基于主成分Logistic模型的退耕还林工程农户参与意愿分析——以四川省雅安市为例

分析新一轮退耕还林工程四川省农户参与意愿的影响因素,可为优化实施政策提供参考。以参与意愿为因变量,以工程项目政策、农户自身条件和区位影响等3类因子指标为自变量,构建了造林营林和林下种养两类项目农户参与意愿的Logistic模型,并设计了主成分回归的求解方法。以四川省雅安市为抽样区,调查获得了246个农户的意愿问卷,分析结果表明:主成分Logistic模型拟合精度较高、回归系数符合参与意愿的影响逻辑判断;影响农户参与造林营林项目意愿的因子有户主年龄B1和产品产生周期长短A7综合的主成分因子H11、启动资金保障A4,反映了农户对该类项目回报周期过长、初期资金不足等问题的担忧;影响农户参与林下种养项目意愿的因子为家庭劳力规模B3、项目区的区位C2,反映出该类项目受家庭劳动力不足、因地区远而产品经济难实现的制约影响。本文针对上述问题给出了提高农户参与积极性的政策建议。将先验分析和回归分析有机结合的主成分Logistic建模克服了纯数理统计方法的局限性,研究区具有地域代表性,可为类似地区退耕还林工程实施提供借鉴。

Farmers' Willingness to Participate in the Grain for Green Project Based on Principal Component Logistic Model:A Case Study of Ya'an

This paper aims to analyze the influencing factors of farmers` willingness to participate in the new round of Grain for Green Project in Sichuan province for policies decision-making.To reflect the relationships between participation willingness of farmer and the factors of project policies,the farmer`s own conditions and regional conditions,two logistic functions for afforestation and under-forest industries were built and designed to be solved by Principal Component Regression Analysis.Taking Ya`an as a study area,the authors have surveyed related sampling data of 246 farmers by questionnaires and the analysis results illustrate that the two principal component logistic models have high precision with logical regression coefficients;for afforestation project M1,a principal component factor H11 of householder age B1 and production cycle A7 and startup financial support policy A4 show negative impacts on participating willingness of farmers,which reveals the concern of farmers on investment return risk from longtime production cycle and lack of startup capital;for under-forest project M2,two negative factors of household labor force B3 and geographical location of project C2 show that participating willingness of farmers were conditioned by the lack of household labor force and the difficulty of realizing products benefits caused by geographical remoteness.To boost farmers` motivation,the authors put forward corresponding policy suggestions aiming at the above issues.The method combing transcendental analytic and principal component regression analysis can avoid the limitation of using mathematical statistics only and Ya`an is geographically representative in Sichuan province.So the research in this paper can provide reference for Grain for Green Projects implemented in other similar areas.