摘要: |
[目的]为合理引导农户积极有序地退出农村宅基地,亟需开展不同模式下农村宅基地退出的农户选择偏好研究,准确把握不同类型农户的宅基地退出模式选择偏好及其影响因素,为研制出与不同类型农户相适应的宅基地退出管理策略提供参考。[方法]文章选取福建省晋江市作为典型案例研究区,采用问卷调查法和深度访谈法获取研究数据,基于多分类Logistic模型对不同模式下农村宅基地退出的农户选择偏好及其影响因素进行实证研究。[结果]农户选择货币补偿模式的正相关影响因素有家庭非农收入比重、宅基地与县镇距离和行为认知,负相关影响因素有年龄、受教育水平; 农户选择资产置换模式的正相关影响因素有家庭人口数和行为认知,负相关影响因素有宅基地与县镇距离; 农户选择指标置换模式的正相关影响因素有年龄、受教育水平、宅基地面积,负相关影响因素有家庭非农收入比重和行为认知。郊区非农业型农户适用于货币补偿模式,城中村非农业型农户适用于资产置换模式,郊区农业型农户适用于指标置换模式。[结论]不同模式下农村宅基地退出的农户选择偏好具有较大的差异。因此,在宅基地退出模式实施过程中,应采取差别化的政策措施来推动农户积极参与农村宅基地退出。在货币补偿模式下,应确保农户在城镇的保障性住房; 在资产置换模式下,应保障农户转变户籍后的福利水平; 在指标置换模式下,应提升农户的非农就业能力,尊重农户的退出意愿与诉求。 |
关键词: 农户选择偏好退出模式农村宅基地退出多分类Logistic模型影响因素 |
DOI: |
分类号:F3211 |
基金项目:教育部人文社会科学研究规划基金项目“乡村振兴进程中农村宅基地退出的模式选择及政策优化研究:基于农户行为视角”(19YJA630043); 国家自然科学基金项目“基于功能冲突权衡的乡村景观格局优化研究”(41401210); 2018年度福建省高校杰出青年科研人才培育计划项目 |
|
RESEARCH ON FAMERS′ SELECTION PREFERENCE AND INFLUENCING FACTORS OF RURAL RESIDENTIAL LAND WITHDRAWAL UNDER DIFFERENT PATTERNS*——EMPIRICAL ANALYSIS BASED ON JINJIANG CITY, FUJIAN PROVINCE |
Liang Fachao1,2, Liu Lihui1
|
1.School of Politics and Public Administration, Huaqiao University, Quanzhou 362021,Fujian,China;2.Political Development and Public Governance Research Center, Huaqiao University, Quanzhou 362021, Fujian,China
|
Abstract: |
To reasonably guide farmers to withdraw from rural residential land in an active and orderly way, it is necessary to study farmers′ selection preference of rural residential land withdrawal under different patterns. Accurately grasping the selection preferences of patterns and influencing factors of different types of farmers could provide reference for formulating the management strategy which is suitable for different types of farmers. Jinjiang city in Fujian province was selected as a typical case area, and the methods of questionnaires and in depth interviews were employed to obtain the research data. Based on the multiple Logistic model, we carried out an empirical analysis on farmers′ selection preference of rural residential land withdrawal under different patterns. The results showed that the positively related influencing factors for farmers′ selection of monetary compensation pattern included the proportion of household non agricultural income, the distance between rural residential land and county seat; and the negative related influencing factors included age and education level. The positively related influencing factors for farmers′ selection of asset replacement pattern included family population and behavioral cognition, and the negatively related influencing factors included the distance between homestead and county seat. The positively related influencing factors for farmers′ selection of index replacement pattern included age, education level, and the area of rural residential land; and the negatively related influencing factors included the proportion of household non agricultural income and behavioral cognition. The rural non agricultural farmers were suitable for monetary compensation pattern, the urban non agricultural farmers were suitable for asset replacement pattern, and the suburban agricultural farmers were suitable for index replacement pattern. There is a significant difference in the selection preference of rural residential land withdrawal under different patterns. Therefore, it is critical to take different kinds of policies and measures to promote farmers participate in rural residential land withdrawal actively in the process of implementation of the rural residential land withdrawal patterns. We should ensure the low income housing for farmers in cities and towns under the monetary compensation pattern of rural residential land withdrawal. The welfare level of farmers after changing the household registration should be guaranteed under the asset replacement pattern of rural residential land withdrawal. Under the index replacement pattern of rural residential land withdrawal, farmers′ off farm employment ability should be enhanced and their withdrawal wishes and demands should be respected. |
Key words: farmers′ selection preference withdrawal patterns rural residential land withdrawal multinomial Logistic model influencing factors |