The labor force, physical capital, and energy sources are key economic drivers that enhance the output levels of developing economies. Despite their significance, the impact of these factors on agricultural and industrial output in Pakistan remains underexplored. This study aims to address this gap by examining the effects of the labor force, physical capital, and energy consumption—including electricity, oil, and gas—on agricultural and industrial output. Additionally, we explore the combined effects of electricity and oil consumption on these sectors. Based on unit root test results, which indicate that the variables as either I(0) or I(1), the Autoregressive Distributed Lag (ARDL) technique is selected. This method is particularly effective for handling mixed integration orders and provides robust estimates in small sample sizes, allowing for a thorough examination of both short- and long-run dynamics. Using annual time-series data from Pakistan for the period 1990–2022, the empirical results reveal that higher levels of the labor force, physical capital, electricity consumption, oil consumption, and gas consumption significantly increase agricultural and industrial output in both the short and long run. Furthermore, the findings reveal that the combined effect of electricity and oil consumption has a stronger impact on agricultural and industrial output compared to their individual effects. These results are further validated using alternative econometric techniques such as DOLS and FMOLS. To enhance Pakistan’s agricultural and industrial performance, policies should prioritize investment in human capital and physical capital development, ensure reliable and efficient energy supplies, and promote integrated energy management strategies. These steps are crucial for fostering sustainable economic growth and productivity in both sectors.

The labor force is a crucial factor in conducting economic activities, especially in labor-surplus countries like Pakistan. In this study, we explore the impact of labor force participation (LF) on economic growth (EG), with an emphasis on how this impact depends on the levels of health and education expenditures. We analyze time series data from Pakistan spanning from 1980 to 2022, using ARDL (Autoregressive Distributed Lag), ECM (Error Correction Model) and Granger causality techniques for empirical analysis. The ARDL results indicate that LF significantly boosts EG, both in the short and long run. Furthermore, the estimations reveal that better facilities for health and education strengthen the positive effects of LF on EG. This suggests a complementary relationship between health, education, and LF in driving EG. Moreover, our findings highlight the temporal significance of health and education: Health plays a more crucial role in the short run, while education’s impact is more substantial in the long run. Furthermore, the Granger causality results indicate that LF, health, and education significantly contribute to EG. It is advisable for the government to prioritize investments in the health and education sectors. This approach can empower individuals to actively and effectively participate in economic activities, eventually contributing to the overall economic output of the nation.

The study aims to assess the performance of European sustainable agriculture through a new model of agricultural sustainability, addressing a significant gap identified in the literature: the lack of a systematic framework integrating the economic, environmental, and resource efficiency dimensions of agricultural resource use in the context of the EU Common Agricultural Policy and the Green Deal. The research develops four synthetic indicators: ISPAS (Index of Sustainable Agricultural Productivity), IREA (Index of Reduced Emissions from Agriculture), ISAC (Index of Combined Agricultural Sustainability), and IESA (Index of Agricultural Land Area Efficiency), each reflecting complementary aspects of sustainable agricultural performance. The methodology is based on an econometric linear model and a dynamic Arellano–Bond model, which allows the analysis of the temporal relationships between synthetic indicators and agricultural sustainability performance, capturing the inertia effects and structural dynamics of the European agricultural sector. The modeling provides a robust approach to capture the interdependencies between agricultural emission reductions, sustainability mainstreaming, and land use efficiency. The results of the study indicate a superior quality of measurement by applying this integrated framework, highlighting significant relationships between emission reductions, the integration of economic and environmental dimensions, and the optimization of agricultural land use. The analysis also provides valuable policy implications, suggesting concrete directions for adapting European agricultural policies to the structural particularities of Member States. By integrating a dynamic methodological framework and innovative synthetic indicators, this study contributes to a thorough understanding of agricultural sustainability performance and provides a practical tool for underpinning sustainable agricultural policies in the European Union.

Environmental sustainability has been a challenging issue all over the globe, with air pollution posing a significant threat. One main factor contributing to air pollution is the growth of the shadow economies. This study investigates the effect of the shadow economy on air pollution and explores how these effects depend on the levels of governance indicators. We utilize key air pollution indicators: carbon dioxide (CO₂) and nitrous oxide (N₂O) emissions. Furthermore, we examine the role of key governance indicators: corruption control, the rule of law, and regulatory quality. The study utilizes an annual panel dataset of 107 selected developing countries worldwide, spanning from 2002 to 2020, and employs the System GMM technique, which effectively tackles the omitted variable bias, potential endogeneity, and simultaneity issues in the model. The estimation results indicate that a sizeable shadow economy significantly increases the levels of CO₂ and N₂O emissions. Moreover, the results reveal that robust governance frameworks, evidenced by enhanced corruption control, a stronger rule of law, and superior regularity quality, mitigate the adverse effects of the shadow economy on CO₂ and N₂O emissions. This highlights a significant substitutability between the shadow economy and governance indicators, indicating that improvements in governance formworks will not only reduce the size of the shadow economy but also weaken its harmful impact on air pollution. Policy initiatives should thus focus on strengthening governance mechanisms, particularly enhancing control of corruption and the rule of law to effectively reduce the environmental impact of the shadow economies in developing countries. Additionally, governments should prioritize reforms in regulations and legal frameworks to limit the expansion of the shadow economy, thereby decreasing their contribution to air pollution.

The present research aims to address the highly topical issue of heavy metal water pollution from an integrated European perspective, i.e., to quantify through modelling a general model of water pollution reduction in the EU. The objectives of the study are mainly aimed at identifying effective solutions to reduce heavy metal water pollution and providing supranational decision-makers with public policy directions in the field. The research methods consist of the foundation of working hypotheses based on the study of the literature, the consolidation of official statistical databases in the field, econometric modelling and the conceptualisation of a general model and its testing and validation by statistical methods. The results of the analysis consist of the following marginal contributions: the identification of a general model for combating heavy metal pollution; the calculation of the degree of contribution of regional policies to the general model; and the identification of effective solutions to improve the combating of heavy metal water pollution in Europe. The main conclusion of the analysis shows that significant progress has been achieved at the EU level in the field of combating heavy metal water pollution. However, the level of disparity and poor policy coordination are real vulnerabilities for the EU.