摘要
基于农户退耕还林意愿影响因素的理论分析,采用2012年农户调查数据,运用Binary Logistic回归模型进行了实证研究。研究发现:在政府强制推动的背景下,参与方式与参与程度、政策认知及政策执行力度是影响农户退耕还林意愿的主导因素,退耕还林净效用、家庭禀赋的作用弱化。其中:①政府强制参与将导致农户抵制;被征求过意见、了解补偿政策、知道退耕还林目的和按时收到补偿款的农户,退耕还林意愿强。②土地机会成本对农户退耕还林意愿几乎没有影响,但土地机会成本上升、造林营林成本高,削弱了农户退耕还林意愿,同时劳动力机会成本上升的负向作用不容忽视。③林木及林地产权收益的正向作用显著,经济补偿、林业收益、结构调整收益的影响未能得到证实。④以种植业为家庭主要收入来源的农户退耕还林意愿弱。
Based on theoretical research of factors influencing farmers' willingness to participate in Grain for Green Pro- ject,using data from household survey in2012 an empirical analysis was carried out with the method of binary logistic re- gression. The results show: on the context of government enforcement, instead of the net utility of the project and house- hold endowment the primary influencing factors are farmers participated in the project was voluntary or not,their percep- tion of related policies and on what level the policies was implemented. Among these ,①those farmers who were consul- ted by the forestry sector before the implementation of the project ,understood the policies ,knew the purpose of the pro- gram,were motivated by compensation and received compensation on time have strong willingness to participate in the grain for green project. ②The opportunity cost of land hardly exert any effect on farmers' willingness in participation, however, increasing opportunity cost of land as well as high costs of afforestation undermine farmers' willingness. Besides,the negative effect of opportunity cost of labor cannot be ignored. ③Non-monetary gains such as giving farmers the ownership of trees, extend the term of land use right etc have a positive influence on farmers' willing- ness. The effects of compensation,revenues of conversion land and the benefits farmers' can gain from production re- structure was failed to be confirmed. ④ Households relying on plantation for their living were reluctant to participate the project.
出处
《经济地理》
CSSCI
北大核心
2014年第2期131-138,共8页
Economic Geography
基金
国家社会科学基金项目(2010YBJJ11)
重庆社会科学规划项目(10BJY025)
关键词
农户
退耕还林意愿
影响因素
BINARY
LOGISTIC模型
farmers
willingness to participate in grain-for-green project
influencing factors
binary logistic model