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草原生态补奖政策满意度影响因素的meta分析 被引量:9

Factors Affecting Herders’ Satisfaction of Grassland Eco-Compensation and Awarding Policy Implementation:A Meta-analysis
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摘要 基于13篇关于草原生态补奖政策满意度研究文献的3074个样本量,运用meta分析法研究了我国牧民对草原生态补奖政策满意度的影响因素,并且分析了影响因素的异质性及其来源。结果表明,牧民的年龄、受教育程度、家庭人口数量、家庭补贴收入、家庭牧业收入、牲畜量、饲草料支出、补偿金发放及时程度、草地退化程度及牧民对补偿金发放标准的满意程度均对补奖政策的满意度存在显著正向影响,而牧民性别不存在显著影响;各变量并不存在发表偏倚;家庭人口数量、补贴收入和牧民对补偿金发放标准的满意程度存在较显著的异质性;进一步的分析发现异质性的来源是变量的测量方式和地区差异等因素。 Based on 3074 sample sizes of 13 papers on the satisfaction of the Grassland Ecological Compensation and Awarding Policy,the meta-analysis method was employed to study the factors affecting of herders’ satisfaction with the Grassland Ecological Compensation and Awarding Policy,and the heterogeneity and sources of influencing factors were analyzed.The results showed that herdsmen’s age,education level,family population,family subsidy income,family animal husbandry income,livestock quantity,forage expenditure,timely payment of compensation,grassland degradation and herdsmen’s satisfaction with the standard of compensation payment were significantly positively correlated with their satisfaction with compensation policy.However,herdsmen’s gender had no significant impact.There was no publication bias was in each variable;there was significant heterogeneity in the number of family populations,subsidy income,and herdsmen’s satisfaction of compensation criteria.Further analysis showed that the source of heterogeneity was the measurement of variables and regional differences.
作者 关士琪 张岩 王变变 李丽华 GUAN Shi-qi;ZHANG Yan;WANG Bian-bian;LI Li-hua(State Key Laboratory of Grassland Agro-ecosystems/Key Laboratory Forage and Livestock Industry Innovation of Ministry of Agriculture/College of Pastoral Agriculture Science and Technology,Lanzhou University,Lanzhou 730020,China)
出处 《中国草地学报》 CSCD 北大核心 2019年第5期134-143,共10页 Chinese Journal of Grassland
基金 中国工程院院士咨询项目“中国草业发展战略研究”(055000031) 中央高校基本科研业务费专项资金(lzujbky-2018-1)
关键词 草原生态补奖政策 满意度 影响因素 META分析 Grassland ecological compensation and awarding policy Satisfaction Influential factors Meta-analysis
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