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草业学报 ›› 2020, Vol. 29 ›› Issue (4): 63-72.DOI: 10.11686/cyxb2019328

• 研究论文 • 上一篇    下一篇

草原补奖政策对牧户牧业生产决策行为的影响研究

高雅灵, 林慧龙*, 马海丽, 吴廷美   

  1. 兰州大学草地农业生态系统国家重点实验室,兰州大学农业农村部草牧业创新重点实验室,兰州大学中国草业发展战略研究中心,兰州大学草地农业科技学院,甘肃 兰州 730020
  • 收稿日期:2019-07-17 修回日期:2019-09-29 出版日期:2020-04-20 发布日期:2020-04-20
  • 通讯作者: E-mail: linhuilong@lzu.edu.cn
  • 作者简介:高雅灵(1994-),女,甘肃平凉人,在读硕士。E-mail: gaoyl16@lzu.edu.cn
  • 基金资助:
    国家科学自然基金项目(71773003),中国工程院重点咨询项目(纵20180093),中央高校基本科研业务费专项资金(lzujbky-2019-kb28,lzujbky-2020-kb29)和国家林业和草原局软科学项目(2019131021)资助

A study of factors affecting decision-making behaviour of pastoral farmers’ animal husbandry production under the grassland ecological reward policy

GAO Ya-ling, LIN Hui-long*, MA Hai-li, WU Ting-mei   

  1. State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Forage and Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Chinese Center for Strategic Research of Grassland Agriculture Development, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
  • Received:2019-07-17 Revised:2019-09-29 Online:2020-04-20 Published:2020-04-20
  • Contact: E-mail: linhuilong@lzu.edu.cn

摘要: 我国实施草原生态保护补助奖励政策已历经7年,实证分析该政策对牧户牧业决策行为的影响,对于完善第二期补奖政策和牧户生产决策行为的深入研究具有积极意义。研究基于草原补奖政策实施前后甘肃省牧区及半农半牧区7个县220户牧户的调查,运用Logistic模型和负二项回归模型分析了草原生态补奖政策对牧户生产决策行为的影响。结果表明:草原补奖政策对牧户的生产决策行为总体上产生了显著正向影响,但对半农半牧区牧户牧业生产决策行为的影响高于牧区;草原补奖政策并不是影响牧户生产决策行为的唯一因素,除补奖政策外,牧户生产决策行为影响因素具有非对称性。从前期牧户扩大牧业生产规模的可能性来看,牧区主要受家庭特征因素的影响,而半农半牧区主要受外部环境因素的影响。从后期牧户扩大多少牧业生产规模来看,牧区牧户关注更多的是资金、牧业生产的风险保障和饲草储备,而半农半牧区牧户则侧重于收入来源、市场行情和饲草储备。最后建议重视荒漠化草原类型,综合牧户家庭特征,实施差异化补贴;切合牧户需求,提高牧户主体决策水平,实现牧业生产效益最大化。

关键词: 草原生态补奖政策, 生产决策行为, Logistic模型, 负二项回归模型

Abstract: It has been seven years since China implemented the policy of grant and reward for grassland ecological protection. Empirical analysis and in depth study of the policy’s impact on herdsmen’s decision-making behavior pertaining to production from their farms, is of positive value to inform the implementation of the second stage of the policy. This paper is based on a survey of 220 herdsmen in seven counties including pastoral areas and semi-agricultural and semi-pastoral areas in Gansu Province before and after the implementation of the eco-compensation policy. A logistic model and negative binomial regression model are used to analyze the impact of the grassland eco-compensation policy on herdsmen’s production decision-making behavior. It was found that the policy of grassland reward has a significant positive impact on the production decision-making behavior of herdsmen in general, but the impact on the production decision-making behavior of herdsmen in semi-agricultural and semi-pastoral areas is higher than that in pastoral areas. The policy of grassland reward is not the sole factor affecting the production decision-making behavior of herdsmen. Besides the policy of reward, the other factors affecting the production decision-making behavior of herdsmen in pastoral areas are different from semi-agricultural and semi-pastoral areas. The analysis showed decision-making in the pastoral areas is mainly affected by the family situation, while in the semi-agricultural and semi-pastoral areas decision-making is mainly affected by external environmental factors. With respect to the scale of animal production and decisions about future expansion, herdsmen in pastoral areas pay more attention to availability of capital, the risk profile of the animal production system, and forage reserves, while herdsmen in semi-agricultural and semi-pastoral areas focus on income sources, market returns and forage reserves. Based on the data from this study, it is suggested that attention should focus on grassland types prone to desertification, comprehensive understanding of herdsmen’s family situations. Differential subsidies should be implemented, and targeted to meet herdsmen’s needs, positively direct the decision-making of herdsmen and maximize the wider benefits of the animal production industry.

Key words: grassland ecological reward policy, production decision-making behaviour, logistic model, negative binomial regression model