This study investigates the intricate relationship between external debt, debt service, and economic growth by using the panel data of 32 Asian Developing Economies (ADE) spanning 1995 to 2020. Employing a two-step system generalized method of moments (GMM) and a dynamic common correlated estimate (DCCE) model, the research explores key macroeconomic channels through which debt influences growth and rigorously tests for debt overhang and crowding-out effects. Findings reveal that public and private investment, total factor productivity, and national savings are pivotal channels transmitting the non-linear effect of external debt on economic growth. Notably, only private and public investment convey the non-linear effects of debt service to economic growth, while productivity and savings convey the linear effect. Evidence of debt overhang and crowding-out effects is identified in the sampled economies. The study suggests strategic measures for developing countries, emphasizing the productive use of accumulated debt, enhanced debt management, and timely project completion. Furthermore, it advocates for fostering economic growth through increased productivity, domestic savings, and private sector expansion to reduce dependence on foreign debt, facilitating both debt repayment and economic self-sufficiency.

A strong need exists to increase the knowledge and recognize the values of neighborhood services. This paper makes an attempt to examine the impact of neighborhood services on land values, through analysis based on results obtained from multi linear regression analysis. This case study was done in area of dense urban settlement to check the consequence of neighborhood services through the hedonic pricing model base variables which include the structural, locational, community and neighborhood services. The regression coefficient was checked at (p < 0.05) level of significance for each variable. The primary data was collect through the questionnaire filling by random sampling and Punjab Urban Gazette was used for the verification of land values in study area. The results found a valuable potential on land and property values of neighborhood services through the regression analysis results express through R (0.926), R² (0.856) and coefficient tables to represent the effect of each individual variable on property and land values. Every individual variable play role in defining the values of land and property based upon its utilization such as larger the structure of a property, more the covered area, larger size of a property more the land area higher price. Similarly, for locational factor study in geography, a piece of land adjacent to the road have high land values 50–70% compare to those located at distance. Very less attention has been paid on such issues in the world due to lack of effective urban planning and research on such crucial issues. If empirical studies on such issue has been done, effective way can be obtained for urban planning.

Fiscal decentralization is perceived as a viable strategy for fostering economic growth in Pakistan. Concerns persist regarding its potential impact on environmental quality, particularly in relation to increased carbon emissions. Employing diverse analytical methods such as structural vector autoregressive (SVAR) modeling and autoregressive moving average model evaluations, this study comprehensively explores the dynamic relationships among fiscal decentralization, economic development, and environmental quality over the period 1979–2019. Intriguing trends emerge, revealing positive correlations between environmental efficiency and variables, including revenue collection, tax autonomy, and transfer payments. Conversely, a negative correlation is observed between government spending and economic growth. The interplay of these variables results in oscillations in the influence of fiscal decentralization on carbon emissions, presenting a complex challenge for policymakers. Notably, positive fiscal decentralization shocks lead to an increase in carbon emissions, while positive expenditure decentralization and economic development correlate with decreased carbon emissions. Despite economic growth's statistically significant negative impact on carbon emissions, the intricate nature of the relationships underscores the complexity of the link between fiscal decentralization, economic expansion, and environmental outcomes. From a policy perspective, the study emphasizes the need to adjust fiscal policies and coordinate intergovernmental fiscal ties across all government levels to enhance environmental efficiency. These findings provide policymakers with valuable insights to navigate the intricate landscape of fiscal decentralization and its environmental implications.

Although the importance of green supply chain management (GSCM) in addressing climate change and enhancing performance has been acknowledged, the roles of green innovation (GI), green self-efficacy (GSE), and big data analytics capability (BDAC) in shaping environmental performance (EP) and financial performance (FP) remain underexplored. This study investigates these relationships using the dynamic capability view and self-efficacy theories. Data were collected through an online survey of 386 employees from Pakistani manufacturing firms and analyzed using partial least square structural equation modeling, validated and ranked through artificial neural network analysis. The findings show that GSCM practices significantly enhance EP and FP. GI and GSE serve as key mediators, while BDAC moderates the relationship between GSCM and EP, though its effect on FP is insignificant. This research addresses the overlooked interplay among these constructs, offering practical insights for firms and policymakers to institutionalize GSCM by prioritizing green training programs to strengthen GSE, while developing BDAC to enhance environmental monitoring, support informed decisions, and improve the sustainability outcomes of GSCM.