The increase in energy consumption is closely linked to environmental pollution. Healthcare spending has increased significantly in recent years in all countries, especially after the pandemic. The link between healthcare spending, greenhouse gas emissions and gross domestic product has led many researchers to use modelling techniques to assess this relationship. For this purpose, this paper analyzes the relationship between per capita healthcare expenditure, per capita gross domestic product and per capita greenhouse gas emissions in the 27 EU countries for the period 2000 to 2020 using Error Correction Westerlund, and Westerlund and Edgerton Lagrange Multiplier (LM) bootstrap panel cointegration test. The estimation of model coefficients was carried out using the Augmented Mean Group (AMG) method adopted by Eberhardt and Teal, when there is heterogeneity and cross-sectional dependence in cross-sectional units. In addition, Dumitrescu and Hurlin test has been used to detect causality. The findings of the study showed that in the long run, per capita emissions of greenhouse gases have a negative effect on per capita health expenditure, except from the case of Greece, Lithuania, Luxembourg and Latvia. On the other hand, long-term individual co-integration factors of GDP per capita have a positively strong impact on health expenditure per capita in all EU countries. Finally, Dumitrescu and Urlin’s causality results reveal a significant one-way causality relationship from GDP per capita and CO₂ emissions per capita to healthcare expenditure per capita for all EU countries.

Earnings disparities in South Africa, and specifically the Eastern Cape region are influenced by a complex interplay of historical, socio-economic, and demographic factors. Despite significant progress since the end of apartheid, persistent disparities in earnings continue to raise questions about the effectiveness of policies aimed at reducing inequality and promoting equitable social system. Individual-level dataset from the 2021 South African general household survey were subjected to exploratory analysis, while Heckman selection model was used to investigate the determinants of earnings disparities in the study area. The results showed that majority of the population are not working for a wage, commission or salary, which also pointed to the gravity of unemployment situation in the area of study. Most of the working population (both male and female) are lowest earners (R ≤ 10,000), and this also cuts across all age-group categories. Majority of working population have no formal education, are drop out, or have less than grade-12 certificate, and very few working populations with higher education status were found in the moderate and relatively high earnings categories. While many of the working population are engaged in the informal sector, those in the formal sector are in the lowest earners group. Compared to any other race, the Black African group constituted the majority of non-wage earners, and most in this group were found in the lowest earners group. Some of the working population who were beneficiaries of social grants and medical aids scheme were found in the lowest, low, and moderate earnings categories. The findings significantly isolated the earnings-effect of age, marital status, gender, race, education, geographic indicators, employment sector, and index of health conditions and disabilities. The study recommends interventions addressing racial, gender, and geographic wage gaps, while also emphasizing the importance of equitable access to education, health infrastructure, and skills development.

This paper presents an assessment approach to fostering socioeconomic re-development and resilience in Iraqi regions emerging from the destruction and instability, in the aftermath of the war conflict in Iraq. Focusing on the intricate interplay of logistics infrastructure and economic recovery, the present study proposes a novel framework that integrates general resilience insights, data analytics, infrastructure systems, and decision support from Data Envelopment Analysis (DEA). We draw inspiration also from historical cases on “creative destruction” or “Blessing in Disguise” (BiD) phenomena, like the post-WWII reconstruction of Rotterdam, so as to develop the notion of stepwise or cascadic prosilience, analyzing how innovative logistics systems may in various stages contribute to economic rejuvenation. Our approach recognizes the multifaceted nature of regional resilience capacity, encompassing both static (conserving resources, rerouting, etc.) and dynamic (accelerating recovery through innovative strategies) dimensions. The logistics aspect spans both the supply side (new infrastructure, ICT facilities) and the demand side (changing transportation flows and product demands), culminating in an integrated perspective for sustainable growth of Iraqi regions. In our study, we explore several forward-looking strategic future options (scenarios) for recovery and reconstruction policy factors in the context of regional development in Iraq, regarding them as crucial strategic elements for effective post-conflict rebuilding and regeneration. Given that such assets and infrastructures typically extend beyond a single city or area, their geographic scope is broader, calling for a multi-region approach. By leveraging the extended DEA approach by an incorporation of a super-efficiency (SE) DEA approach so as to better discriminate among efficient Decision-Making Units (DMUs)—in this case, regions in Iraq—our research aims to present actionable and effective insights for infrastructure investment strategies at regional-governorate scale in Iraq, that optimize efficiency, sustainability and resilience. This approach may ultimately foster prosperous and stable post-conflict regional economies that display—by means of a cascadic change—a new balanced prosilient future.