Search results

The study measured quality financial inclusion, a more comprehensive measure of financial inclusion, and examined its determinants at a consumer level in South Africa.

This study leveraged on FinScope 2015 survey data to compute a quality financial inclusion index using polychoric principal component analysis. Subsequently, a heteroscedasticity consistent ordinary least squares regression model was employed to assess determinants of quality financial inclusion.

The empirical findings indicated that gender, education, financial literacy, income, location and geographical proximity determine quality financial inclusion. These findings could inform policymakers and financial services providers on how quality financial inclusion can be promoted through tailoring financial products for various socio-demographic groups.

Due to data limitations, the study was confined to South Africa and did not capture digital financial inclusion. Hence, future studies could replicate the study in Sub-Saharan Africa's context and compute an index that captures digital financial inclusion.

These findings could inform policymakers and financial services providers on how quality financial inclusion can be promoted through tailoring financial products for various socio-demographic groups.

This study proposed a more comprehensive measure of quality financial inclusion from a demand-side perspective by accounting for important dimensions that include diversity, affordability, appropriateness and flexibility of financial products and services.

The effectiveness of hedging drought risks with weather derivatives was investigated for rain‐fed grain maize production in Switzerland under current (1981‐2003) and projected future (2070‐2100) climatic conditions. Depending on location, hedging reduced the value‐at‐ (VaR) measure to a variable degree, although with a considerable basis risk, but hedging may provide a valid risk transfer since loading of 90 per cent to 240 per cent of the fair premium can be paid to obtain a hedged situation with improved outcomes relative to the reference. However, the fair premium of a specific contract may vary by a factor of two to four over the 70‐year period considered, which represents a substantial uncertainty for both the farmer and the institution writing the contract.

This paper explored factors that impact insurance choices of demand (farmers) and supply (insurance companies) side, respectively.

Specially designed survey questions allow one to fully observe the demand tendency from farmers and partially observe the supply tendency from insurance companies. Using bi‐vairate probit model, a joint estimation of insurance decisions of both supply and demand sides suggested that factors perform different roles in affecting insurance participation.

Farmer's age and education have positive impacts on insurance demand, but are indifference to insurance providers. Insurance suppliers care about farmers' experience in the fields when providing insurance services, however, on the demand side, farmers' experience occasionally results in overconfidence and hence, impedes farmers' insurance purchasing. Production scales, proxy by sow inventory, are put more weight by farmers than insurance suppliers when making decisions. Production efficiency measures perform as incentives for farmers to purchase insurance. While suppliers prefer customers who use vaccine, farmers tend to treat vaccine as a substitute for insurance to prevent disease risk.

Results from bi‐vairate probit model offer deeper understandings about livestock insurance choices and provide further insights to improve policy design and promote participation.

The study designed a special questionnaire and firstly used bi‐vairate probit model to offer more understandings about demand and supply sides of livestock insurance.

The authors investigate whether an index-based weather insurance (WII) product can complement or replace existing traditional crop yield insurance for mitigating farmers' financial risks, with an application to blueberry growers in British Columbia (BC).

A hybrid model combining expected utility (EU) and prospect values is developed to analyse farmers' demand for WII.

While weather data are used to investigate supply elements, a hybrid model combining EU theory and prospect theory (PT) is developed to analyse farmers' demand for WII. On the supply side, a quality index is constructed and the relationship between the quality index and key weather parameters is quantified using a partial least squares structural model. The authors then model weather parameters via time-series analysis and statistical distributions to provide reasonable estimates for calculating actuarially sound insurance premiums for a rainfall indexed, insurance product. This model indicates that decreases in the proportion of a blueberry grower's total revenue and revenue volatility will decrease the possibility that they participate in WII. At the same time, an increase in the value loss aversion coefficient and WII's basis risk further leads to less demand for WII. In short, a grower may decide not to participate in WII at an actuarially fair premium due to the combined effects of the above factors. Overall, while the supply analysis enables us to demonstrate that WII can potentially help in mitigating farmers' financial risks, it turns out that, on the demand side, blueberry growers are unwilling to pay for such a product without large government subsidies.

