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The purpose of this paper is to investigate the effect of flood occurrence on mortality rate and life expectancy amongst 53 African countries.

The study utilizes panel data from the period 2000–2018 on 53 African countries and system generalized method of moments (system GMM) for the analysis.

The result indicates that flood occurrence causes the destruction of health facilities and the spread of diseases which reduces life expectancy. In addition, flood occurrence increases mortality rate amongst 53 African countries.

The study recommends that governments amongst African countries should implement strategies being enshrined in Conference of Parties (COP, 2021) on climate change. This will help to reduce the level of climate change and flood occurrence.

Previous studies focussed on the adverse effect of flood occurrence without considering the issue of life expectancy amongst African countries. This study contributes to existing empirical studies by examining the effect of flood occurrence on mortality rate and life expectancy amongst African countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2022-0508.

While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.

This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.

The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).

The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.

This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.

Entrepreneurs nurture their ambitions of founding tech start-ups that facilitate significant innovations despite vulnerability and considerable uncertainty by resolutely addressing multiple challenges to avert failures. The paper aims to answer how soon do tech start-ups fail, given their lifecycle comprising multiple stages of formation and what attributes hasten failure of tech start-ups over their lifecycle? These questions have not been answered adequately, particularly in the context of India's emerging economy, where an aspiring start-up ecosystem is striving to flourish at an exceptional rate.

The study addressed two specific objectives: (1) Does life expectancy vary between life-cycle stages? and (2) What attributes impact tech start-ups' failures? Primary data were gathered from 151 cofounders (101 who have experienced failure and 50 who are successful and continuing their operations) from India's 6 leading start-up hubs. The survival analysis techniques were used, including non-parametric Kaplan–Meier estimator, to study the first objective and semi-parametric Cox proportional hazard regression to explore the second objective.

The survival probability log-rank statistics ascertain that life expectancy is different across the life-cycle stages, namely emergence, stability and growth. The hazard ratios (HRs) throw light on attributes like stage, revenue, conflict with investors, number of current start-ups, cofounder experience, level of confidence (LoC) and educational qualifications as the key attributes that influence start-up life expectancy over its lifecycle.

The empirical study on tech start-ups' life expectancy has practical implications for entrepreneurs and investors besides guiding the ecosystem's policymakers. First, the study helps entrepreneurs plan for resources and be aware of their start-up journey's potential pitfalls. Second, the study helps investors to establish the engagement framework and plan their future funding strategy. Third, the study helps policymakers to design and establish progressive support mechanisms that can prevent a start-up's failure.

First and foremost, start-up life expectancy study by life-cycle stages provide detailed insights on start-ups' failures. The theoretical framework defined is replicable, scalable and distinctly measurable for studying the start-up failure phenomenon. The life expectancy of tech start-ups by life-cycle stage is a critical empirical contribution. Next, the attributes impacting start-up life expectancy are identified in the context of an emerging economy.

Few empirical studies examined the relationship between life expectancy and income in India. This study aims to examine the impact of life expectancy on economic growth in India by incorporating all the major states of India.

This study is based on secondary data and includes 16 major states of India covering the periods 2000–2014. The author used panel fixed effect model (FEM) to examine the impact of life expectancy on economic growth.

Empirical analysis revealed a positive trend in life expectancy in India. In association with life expectancy, the author found continuous growth in the elderly population. The result of the FEM shows that gains in life expectancy positively affect economic growth in India. The empirical findings do not support any negative impact of life expectancy gains on economic growth.

This study is the outcome of the independent and original research work of the authors and contributes significantly to the literature on the demography–economic relationship. The findings of this study help the author to understand that life expectancy gain is in no way a constraint, rather the skill and experience of the workforce are crucial to determining economic growth.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2022-0422.

What is the relationship between longevity and health? Health expectancies were developed more than 30 years ago specifically to answer this question. It may therefore be the time to try to answer this question, though it is worth noting that the question implies a unidirectional relationship. Almost no one questions the positive association between health and longevity. It is expected that healthy, robust people will live, on average, longer than frail people. This heterogeneity in terms of robustness/frailty may explain the shape of the mortality trajectory with age, ie. the oldest old seem to follow a lower mortality schedule (Vaupel et al, 1979). On the other hand, many people wonder about the relationship between longevity and health. Are we living longer because we are in better health? Are we living longer in good health? Or are we merely surviving longer whatever our health status? In other words, can we live in good health as long as we can survive? And this is exactly the purpose of health expectancies: monitoring how long people live in various health statuses (Sanders, 1964; Sullivan, 1971; Robine et al, 2003a).

The purpose of the study is to examine the relationship between air pollution and life expectancy considering the roles of institutional quality, agricultural output, foreign direct investment (FDI) and other socio-economic variables in Nigeria from 1981Q1 to 2019Q4.

The study employed spliced quarterly data from annual series collected from the World Bank development indicators and Central Bank of Nigeria. The dynamic multivariate models were analysed using the vector error correction mechanism (VECM), variance decomposition and Granger causality techniques.

The VECM result indicated a statistically significant adverse effect of air pollution on life expectancy. However, institutional quality, gross domestic product per capita, agricultural output, government social expenditure and school enrolment rate ameliorate the adverse health effects of air pollution, while FDI had mixed effects on life expectancy at different significance levels and at varying lag lengths. The Granger causality result revealed a uni-directional causality from air pollution to life expectancy; bidirectional causal chain between agriculture, FDI, government social expenditure and life expectancy, while a uni-directional causal linkage run from life expectancy to income per head and from school enrolment to life expectancy respectively. However, there is no evidence of causation between institutional quality and life expectancy due to weak institutional quality, but foreign direct invest causes carbon emission in a uni-directional manner in line with pollution haven hypothesis.

