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In many countries, the urban–rural income inequality affects healthy and sustainable economic development and is a pressing issue that requires immediate attention. As a new industrial development model, rural industrial convergence can provide new ideas and impetus for alleviating the urban–rural income inequality. This study, drawing on provincial panel data from China spanning 2010 to 2022, used the entropy method and Theil index to measure the rural industrial convergence and the urban–rural income inequality, respectively, and empirically tested the effect and mechanism of rural industrial convergence on the urban–rural income inequality. The results showed the following: (1) Rural industrial convergence had a notable impact on alleviating the urban–rural income inequality. (2) Rural industrial convergence could help reduce the urban–rural income inequality by increasing the scale of land operation. (3) The government attention to green development could positively moderate the impact of rural industrial convergence on the urban–rural income inequality; the deeper the government attention to green development, the greater the role rural industrial convergence played in alleviating the urban–rural income inequality. (4) There was a threshold effect in the alleviating effect of rural industrial convergence on the urban–rural income inequality, which was gradually strengthened when the growth of the digital economy and the enhancement of the business environment were beyond the threshold point. (5) Rural industrial convergence also had significant spatial spillover effects on adjacent regions. Overall, the findings of this study enrich the research on the impact of rural industrial convergence on the urban–rural income inequality and provide insights for other similar countries. [ABSTRACT FROM AUTHOR]

In many countries, the urban–rural income inequality affects healthy and sustainable economic development and is a pressing issue that requires immediate attention. As a new industrial development model, rural industrial convergence can provide new ideas and impetus for alleviating the urban–rural income inequality. This study, drawing on provincial panel data from China spanning 2010 to 2022, used the entropy method and Theil index to measure the rural industrial convergence and the urban–rural income inequality, respectively, and empirically tested the effect and mechanism of rural industrial convergence on the urban–rural income inequality. The results showed the following: (1) Rural industrial convergence had a notable impact on alleviating the urban–rural income inequality. (2) Rural industrial convergence could help reduce the urban–rural income inequality by increasing the scale of land operation. (3) The government attention to green development could positively moderate the impact of rural industrial convergence on the urban–rural income inequality; the deeper the government attention to green development, the greater the role rural industrial convergence played in alleviating the urban–rural income inequality. (4) There was a threshold effect in the alleviating effect of rural industrial convergence on the urban–rural income inequality, which was gradually strengthened when the growth of the digital economy and the enhancement of the business environment were beyond the threshold point. (5) Rural industrial convergence also had significant spatial spillover effects on adjacent regions. Overall, the findings of this study enrich the research on the impact of rural industrial convergence on the urban–rural income inequality and provide insights for other similar countries.

China’s Rural Multifunctional Community (RMC) construction is an effective means to achieve economic growth and environmental sustainability in agriculture. Therefore, we measure the agricultural green total factor productivity (AGTFP) in China considering carbon emissions and non-point source pollution and examine the impact of China’s pilot RMC policy on AGTFP using the difference-in-difference (DID) model based on panel data for 30 of China’s provincial-level regions during 2010–2020. Further, we analyze the regional heterogeneity and internal transmission channel. The main findings are as follows. First, the implementation of China’s pilot RMC policy significantly increases AGTFP. Second, the effects have a downward trend from eastern to western China which may be caused by the different levels in the economy, infrastructure, environmental resources, labor size and quality, transportation, innovation capability, etc. Finally, China’s pilot RMC policy can improve AGTFP through the channels of rural industrial convergence, agricultural green technology innovation and urban-rural income gap reduction. [ABSTRACT FROM AUTHOR]

