance contracts to allow for the presence of Social Capital as a determinant of the severity of moral hazard in informal contracts. We provide a rigorous definition of Social Network and Social Capital by means of an equilibrium concept typical of the Network literature. Such a formal approach gives us a clear guidance for measuring Social Capital and validate the model on empirical data. The model is estimated on a panel dataset, supporting our claim that Social Capital increases the demand for non-life insurance. We test for the presence of spatial correlation, and conclude that the spatial structure of demand for non-life insurance contracts is completely determined by the spatial distribution of Social Capital.

Insurance, Consumption, and Saving: A Dynamic Analysis in Continuous Time

This paper shows how the demand for non-life insurance interacts with consumption and saving. The analysis is set in continuous time, using the maximum principle. When insurance is actuarially fair, the insurance and consumption decisions are separable. With loaded premiums, and alternatively without insurance, optimal consumption is dynamically related to the growth rate of the loss probability, and a growing loss probability generates precautionary saving. With loaded premiums, less than full insurance is demanded at each instant, and optimal cover varies over time, whether or not the loss probability is constant.

Property insurance, quality and reservation premium: A note

The aim of this note is to investigate the effects of the introduction of a ‘quality’ variable in a model of non-life insurance demand. The framework, based on the model of Mossin (1968) with deductible, analyses the variations of the reservation premium when the quality is of the additive or the multiplicative type and the deductible is absolute or proportional.

The Demand for Non-Life Insurance: A Consumption-Oriented Model

The Demand for Non-Life Insurance: A Consumption-Oriented Model