Wang Li, Li Nan, Xie Qian
School of Economics & Management, Northwest University, Xi'an 710127, China.
Heliyon. 2024 Feb 28;10(5):e27248. doi: 10.1016/j.heliyon.2024.e27248. eCollection 2024 Mar 15.
Green development of agriculture and rural areas (GDARA) is an essential part of rural revitalization and high-quality development. Based on 2011 to 2020 provincial panel data from China, the entropy-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model is constructed to measure the level of GDARA, finding that the overall level during the sample period was positive. Then the regional differences mainly from intra-regional were revealed by the methods of Dagum Gini coefficient and Kernel density estimation and were shrinking overall. Besides, the results of Markov chain transfer matrix show the dynamic characteristics clearly, which the low-level regions shift to the middle and high levels with a greater probability. The results of the spatial autocorrelation test display that GDARA has a spatial clustering effect. Finally, the industrial upgrading and the business income of leisure agriculture are respectively proven to hinder GDARA at most by the Obstacle degree model empirically. Based on a series of empirical tests, a few relevant policy recommendations are proposed to promote the road to strong agriculture and rural areas in China.
农业农村绿色发展是乡村振兴和高质量发展的重要组成部分。基于2011—2020年中国省级面板数据，构建基于熵值法的逼近理想解排序法（TOPSIS）模型来测度农业农村绿色发展水平，发现样本期内整体水平呈正向态势。然后运用达格姆基尼系数法和核密度估计法揭示了主要源于区域内部的地区差异，且整体差异呈缩小趋势。此外，马尔可夫链转移矩阵结果清晰地显示出动态特征，即低水平地区向中高水平转移的概率更大。空间自相关检验结果表明农业农村绿色发展具有空间集聚效应。最后，通过障碍度模型实证证明产业升级和休闲农业经营收入对农业农村绿色发展的阻碍作用最大。基于一系列实证检验，提出了一些相关政策建议，以推动中国农业农村现代化之路。