The convergence of rural industries has brought about significant changes in the traditional small-scale farmer management model, as well as new requirements for the quality and skills of agricultural practitioners in China. Meanwhile, it has inevitably affected the agricultural environmental total factor productivity (AETFP). This paper endeavors to assess the impact of industrial convergence on AETFP, striving to clarify their inherent connection and furnish insightful guidance for policymaking. Utilizing inter-provincial panel data from China spanning 2008 to 2021, this paper applies the SBM-GML model for measurement purposes and employs the entropy method to evaluate the extent of industrial convergence in rural areas. It delves into the mechanism through which industrial convergence influences AETFP, utilizing the intermediary effect model and incorporating two mediating variables: rural human capital and agricultural scale operations. The findings of this research reveal that industrial convergence exerts a direct positive influence on AETFP, while rural human capital and agricultural scale operations serve as partial mediators in this process. Additionally, the stability of the transmission mechanism receives further validation via the application of interaction terms. Consequently, it is possible to enhance AETFP via the expedited convergent development of industries, coupled with the strategic utilization of rural human capital and agricultural scale operations as catalysts for further improvements in AETFP. [ABSTRACT FROM AUTHOR]

Farmers’ income growth is a significant social problem, which has a bearing on the building of a moderately prosperous society in an all-round way. The convergence of rural industries based on agricultural development has become a meaningful way to solve the problem. The convergence of rural industries cannot be separated from the construction of urbanisation because the aggregation of population resources and the optimisation of industrial structures need the support of urbanisation. Based on the panel data of 29 provinces in China from 2004 to 2020, this paper makes an empirical study on the interaction between rural industrial agglomeration, urbanisation level, and farmers’ income using the theories of “intermediate role” and “threshold effect.” The results show that rural industrial agglomeration significantly affects farmers’ economic development, among which the eastern, western, and central regions have the most substantial positive effect. The level of urbanisation development is the mediating variable of the impact of rural industrial convergence on farmers’ income growth, which indirectly promotes farmers’ income growth, and the mediating effect is significant. Lastly, the level of urbanisation development is the threshold variable for the impact of rural industrial convergence on farmers’ income growth, and the coefficient of rural industrial convergence on farmers’ income growth is highest when the level of urbanisation is between 0.7960 and 0.8500. Therefore, in order to achieve sustainable growth in farmers’ operating income, wage income and financial transfer income, the country should give full play to the advantages of rural industrial integration, build a modernised industrial system for agriculture, expand the functions of agriculture in the secondary and tertiary sectors, and make good use of the policies that benefit the people in rural industrial development. At the same time, with the opportunity of county urbanisation, a rural industrial development system with the county as the centre of development has been established, guiding the rational flow and effective integration of urban and rural industrial resource elements and realising the integrated development of urbanisation and rural industry. Given the differences in industrial development in the eastern, central and western regions, the State should also promote rural industrial integration policies by stage, region and strategy to raise the level of farmers’ income.

Coordination of rural industrial convergence and ecological environment is an important issue in rural social and economic development. This study aims to introduce a comprehensive evaluation index system and construct an integrated approach to evaluate and predict the coupling coordination between rural industrial convergence and ecological environment. Firstly, an index system including 40 indexes is developed for evaluating the two subsystems, and then entropy weight method is applied to determine the weights. Finally, a coupling coordination model and a grey prediction model are developed using provincial panel data from 2017 to 2021 for 29 provinces in China. There are three main findings: 1) penetration of new technologies and agricultural industrialization are the main driving factors of rural industrial convergence. In the three dimensions of ecological environment, environmental pressure has been the smallest contributor, implying that environmental pressure in rural China still needs attention in the next decade. 2) the coupling coordination between rural industrial convergence and ecological environment shows a fluctuating upward trend in China during the studied period and will continue to rise in the next 12 years. Among the 29 provinces studied, only 4 eastern developed provinces have reached primary coordination. The forecast data suggests that coordination with ecological environment will promote the development of rural industrial convergence. 3) the spatial differences of the coupling coordination are related to the level of economic and cultural development, application of agricultural technology, convergence of information technology, energy consumption structure and stock of natural resources. In conclusion, the research develops a rational index system and an effective approach to measure and predict the coupling coordination between rural industrial convergence and ecological environment, providing a theoretical basis for the environmental considerations in the rural industrial convergence policy-making.

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Copyright of Acta Agriculturae Zhejiangensis is the property of Acta Agriculturae Zhejiangensis Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)