玉米秸秆还田技术支付与受偿意愿差异性研究——以保定市徐水区农户调查为例

Disparity between willingness to pay/accept for corn straw counter-field technology: A case study of farmer survey in Xushui District of Baoding City

  • 摘要: 如何揭示秸秆还田技术实践中利益相关者生态补偿的真实意愿,不但是技术外部性测度研究的难点问题,也是提高农业补偿政策准确性与效能的有效途径。以往的研究较多地采用农田生态系统的生态服务价值量估算技术产生的外部性价值,由于未充分考虑环境利益双方量价关系的均衡,评估结果的准确性往往受到质疑。鉴于此,本研究首先厘清主体关系,农户是生产技术的实践者和环境保护参与者,理应成为技术进步的受益者。因而,技术外部性测度应充分尊重农民的意愿和利益。其次,确定研究方法。本研究采用国际通用的意愿价值评估法(CVM),引导获取河北省保定市徐水区502户受访者采纳秸秆还田技术的支付意愿(WTP)和受偿意愿(WTA);结合多元对数线性模型估计法,估算受访者应用秸秆还田技术主要机械成本(包括秸秆粉碎及旋耕费用)的最大WTP值和最小WTA值。结果表明:WTP的期望值为38.23元·户-1·a-1,WTA的期望值为137.52元·户-1·a-1,WTA/WTP的比值为3.6倍。本文进一步剖析WTP与WTA差异性原因,运用回归模型分析两者差异性影响因素,其中:机械成本对差异性有显著正向影响,已成为影响玉米秸秆还田推广的重要决定因素;劳动力比率、信息来源、灌溉成本和收割方式等4个因素与差异性均产生负向关联。可见,在大力推广玉米生产全程机械化进程中,机械成本上涨部分抵消了国家惠农政策补贴的效果,导致农户参与秸秆还田积极性并不高。因此,决策部门及时跟进技术价值评估工作,建立针对农户的直接补偿机制,是从根源上解决技术外部性内部化问题的有效途径。

     

    Abstract: How to reveal the real willingness of stakeholders for eco-compensation of technological practices has not only been a difficult research issue in measuring technological externalities, but also a key question in improving the accuracy and effectiveness of agricultural compensation policy. A number of studies have used ecological services value of farmland ecosystems to estimate the value of technological externality. The accuracy of the assessment results have been questioned on the basis of lacking adequate consideration of equilibrium of the relationship between participant parties. In view of this, this study first clarified the relationship between the main parties, where farmers were practitioners of production technology and environmental protection and therefore the beneficiaries of technological advancement. Therefore, the measure of technological externalities fully respected the wishes and interests of farmers. The second objective of the study was to determine research methods used in assessing the willingness of farmers. The paper used Contingent Valuation Method (CVM), which is a general intention value assessment used to determine the willingness to pay (WTP) and the willingness to accept (WTA), to determine the adoption of straw-return technology across 502 respondents. Then it estimated the maximum WTP and minimum WTA values of the mechanical costs (including:straw pulverization and rotational tillage) based on multivariate log-linear model estimation method. Based on the findings of the study, the expectancy values of WTP and WTA were respectively 38.23 ¥ and 137.52 ¥ per household per year for shredding and spinning costs of straw-return to the field, with WTA/WTP ratio of 3.6. The paper further analyzed the differences between WTP and WTA based on multiple logarithmic regression models and noted that the influencing factors of WTP and WTA asymmetry were labor force, information source, irrigation cost, mechanical cost and harvest mode. In addition, mechanical cost had a significant positive effect on the differences between WTA and WTP, while all other factors had a negative correlation. It was noted that on the one hand of the process of promoting whole-process mechanization of maize production, the increase in mechanical cost partially neutralized the beneficial effects of subsidies on farmers in the country. As a result, farmers had a low enthusiasm to return straw to the soil. On the other hand, since most corn farmers used to adopt traditional mode of production (including low labor and irrigation inputs, use of artificial harvesting and lack of information sources), the WTP of farmers for straw counter-field was also low. In fact, farmer households were even looking forward more to the government to speedily implement a reasonable subsidy policy. Thus, subsides were to be used by policy-makers to induce further adoption and reduce premiums costs on production practices. Empirical studies have confirmed that compensation standard of straw mulching technology in the northern arid area of China was 87.88 ¥ per household per year, which was reasonable and effective. In summary, the government should pay more attention on three issues in decision-making:1) establishment of a fair and effective compensation policy mechanism for farmers to work together and share the fruits of technological advancement; 2) strengthening of research on the methodology of technical-value assessment and establishment of a technical-value assessment based system for CVM and econometric models; 3) improvement of monitoring mechanism of promotion of agricultural technology and setting up information resource sharing platforms.

     

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