The authors argue that the demand for insurance may be affected by the level and the volatility of a berry grower's total revenue. Hence, the authors propose a hybrid expression that assumes a farmer seeks to maximize the total utility function to capture the rational and intuitive parts of a farmer's decision-making process. The EU represents rationality and the prospect value represents the intuitive component. Meanwhile, the authors investigate the possibility of using key weather parameters to construct a berry quality index – one that could be applied to other agricultural areas for studying the relationship between weather conditions and product quality.

This paper investigates Chinese agricultural insurance agents willingness to offer (WTO) livestock insurance based on the variations of eight main attributes of livestock insurance.

This study implements discrete choice experiments (DCE) with actual insurance agents who design, sell and operate livestock insurance in China. The choice experiment of this study is based on the D-optimal approach, a six-block design, with 15 cards per block and two choices per card. The sample size was 211. Econometrics results are based on conditional and mixed logit models.

The authors find that the subsidy effect is enormous; a one level increase of subsidy leads to 3.166 times higher probability to offer. This subsidy effect is important as it confirms the endogenous structure between price and quantity in insurance offering, where subsidy does not only incentivize demand but also the supply. Another main factor of insurance investigated is the impact of different coverage types on agents' WTO. The authors find that agents prefer mortality insurance the most, followed by revenue insurance and profit insurance, while Index-Based Livestock Insurance (IBLI) is the least preferred to offer. Agents' knowledge about these newer types of insurance supports their WTO as well; thus, proper education is necessary to promote the more advanced types of livestock insurance.

A limitation is that in the presence of COVID 19, and administrative issues at the local level, the sample was not randomly drawn. Nonetheless, the authors believe that there is enough diversity across participants, insurers and provinces and have done sufficient robustness checks to support results and conclusions.

This study provides further validation for the DCE research method that could potentially be applied to different analyses: using choice experiments to study insurers and reveal their preferences, through combinations of various levels of core attributes for insurance products. The findings and contribution are critical to the reform and improvement of livestock insurance in China and for insurance markets more broadly. The authors find that insurers do not place equal weights or values on insurance product attributes and do not view types of insurance equally. In other words, while farmers may hold different preferences about the type of insurance they demand, the results suggest that insurers also hold preferences in the type of insurance they sell.

So far as the authors are aware, this is the first DCE designed around the supply of insurance products with the subjects being insurance agents, marketers and executives.

This paper examines the relationship between behavioral biases, and demand decisions for life insurance products in Uganda.

Data were collected from 351 life insurance policyholders in Uganda. The authors used a cross-sectional survey by applying a structured questionnaire. Descriptive analysis was conducted and hypothesized relationships between the constructs were evaluated through the use of structural equation modeling.

Results indicate that, behavioral biases are significant predictors of life insurance demand among Ugandan policyholders. Also, the two behavioral bias variables (heuristic bias and prospect bias) are significant predictors of demand decisions for life insurance products.

These results are helpful for both insurers and regulators. For insurers, it is now evident that demand decisions for life insurance products are not fully rational. It is imperative for insurers to simplify life insurance product information (heuristics), integrate product education and widen dissemination of product information (prospect bias) to allow policyholders to come up with optimal demand decisions. While for insurance policymakers, the study provides an understanding of behavioral biases. With such insights, policymakers can identify exploitative and deceptive information that target policyholders to better guide life insurance documentation and product designs.

This study is the first to offer insights into behavioral biases' influence on demand decisions for life insurance products in a developing country like Uganda. By integrating prospects and expected utility theory, this study examines rationality and irrationality in demand decisions for life insurance products.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0201

The crop insurance purchase decision for a group of Kansas farmers is analyzed using farm‐level data from the 1990s, a period that experienced many changes in the federal crop insurance program. Results indicate a reduction in the elasticity of the demand for crop insurance with respect to premium rates by the end of the decade. The reduction in demand elasticity corresponded with a considerable increase in government subsidies by the end of the 1990s. This result may also reflect the attractiveness of new revenue insurance products which may have made producers less sensitive to premium changes.

