This study examines the effects of health expenditure, energy consumption, CO₂ emissions, population size, and income on health outcomes in 46 Asian nations between 1997 and 2019. Cross-sectional dependence (CSD) and slope heterogeneity (SH) tests are utilized due to the close linkages between Asian nations as a result of commerce, tourism, religion, and international agreements. The research uses unit root and cointegration tests of the second generation after validating CSD and SH issues. Due to the results of the CSD and SH tests, it is clear that conventional methods of estimation are inappropriate, so a new panel method, the inter autoregressive distributive lag (CS-ARDL) model, is used instead. In addition to CS-ARDL, the study’s results were checked with a common correlated effects mean group (CCEMG) method and an augmented mean group (AMG) method. According to the CS-ARDL study, higher rates of energy use and healthcare spending lead to better health outcomes for Asian countries over the long run. CO₂ emissions are shown to be harmful to human health, according to the study. The influence of a population’s size on health outcomes is shown to be negative in the CS-ARDL and CCEMG, but favorable in the AMG. Only the AMG coefficient is significant. In most instances, the results of the AMG and CCEMG corroborate the results of the CS-ARDL. Among all the factors influencing life expectancy in Asian countries, healthcare spending is the most influential. Hence, to improve health outcomes, Asian countries need to take the required actions to boost health spending, energy consumption, and long-term economic growth. To achieve the best possible health outcomes, Asian countries should also reduce their CO₂ emissions.

The overcoming of the issues on energy crisis and inequality have become the priorities as far developing as developed countries are concerned. Moreover, energy inequality has increased due to the shortage of natural gas and rising energy prices in retaliation to the economic recovery affected by the COVID-19 pandemic. This study aims to verify the linkage between the growth of renewable energy consumption and the country’s economic advancement. In this context, this paper determines the main driving forces of renewable energy consumption in European countries during 2000–2018. The annual data for panel regression analysis are retrieved from the OECD. Stat and World Bank Open Data. This empirical analysis employed a set of estimation procedures such as the panel unit root test (Levin, Lin & Chu; Im, Pesaran, Shin W-Stat; ADF-Fisher Chi-square; and PP-Fisher Chi-square methods), the Pearson correlation, fixed- and random-effects models, generalized method of moments (GMM), Hausman and the robustness tests. The results from the Hausman test ratified that the fixed-effects regression model is more suitable for involved panel balanced data. The results of fixed-effects regression and GMM identified the statistically significant and positive relationship between the share of renewable energy consumption of total final energy consumption, GDP per capita, and CO₂ emissions per capita for the overall sample. In turn, the total labor force, the gross capital formation, and production-based CO₂ intensity are inversely related to renewable energy consumption. The identified effects could provide some insights for policymakers to improve the renewable energy sector towards gaining sustainable economic development.

We investigated the resilience of small-scale family farms because of the contemporary importance of both the farms’ resilience and the role of these farms in five countries of Central and Eastern Europe. The authors addressed a research gap concerning cross-sectional research on the resilience of farms by combining determinants from various fields. Thus, the primary goal of this article was to identify microeconomic and political factors and links to markets that affect the resilience of small-scale family farms in Lithuania, Moldova, Poland, Romania and Serbia. Using a database of over 3500 farms, the resilience of the farms was calculated, and then the impact of selected factors on that resilience was determined. The research showed that the production scale was the key determinant of the resilience of farms. To achieve higher benefits, increasing the production should be combined with strengthening the market integration of agricultural producers. The position of the producer in the food supply chain determined the income situation of the farm (economic stability). This shaped the quality of life of the family members (social stability). Identifying the effects of those dependencies may provide recommendations for the policy of supporting small-scale family farms in the analysed countries.

Small- and medium-sized family farms are places to live and sources of income for about half of the population. The aim of this analysis was to determine the relationship between eco-efficiency and human capital efficiency on small- and medium-sized family farms. The analysis was carried out using an economic measure (value of agricultural production per work hour calculated per hectare) and two synthetic measures (human capital and environmental measures). The synthetic measures were determined using the TOPSIS-CRITIC method by defining weights for variables used in the measures. The analysis covered five countries: Lithuania (960 farms), Moldavia (532 farms), Poland (696 farms), Romania (872 farms) and Serbia (524 farms). All of these countries are characterised by a high fragmentation of agricultural holdings. The analysis allowed us to formulate the following conclusions: eco-efficiency and human capital efficiency indices increased with area for small- and medium-sized family farms. An increase in the eco-efficiency index with an increase in farm area suggests that the smaller the farm area, the more extensive the agricultural production that was carried out. In addition, an increase in human capital efficiency with an increase in farm area indicates that there was inefficiency in the utilisation of human capital resources on the agricultural farms studied.

The agricultural sector ensures food security and is a major source of employment, income, and economic activity in rural areas. The Food and Agriculture Organization of the United Nations (FAO) considers that family farms are the key to a sustainable future in Europe and Central Asia. In Romania, small farms represent the pillar on which Romanian society has been developed. Although the trend has been a reduction in the number of small farms and an increase in the number of large farms, the Government of Romania understands the importance of small farms and therefore supports them through policies involving direct payments, rural development instruments, special initiatives, and loans and outstanding obligations, among others, which focus on increasing their economic performance. The aim of our research was to determine the relationship between farmers’ motivation, their job satisfaction, and the farm economic performance in the case of small Romanian farms. The research sample consisted of 900 small farms (utilized agricultural area (UAA): under 20 ha; standard output (SO): under EUR 15,000). The data obtained after applying the questionnaires were analyzed using SPSS 20.0 and Amos 24.0. For the exploratory factor analysis, values of Bartlett’s test of sphericity, the Kaiser–Meyer–Olkin test, and Cronbach’s alpha coefficient were calculated for each dimension of the proposed model. The hypothesis that motivation, job satisfaction, and farm economic performance directly and positively influence each other was confirmed. An important finding was that the correlation coefficient between farmers’ motivation and farm economic performance was ρ = 0.78, while that for the relation between farmers’ job satisfaction and farm economic performance was ρ = 0.53, which was similar to the correlation coefficient calculated for the relationship between farmers’ motivation and farmers’ job satisfaction. This result allows us to conclude that the influence of farmers’ motivation factors on farm economic performance is stronger than the influence of job satisfaction in the case of Romanian farmers on small farms. This might explain why, although work in agriculture is considered to be worse than an office job and the people that work in agriculture are sometimes stigmatized and receive lower incomes, there are still very strong motivators for Romanian farmers to continue their work in agriculture. This is proven by the fact that Romania has the highest number of small farms in Europe, and this number is not decreasing.