Does economic agglomeration improve agricultural green total factor productivity? Evidence from China's Yangtze river delta

Low-carbon pilot policy and development path in urban agglomerations of China: Mechanism analysis and stage identification

Urban agglomeration (UA) plays as the main carrier of economy and society in China, concentrating the human activities, energy consumptions, and subsequent carbon emissions in space. The policy-induced mechanism of carbon emissions in the units of UA is currently less explored, and diversities of low-carbon development path of UAs remain unknown. Thus, this study analyzes the carbon emissions of 19 UAs in China from 2006 to 2019, focuses on the low-carbon city pilot policy (LCPP), constructs an SDM-DID model to investigate the impacts of LCPP on carbon emissions regionally, and delineates the stages of low-carbon development in UAs based on the theory of Environmental Kuznets Curve. The results show that carbon emissions of China's UAs are spatially distributed as higher in the east but lower in the west, and increase faster in the central. The effect of LCPP on carbon emissions is significant but inhibitory in the central and northeastern UAs, while it becomes insignificant in the eastern ones. Finally, the low-carbon development paths of all UAs are divided into Type I, strong Type I, Type II, Type III, and Type IV stage. The eastern UAs are all at Type I stage because they are more sensitive and ahead in terms of low-carbon development strategies. The findings of this study can provide references for city groups to formulate carbon reduction policies and decouple the relations between economic development and carbon emissions.

Special collections for applying artificial intelligence techniques to encourage economic growth and maintain sustainable societies

Efficient resource use requires substantial evaluation and re-evaluation of production processes. Since not all production details can be properly and timely monitored and adjusted, improvement of resource allocation has long been a critical issue in commodity production, technique selection, and sustainable development. The progress of artificial intelligence (AI) offers a possibility. For example, with deep learning techniques and extensive data analysis, most previously unincorporated or unknown information associated with a firm's activities can be appropriately reflected and calculated. Once the firms take the report, a more efficient and economically friendly production strategy could be made. The central theme of this special collection is to invite studies on how the design and application of AI benefit not only the fields of computer science and information engineering but also the interdisciplinary fields, including renewable energy development, environmental protection, and economic analysis. Fourteen papers are published in this special collection.

Spatial-temporal evolution and convergence analysis of agricultural green total factor productivity-evidence from the Yangtze River Delta Region of China

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist-Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use.