This study examines the relationship between policyholders’ psychographic characteristics and demand decisions for life insurance products in Uganda.

The study is based on a cross-sectional survey. Using a purposive sampling method, 389 questionnaires were administered to life insurance policyholders in the four geographical regions of Uganda. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the primary data, specifically to test the relationships between the dependent and independent variables.

The findings indicate a positive and significant influence of psychographic characteristics on demand decisions for life insurance products. In addition, the analysis indicates that the two first-order constructs of psychographic characteristics, namely price consciousness and consumer innovativeness, are positive and significant predictors of demand decisions for life insurance products. In contrast, the third first-order construct religious salience, exhibits a negative and nonsignificant effect on demand decisions for life insurance products.

For insurance practitioners, to influence demand decisions, they should emphasize premium-related appeals in their marketing messages (price consciousness) ignore product decisions based on religious beliefs and norms (religious salience). They should also ensure that insurance products are highly trustable and experiential (consumer innovativeness). For insurance policymakers, it offers an in-depth understanding of customer psychographic characteristics, which can be used to identify exploitative information embedded in certain marketing campaigns targeting specific psychographic characteristics, for better regulation.

The study provides a basis for understanding lifestyle and personality characteristics (psychographics), which may influence demand decisions for life insurance products in a developing country like Uganda, where the insurance industry is at an early stage of development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0440

Life insurance is a kind of long-term investment; hence, the purpose of buying life insurance is to cover both current and future damages for the insured. Although insurance plays a crucial rule in fiscal and economic development, in MENA countries, insurance, especially life insurance, remains undeveloped, with a low penetration rate. Therefore, the purpose of this paper is to determine the factors that affect life insurance demand.

To analyze the determinants of life insurance demand during 2004-2012, a panel data model was estimated with Eviews software. Data on population, gross domestic product (GDP), interest rate, inflation rate, and human development index are extracted from the World Bank, and data on life insurance premium are gathered from Sigma International reports.

Results show that the price elasticity of life insurance demand is −0.77, the elasticity of life insurance subject to HDI is 1.68, the elasticity of life insurance subject to GDP is 0.92, and the elasticity of life insurance subject to interest rate is −0.33. The demand for life insurance has a positive significant relationship with population size.

The low elasticity of life insurance demand subject to GDP, interest rate, and inflation rate shows that the life insurance penetration rate in MENA countries is due to the dominance of compulsory insurance, and not due to voluntary purchasing of life insurance. The higher effect of HDI on the life insurance demand illustrates that, for developing the life insurance market, it is first necessary to improve the standard of life, education status, and the economic base.

As in the MENA region life insurance has remained undeveloped and there are no related studies in this area, it can be hypothesized that the life insurance penetration rate in MENA is due to the dominance of compulsory insurance and not due to voluntary purchasing of life insurance. The higher effect of HDI on life insurance demand illustrates that, for developing the life insurance market, it is first necessary to improve the standard of life, education status, and economic base.

The purpose of this paper is to identify the factors which influence the demand for micro‐insurance services among the informal sector workers of Ghana who are quite vulnerable to various risks in the economy.

The study adopts a quantitative technique based on primary data sampled randomly from 100 informal sector workers from four major market centers in Accra, Ghana. The probit regression model was used for the empirical investigation.

Empirical investigation using the probit model indicates that premium flexibility, income level and nodal agency are significant determinants of micro‐insurance demand. Insurance knowledge, expectation (trust) and marital status were also found to have positive and significant impact on the demand for micro insurance. Interestingly, the empirical analysis shows that formal education is not a significant determinant; rather one's level of insurance knowledge has a positive and significant impact on micro‐insurance demand.

Insurers must consider the nature of the cash‐flow of informal workers in the design of premiums. The government must integrate micro insurance into its poverty reduction program.

The micro‐insurance market is very new and unresearched in Ghana. This foundational study is, therefore, very original and a most valuable guide to commercial insurance companies which want to venture into this huge untapped opportunity in the Ghanaian informal sector.