环境规制下养殖户的环境投入行为研究*——基于双栏模型的实证分析

THE RESEARCH OF FARMERS′ ENVIRONMENTAL INVESTMENT UNDER ENVIRONMENTAL REGULATION*——EMPIRICAL ANALYSIS BASED ON THE DOUBLE COLUMN MODEL

关键词:  环境规制风险认知双栏模型TPB理论MOA模型

Key words:  environmental regulation  risk perception  double column model  TPB theory  MOA model

摘要:

［目的］畜禽养殖业的快速发展导致了环境负外部性扩大，畜禽养殖污染问题推动了环境规制政策体系的完善； 日趋严厉的环境规制下，养殖户的环境投入行为对畜禽养殖的环境治理具有重要意义。［方法］文章在归纳和完善了TPB理论及MOA模型的基础上，运用江苏、河北、山东3省的401个蛋鸡养殖户的整周期生产数据，采用双栏模型从环境投入意愿及投入程度两阶段，实证分析了环境规制下养殖户的风险认知及环境投入能力对其环境投入的影响程度及差异。［结果］实证结果表明，规制强度、养殖户的环境污染认知和投入能力对环境投入行为有显著的正向促进作用，但规制成本认知对环境投入行为呈现出倒“U”型的影响。［结论］政府应加强对养殖户环境风险认知的塑造，制定出差异化的规制政策，提升规制政策的监管效率，积极促进养殖户的环评申报工作。政府还应发展多维度粪污处理合作模式，降低养殖户的环境投入风险和成本。

Abstract:

The environmental pollution has been increasing with the development of livestock and poultry farming, which promotes environmental regulation improving constantly; with the more and more rigorous environmental regulation, farms′ investment behaviors have great significance on environmental governance. In this research, based on the induction and improvement of TPB theory and MOA models, production data from 401 layer farmers in Jiangsu, Hebei and Shandong had been empirically analyzed from intention and degree of environmental investment by double column model, which could find how farmers′ risk cognition and investment ability affected on their investment intention under environmental regulation. The research showed that the improvement of regulation, farms′ cognition in environmental contamination and investment ability could increase farmer′s investment intention significantly. However, the cognition of regulation cost affecting on the behavior of environmental investment showed a U shaped tendency. Accordingly, government should improve the education of farmers′ risk cognition, establish differentiated policies to improve the supervision efficacy in regulation and promote farmers to apply environmental assessment. In addition, government should also develop various cooperative modes in manure treatment to decrease farms′ risk and cost in environmental investment.