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Regional differential decomposition and convergence of rural green development efficiency: evidence from China

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Abstract

An objective understanding of the current situation and influencing factors of rural green development in China is an important prerequisite for effective formulation making of green development policies. Based on the panel data of 31 provinces of China from the year 1997 to 2017, this paper constructs and measures the rural green development efficiency (RGDE) based on Driving-Force, Pressure, State, Influence, Response (DPSIR) model and super-efficiency slacks-based measure (SBM) model. The results show that, the overall RGDE in China is fluctuating and rising from 1997 to 2017, and there are some differences between and within regions. The RGDE in developed areas is higher than that in developing areas, and coastal areas are higher than that in inland areas. The entire country, eastern, central, and western regions show σ convergence, which indicates that the RGDE is getting better, but there is no absolute β convergence, that means there is no “catch-up effect” between regions, but the gradient divergence showed central > eastern > western. At the same time, there is no conditional β convergence; the initial RGDE has a positive impact on the growth rate of RGDE, and the financial self-sufficiency rate promotes the growth of RGDE of the whole country and the western region, but inhibits the improvement of RGDE of the eastern region. The per capita GDP, mechanization degree, and agricultural industrial structure in rural areas did not promote the growth of RGDE. Based on the results, this paper puts forward some policy suggestions, such as promoting the classified implementation of rural green development policies, strengthening the top-level design, optimizing the existing agricultural mechanism and system, and guiding and standardizing the farmers’ green production behavior.

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Notes

  1. Data sources: According to the statistical yearbook of China 2018, the absolute value of agricultural output value from 1978 to 2017 was calculated.

  2. Data sources: http://www.chinanews.com/gn/2016 /06–19/7909149.shtm.

  3. Club convergence means that the initial level and the region with similar structure will converge to the same steady state level over time.

  4. Data sources: https://baike.so.com/doc/1279856-1353305. Html#23635518–24,188,839-2.

  5. Based on the availability of data, this paper takes the annual deposit interest rate published by the People’s Bank of China as the discount rate instead of the inflation rate.

  6. Ministry of Ecological Environment: “The Belt and Road ‘International Cooperation Summit Forum Green Development Road’, April 26, 2019”.

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Acknowledgments

This study is supported by the Major Project of the National Social Science Foundation of China (No. 15ZDA052), National Soft Science Project of State Forestry and Grassland Administration (No. 2019131039), and Major Research Project of County Economy in Shaanxi Province (No.2019XY012).

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Authors and Affiliations

  1. College of Economics and Management, Northwest A&F University, Yangling, 712100, China

    Cui Yu, Liu Wenxin, Sufyan Ullah Khan, Cai Yu, Zhu Jun, Deng Yue & Minjuan Zhao

  2. Institute of Soil and Water Conservation, Northwest A&F University, Yangling, 712100, Shaanxi, China

    Sufyan Ullah Khan

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  1. Cui Yu
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  2. Liu Wenxin
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Correspondence to Minjuan Zhao.

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Yu, C., Wenxin, L., Khan, S.U. et al. Regional differential decomposition and convergence of rural green development efficiency: evidence from China. Environ Sci Pollut Res 27, 22364–22379 (2020). https://doi.org/10.1007/s11356-020-08805-1

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