Additional energy demand is needed to accomplish the mega-projects of the Belt & Road Initiative (BRI). As energy consumption is one of the prime determinants of environmental degradation, the present study investigates the impact of energy inequalities on environmental degradation along with financial development. The entropy approach is applied to quantify the three energy consumption inequalities; average, between, and total energy consumption inequality respectively. The energy consumption inequality of BRI economies follows an uprising temporal trend. The estimates reveal that East Asia and South Asia have the highest and lowest energy consumption inequality among the BRI regions. Within regions, it is found that Central Asia has the lowest, and East Asia has the highest energy inequality among the BRI regions, respectively. Based on bootstrapping, the generalized least square (GLS) is applied to quantify the impact of energy consumption inequalities on environmental degradation along financial development. The energy inequalities have a statistically positive impact on environmental degradation in BRI regions, East Asia, Central Asia, the Middle East and North African region (MENA), and Southeast Asia respectively. In contrast, South Asian economies are sustaining environmental quality despite the energy consumption inequalities. Financial development also has a significantly major impact on environmental degradation in BRI, and its regions except for Central Asia, and MENA.

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According to the World Health Organization, lower-income countries suffer from adverse health issues more than higher-income countries. Information and communication technologies (ICT) have the potential to resolve these issues. Previous research has analyzed the theoretical and empirical causal effects of ICT on infant mortality at country-specific and global levels for a short period of time. However, the causes and results could be different in low-income countries. The objective of this paper was to examine the deficiencies through the use of panel data from 27 low-income countries from 2000–2017. We applied the predictive mean matching technique to supplement the missing data and then used panel data techniques (i.e., fixed effects (FE) and pooled common correlated effects (PCCE)), and system-GMM to estimate the causal effects. We compared the consistency and the possible heterogeneity of previous results using a set of robust techniques and empirical tests. We found that internet access and, to a lesser extent, cellular mobile subscriptions, two of the three ICT variables used in our research, had a significant positive effect on reducing infant mortality in low-income countries. In conclusion, governments and policymakers of low-income countries should consider the availability of internet-related ICT innovations and make them nationally accessible to reduce health crises such as the infant mortality rate.

The most important asset for a person is their health and wellbeing. While it is possible to keep one’s health at its best, it is common for people to have health shocks (HSs; negative shocks to an individual’s health). In this study, using Chinese Health and Nutrition Survey (CHNS) panel data, we studied the impact of different HSs on income using new modified methods. Thus, we considered the substantial links among different HSs, levels of education, and insurance types, as well as their impact on people’s wealth defined by their income. The core aim of this study is to help devise and guide new policies to reduce the effect of these HSs through the proper use of education and insurance channels. In this research, we used simple pooled OLS regression to measure the different causality estimates of HSs, education, and insurance, as well as their interactions. Obtained through the use of up-to-date panel data, the study results are consistent with previous research using different HS and education measures. The findings of this research suggest revising previous policies concerning education levels and health insurance schemes.

PurposeLife insurance is bought with a prior belief that promise stipulated in policy will be honored when due. Discernibly, this belief is backed by the confidence that financial markets and economy will demonstrate satisfactory performance. However, individuals' confidence levels may get shaken through naïve reinforcement learning if they witness negative market or economic condition. Considering this the authors investigate the relationship between investor confidence and life insurance demand.Design/methodology/approachThe authors used bias corrected bootstrapped sample of OECD economies to examine the link between investor confidence and life insurance demand when two possible economic conditions were witnessed: 1) normal/economic expansion and 2) economic/debt impairment. The findings are robust to alternate estimation techniques and endogeneity.FindingsThe authors found that lower investor confidence, sovereign debt impairment and negative market condition will have negative repercussion on life insurance demand. On the other hand, investor confidence-life insurance demand nexus is merely influenced by market and economic condition.Originality/valueThis is a premier research explaining the nexus between investor confidence and life insurance demand in the context of life-cycle hypothesis, sovereign ratings channel and experience-confidence-belief framework. The finding will help economic policy-makers in developing pre-emptive measures to protect life insurance businesses from negative repercussions of lower confidence and negative market conditions.