The study's modelling is limited by not considering the resource curse variable in the model due to paucity of data. Nigeria is the biggest crude oil exporter in Africa and ranks 13th globally with daily output of about 2.4 m barrels. Thus, the negation of resource curse in air pollution–life expectancy nexus de-emphasises the effectiveness of rich resources on health and environment. Future studies could address this limitation by incorporating resource curse in environmental-health models for Nigeria.

It is imperative for the country to adopt stringent anti-air pollution strategies that would establish a balance between FDI attraction and agricultural expansion to the benefits of her citizens' longevity. Also, education should be considered as a strategic action to enhance life expectancy through expansion in the provision, accessibility and affordability to improved school enrolment rate. The choice of quarterly time series over annual data helped to establish the current relationship between air pollution and life expectancy using efficient estimators.

The study contributes to literature by disaggregating yearly series into quarterly series, which has implications for the efficiency of the estimates, unlike earlier studies which ignored this fundamental process. The result of this study produced reliable policy direction for improvement in life expectancy in an emerging economy since quarterly estimates are more robust and reliable for forecasting than its yearly counterpart. The outcome of the study extended the original tenets of the Grossman's health stock theory using the environmental Kuznets curve (EKC) and pollution haven hypotheses (PHH).

The present study investigates the nexus between health performance dynamics and economic growth in 43 countries in sub-Saharan Africa for the period 2004–2018.

Four health performance dynamics are used, notably: total life expectancy, male life expectancy, female life expectancy and risk of maternal death. The empirical evidence is based on quantile regressions (QRs) in order to put into perspective the conditional distribution of economic growth.

The following findings are established: (1) total life expectancy and male life expectancy increase economic growth exclusively in the 10th and 90th quantiles of economic growth; (2) female life expectancy boosts economic growth in the 90th quantile of economic growth and (3) the risk of maternal death reduces economic growth in the 75th and 90th quantiles of economic growth. Policy implications are discussed.

The study complements the literature on the nexus between health performance and economic growth by assessing the nexuses throughout the conditional distribution of economic growth.

One of the most contentious issues concerning benefit–cost analyses of environmental and other regulatory programs has been the valuation of reductions in mortality risks. The conceptual basis for most valuation exercises has been the value of a statistical life (VSL). However, despite decades of both theoretical and empirical research on the meaning and measurement of the VSL concept, there is no consensus concerning the validity of the results it produces in actual applications. In this paper, we review the development and application of the VSL approach and then propose what we believe to be a better way to value changes in mortality hazard.

The purpose of this paper is to investigate the driving forces (economics and socio-demographic) that influence family Takaful demand in the Middle East and North Africa (MENA) region, using a sample of 15 countries from the MENA.

The authors use multivariate analysis, bootstrapping and generalised method of moments techniques. They first examine a full model that combines all variables; second, a model that controls for product market factors; and finally, a model that controls for socio-demographic factors. They further separate all models into linear and log-linear demand functions.

The authors demonstrate that the relationship between the demand for family Takaful in MENA and Islamic banking deposits, education, dependency rate, female life expectancy and Muslim population is significantly positive. On the other hand, the significant factors that are inversely related to the demand for family Takaful in MENA are inflation, financial development and male life expectancy.

The crucial limitation of this study is the amount of data available in regards to the dependent variable, family Takaful contributions. Consequently, to improve the understanding in explaining the family Takaful demand in MENA, further research can take advantage of expanding the variables that were omitted in this research as a consequence of the unavailability of data. Some of the possible influential variables can include government social security expenditure, legal system and government policies, price of Takaful and level of competition within the Takaful and insurance industry.

It is obvious that there are very few studies that focus on the MENA market, and indeed, none of them gives attention to the factors that influence demand for family Takaful. While this study is expected to provide more understanding and awareness on the concept of Takaful and the factors that influence its demand, the authors hope that it would encourage more studies on various issues on the Takaful industry so as to help researchers to understand more aspects of this new emerging business.

The human development index (HDI) and gender‐related development index (GDI) have become accepted as leading measures for ranking human well being in different countries. The purpose of this paper is to identify the planning policies that improve these indices and to also suggest modifications to the indices that yield more sensible policies.Design/methodology/approach – This paper solves the first‐best welfare problem in which the planner maximizes a development index subject to resource constraints.Findings – Planning strategies that maximize the HDI tend towards minimizing consumption and maximizing expenditures on education and health. Interestingly, such strategies also tend towards equitable allocations, even though inequality aversion is not modelled in the HDI. The paper shows that the GDI generates optimal plans with similar properties, and determine when the GDI and HDI generate consistent optimal plans. A problematic feature of the optimal plans is that the income component in the HDI (or GDI) does not play its intended role of securing resources for a decent standard of living. Rather, it acts to distort the allocation between health and education expenditure. The paper argues that it is better to drop income from the index. Alternatively, the paper considers net income, income net of education and health expenditures, as indicating capabilities not already reflected in the index. Finally, it compares how the modified indices and the HDI rank countries.Originality/value – The paper is believed to be the first to integrate development indices into national development planning.