Introduction: This study investigates the impact of China’s national-level city cluster policy on the synergistic governance of urban pollution reduction and carbon reduction, focusing on both “quantity reduction” (PM2.5 and CO ₂ emissions) and “efficiency improvement” (governance effectiveness). The research explores how the policy, as a quasi-natural experiment, contributes to these dual objectives. Methods: Using panel data from 274 prefecture-level and above cities from 2006 to 2023, the study employs a difference-in-differences (DID) model to estimate the impacts of the policy. Additionally, mediating and moderating effect analyses are incorporated to explore the mechanisms driving the outcomes. Results: The findings reveal that the city cluster policy significantly reduces PM2.5 concentrations and CO2 emissions in pilot cities, while simultaneously enhancing governance efficiency. Mechanism analysis identifies three main drivers: green technology innovation, knowledge spillovers, and industrial structure upgrading. Heterogeneity tests show that the quantitative effects (e.g., pollution reduction) are stronger in hub cities, while efficiency gains are more pronounced in non-resource-based cities. There are no significant differences between hub and non-hub cities for efficiency, and no significant impact of resource endowment on quantity reduction. Discussion: This study contributes to the literature in three key ways: (1) it develops a dual-dimensional framework to assess both “quantity reduction” and “efficiency improvement” in pollution and carbon governance; (2) it uncovers the mechanisms through which the city cluster policy operates; and (3) it identifies regional heterogeneity in the policy’s effects across different types of cities. The findings underscore the dual benefits of the policy, validate the mediating mechanisms, and highlight the role of regional differences in the outcomes. Policy implications include expanding and institutionalizing the pilot programme, fostering green innovation, and tailoring city cluster development strategies to local conditions.

Introduction: Sustainable agricultural productivity is a key priority for China as it navigates environmental challenges and growing food demand. Understanding the impact of agricultural structural adjustments, including crop-livestock integration, service-based agriculture, and digital transformation, on Green Total Factor Productivity (GTFP) is essential for formulating effective agricultural policies.Methods: This study analyzes data from 1,743 counties in China spanning from 2003 to 2022. Using econometric models, we examine the relationship between agricultural structural adjustments and GTFP growth, focusing on the roles of technological progress, structural changes, and digitalization. The study accounts for regional variations in agricultural productivity.Results: Our analysis finds that technological progress is the primary driver of GTFP growth. Agricultural structural changes, particularly crop-livestock integration and service-based models, contribute a “structural dividend,” enhancing sectoral efficiency and advancement. Interestingly, service-oriented models initially slow productivity but yield long-term benefits. Digital transformation significantly amplifies these positive effects. Regional analysis reveals that eastern and western regions benefit more from structural upgrades than central regions.Discussion: These findings highlight the importance of designing policies tailored to local contexts, especially considering regional differences in agricultural productivity. The integration of digital technologies and service-oriented models plays a crucial role in advancing GTFP. Policy-makers should focus on promoting inclusive, sustainable, and technologically-driven agricultural development to meet China’s future food security needs.

Introduction: Promoting sustainable food systems requires advancing social and economic equity, particularly in rural areas with limited access to technology. Digital skills are increasingly vital in narrowing consumption disparities and fostering sustainable livelihoods.Methods: This study investigates the impact of digital skills on consumption inequality among Chinese farmers using longitudinal data from the 2014–2020 China Family Panel Studies (CFPS). A Tobit regression model is employed, supplemented with robustness checks.Results: The findings reveal that digital skills significantly reduce consumption inequality, especially in subsistence-related categories (such as food and healthcare) and enjoyment-oriented categories (such as education and leisure).Discussion: Mechanism analysis identifies three key pathways through which digital skills operate: reducing mobility constraints, increasing non-farm employment opportunities, and improving access to information. The effects are particularly pronounced among farmers aged over 60 and those residing in central, western, northeastern, and northern regions. Policy implications include expanding digital skills training, enhancing regulation of rural credit institutions, and improving digital platforms for information dissemination. Tailored, region-specific strategies are recommended to accelerate digital inclusion and promote equitable rural development.

I. Credit ratings play a critical role in debt markets because they inform investors, lenders, and regulators about a firm’s ability to meet its financial obligations (Fitch Ratings 2021; Oh and Pa...