The circular economy has become a strategic priority in the European Union, aiming to reduce dependence on finite natural resources and promote a sustainable economic model. This study investigates the key factors influencing the use of circular materials in the European Union between 2010 and 2022, considering the impact of global challenges such as the coronavirus pandemic, the energy crisis, and geopolitical tensions. Unlike previous research, this study integrates economic, technological, and environmental dimensions, with a particular focus on the role of digital transformation as a catalyst for circularity. The research applies an econometric model based on the analysis of panel data to explore the interconnections between resource productivity, recycling rates, private sector investment, digitalization, and expenditures on research and development. The findings reveal a strong positive relationship between resource efficiency, recycling efforts, and the use of circular materials, emphasizing the importance of infrastructure and technological advancements in supporting circularity. However, significant regional differences among European Union member states are also identified, highlighting the need for targeted policies to address these disparities. In the context of European policies such as the Green Deal and the Circular Economy Action Plan, this study provides valuable insights for decision makers. The results suggest that increasing investment, expanding digital infrastructure, and fostering innovation are essential for accelerating the transition to a circular economy. This research contributes to the existing literature by offering a comprehensive perspective on circularity and demonstrating how digital transformation can enhance sustainability.

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.