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The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

Sustainability has been a global consensus for the governments worldwide to address serious environmental issues. However, there is a lack of data envelopment analysis (DEA) studies evaluating the performance of government in promoting various sustainability sub-systems. To do this evaluation work, our study proposes new parallel-series network DEA models with alternative network structures of incorporating intermediate products. Particularly, this study develops a new methodological framework to evaluate various inefficiency sources. The framework contains an extended method of network meta/group frontier approach and a new concept of efficiency Foster-Greer-Thorbecke indicator. Empirically, this study considers the case of Chinese government-sustainability system from 2010 to 2017. Such work cannot be found in the existing studies. The main findings are summarized as follows. First, China has succeeded in realizing an overall improved efficiency during the examined periods. The importance of various divisions changes over time. Second, the occurrence of method heterogeneity and significant linkage inefficiency implies that the modelers should incorporate intermediate products in a well-suited way. Finally, inland provinces show higher technology gap inefficiency as for economy division. To improve the performance, inland provinces should promote their human capital and adopt advanced technology. This paper proposes new parallel-series network DEA models with alternative network structures of incorporating intermediate products. Particularly, this study proposes a unified framework to analyze the relationship between network structures and inefficiency sources through the use of meta/group-frontier approach. To identify the main technology diffusion that maybe further cause the inefficiency value, this study applies the FGT indicators to the productivity and efficiency field for the first time. The FGT indicators can be used to explore the structure of technology inequality and identify barriers to technology diffusion. [Display omitted] • We propose a new approach for modelling the parallel-series network structure. • This study applies new frontier framework to identify sources of inefficiency. • There has been growing trends in Chinese government-sustainability system. • Managerial inefficiency had a negative annual growth rate of −6.01%. • Inland provinces showed higher technology gap inefficiency for economy division. [ABSTRACT FROM AUTHOR]

The coal industry is an essential energy industry in China. From 2008 to 2020, the global economic crisis, the policy of de-capacity, and the decline of the coal industry all profoundly affected the development of coal mining areas. This paper combined emergy synthesis and super-efficiency Slacks-Based Measure-Data Envelopment Analysis (SBM-DEA) considering undesirable output to evaluate the eco-efficiency in the Longkou coal mining area's circular economy industrial chain from 2008 to 2020. This research finds that the eco-efficiency in the coal mining area was 0.73 in 2008 and then showed an upward trend from 2008 to 2020. The eco-efficiency was relatively effective in 2011, 2013–2016, 2018–2020. Due to the progress in mining technology and the decline in waste emission, the eco-efficiency showed an upward trend, and the peak eco-efficiency value was 1.26 in 2019. The circular industrial chain contributed a lot to the high eco-efficiency in general. The eco-efficiency in 2012, 2017 was low owing to the recession of the coal industry and the overcapacity of coal. According to the analysis results, the coal mining areas should develop circular economy, cleaner production, and extend the circular economy industrial chain. In addition, the coal mining areas ought to expand enterprise-scale, develop new energy industries (e.g., biomass energy, wind energy, photovoltaic power generation). • Evaluated eco-efficiency in the coal mining area's circular economy industrial chain. • Emergy synthesis combines undesirable super-efficiency SBM-DEA is verified. • Eco-efficiency showed an upward trend from 2008 to 2020. • The recession of coal industry and overcapacity of coal affected eco-efficiency. • Coal mining area should develop circular economy, cleaner production. [ABSTRACT FROM AUTHOR]