The inclusive and environmentally sustainable transformation of economic growth is a crucial indicator for the high-quality development of urban areas. In this perspective, this paper explores the connection between digital inclusive finance and inclusive green growth in 270 Chinese cities from 2011 to 2021. The study used a panel dataset, individual fixed-effects models, and multiple mediation models to analyze the results. The study findings reveal that digital inclusive finance effectively stimulates regional inclusive green growth and enhances positive transmission mainly by improving green technology innovation, increasing entrepreneurship levels, and promoting industrial structure upgrading, of which environmental-friendly technology innovation channels constitute the main contributor. The effects of regions, administrative hierarchy of cities, financial marketization, policy support, and environmental regulation are analyzed in heterogeneity analysis. To ensure the robustness of baseline results, this study utilized two-stage least squares (2-SLS) and difference in difference (DID) approaches. Moreover, this study offers valuable insights into the environmental implications of digital financial inclusion in emerging economies.

Technology transfer represents a critical avenue for addressing the challenges associated with carbon emission reduction, warranting thorough investigation into the effects of both domestic and international technology transfer on carbon emissions. This study employs data mining techniques to extract comprehensive data on patent transfers across 334 prefecture-level cities in China from 2000 to 2021, analyzing the influence of technology transfer on carbon emissions from both domestic and international perspectives. The findings indicate that domestic technology transfer and international technology transfer significantly contribute to carbon emission reduction, with international technology transfer exerting a more substantial effect than its domestic counterpart. To mitigate endogeneity concerns, the study utilizes the shortest distance from each city to the telegraph lines established during the late Qing Dynasty as an instrumental variable and the resulting conclusions remain robust. Heterogeneity tests reveal significant regional disparities, particularly in areas located southeast and northwest of the Hu Huanyong line, as well as between regions inside and outside the five major urban agglomerations. The mechanisms underlying carbon reduction suggest that improvements in energy efficiency and upgrades in industrial structure serve as the primary pathways for carbon emission reductions resulting from both domestic and foreign technology transfers. These conclusions provide a theoretical foundation and empirical insights to facilitate the acceleration of technology flow within the context of high-quality development, particularly concerning environmental protection.

While achieving common prosperity necessitates a focus on the efficiency and equity of the primary income distribution, income inequality persists in China. As a critical tax incentive mechanism, China’s Accelerated Depreciation Policy (ADP) of fixed assets not only promotes important changes in corporate productivity and production methods but also significantly influences the primary income distribution within enterprises. However, current research offers a limited understanding of the importance of the ADP in the primary income distribution. Given that the core of the primary distribution lies in adjusting the labor income share, we regard 2014’s ADP as an exogenous “quasi-natural experiment”. After theoretically analyzing this policy’s effect on the labor income share of enterprises, our use of difference in differences (DID) validates our theoretical expectations with respect to China’s A-share listed companies during 2010–2022. The results show that the ADP can significantly increase enterprises’ labor income share; all hypotheses proved to be robust. The analysis of mechanisms shows that the ADP mainly affects the labor income share as it upgrades the corporate human capital structure as well as rent-sharing. Analyzing for heterogeneity, we find that positive effects due to the ADP affecting the labor income share are more prominent among private enterprises, medium and small-sized firms, companies with high financing constraints, capital-intensive industries, manufacturing enterprises, and those with a high level of skilled labor. The conclusions of this study contribute to uncovering the impacts of the ADP on income distribution, offering a clearer identification of particular mechanisms explaining the ADP’s effect on the labor income share. It holds significant theoretical value for understanding the micro-mechanisms of economic impacts generated by relevant policies. Furthermore, it provides policy insights in achieving common prosperity.

The issue of carbon emissions in China’s interprovincial border regions is crucial for achieving the nation’s carbon peaking and neutrality goals. This study aims to comprehensively analyze the spatiotemporal evolution characteristics of carbon emissions in China’s interprovincial border counties from 2005 to 2017, identify their key influencing factors using spatial econometric models, and elucidate the associated spatial spillover effects. Within the STIRPAT model framework and using GIS as a platform, datasets of county-level carbon emissions and spatial weight matrices for China’s interprovincial border areas were analyzed. Maps and spatial data analysis methods were employed to identify spatiotemporal patterns of carbon emissions in these regions. Additionally, the spatial panel Durbin model was utilized to uncover the driving mechanisms of key controlling factors. The findings indicate that although border counties contribute only marginally to China’s total emissions, they exhibit stronger growth compared to non-border counties. Notably, the average emissions in eastern border regions are comparable to the combined emissions of central and western regions. Spatial analysis reveals higher emissions in the north and east, with a trend of bidirectional expansion. While overall disparities are decreasing, they remain significant. High-high (HH) and low-low (LL) clusters demonstrate significant positive spatial correlation. Carbon emissions in border counties show substantial positive spatial spillover effects. Various factors influence emissions differently: population tends to suppress local emissions, while economic growth increases emissions both locally and in neighboring areas. Technological advancement reduces emissions in both local and adjacent regions, and industrial structure plays a driving role. This research provides novel insights into the carbon emission dynamics of border regions and offers a scientific basis for formulating differentiated emission reduction policies.

Introduction: Administrative rank, as an intuitive manifestation of a region’s political capital, significantly influences regional agglomeration capacity and innovative development. Methods: This study utilizes Chongqing’s promotion to a province-level municipality as a quasi-natural experiment, employing panel data from 219 counties in Sichuan and Chongqing (1992–2010) and applying the difference-in-differences (DID) method to evaluate the impact of administrative rank upgrades on regional innovation. Results: The findings show: (1) Administrative rank upgrade significantly enhances regional innovation with long-term positive effects; (2) Spatial spillover effects follow an inverted U-shape, peaking at 60 km and remaining significant within 30–120 km; (3) Population agglomeration and economic agglomeration are key mechanisms, with economic agglomeration having greater impact. Discussion: This study provides theoretical insights for optimizing administrative resource allocation, advancing institutional reform, and refining national innovation-driven development strategies.