我国农村水环境污染日益严重，准确地度量各类农村水环境治理措施的减排效果对于后续政策制定具有重要的参考价值。由于农村水环境污染物监测数据偏少，且存在非平稳性特征，传统方法难以有效度量各类政策作用效果。为此，本文采用多变量离散灰色模型构建减排量测度方法并进行实证研究。首先，梳理了1995年以来我国颁布的农村水环境管理政策，根据政策内容和目标进行归类并选择代表性政策；然后，采用单元调查评估法核算农村各类水污染物排放量；进而将各类政策作为虚拟驱动项引入多变量灰色模型，并采用竞争性模型策略设定一系列减排测度模型，通过适配结果选择最优模型从而度量各类水环境政策的减排效应。研究结果表明，（1）我国农村水环境管理政策总体上具有较好的减排效果，COD、TN、TP三类污染物的年均减排量分别为54.25、66.08和12.9万吨。（2）三类政策减排效应存在一定差异性，"产业与经济型"政策群的减排效应低于"命令控制型"和"自愿参与型"政策。（3）省际层面的政策减排效应存在一定的空间聚集特征。最后，提出了我国农村水环境管理的对策建议。本研究为数据匮乏条件下的政策效应测度提供了借鉴和参考。
With the growing pollution of rural water environment in China, accurate emission reduction measurement of rural water environment management is significant for the subsequent policies. It is difficult to effectively measure the effects of different kinds of policies due to the relatively small amount of data as well as its non-stability characteristics. Therefore, a multivariate discrete grey model is introduced to measure the emission reduction effect and then an empirical research is conducted. Firstly, the policies related to rural water environment management since 1995 are sorted out, and then they are classified into different groups and some representative policies are selected respectively according to the contents and targets. Secondly, the amount of different kinds of water pollutants emission is computed using the unit investigation and evaluation method. Furthermore, different groups of policies are introduced as virtual driven variables into the model, and competitive models strategy is adopted by setting a series of emission reduction measuring models. By comparing the adaptability among those models, the most adaptive model is selected to measure the emission reduction effect of different policy groups respectively. The research results show that rural water environment management policies are effective in general. Meanwhile, there exists certain difference about the emission reduction effect among three groups of policies. Moreover, the effect displays a spatial-clustering feature at province level. Lastly, some countermeasures are proposed to improve the management of rural water environment in China. It is hoped that the study will provide some reference for measurement of policy effectwith insufficient data.
[1] Abler D. Economic evaluation of agricultural pollution control options for China[J]. Journal of Integrative Agriculture, 2015,14(6):1045-1056.
[2] Picazo-Tadeo A J, Gómez-Limón J A, Reig-Martínez E. Assessing farming eco-efficiency:A data envelopment analysis approach[J]. Journal of Environmental Management, 2011,92(4):1154-1164.
[3] Ruttan V W. Productivity growth in world agriculture:Sources and constraints[J]. Journal of Economic Perspectives, 2002,16(4):161-184.
[4] Nanere M, Fraser I, Quazi A, et al. Environmentally adjusted productivity measurement:An Australian case study[J]. Journal of Environmental Management, 2007,85(2):350-362.
[5] 李谷成. 中国农业的绿色生产率革命:1978-2008年[J]. 经济学(季刊), 2014,13(2):537-558.
[6] 梁流涛, 曲福田, 冯淑怡. 基于环境污染约束视角的农业技术效率测度[J]. 自然资源学报, 2012,27(9):1580-1589.
[7] 杜江. 中国农业增长的环境绩效研究[J]. 数量经济技术经济研究, 2014,31(11):53-69.
[8] Shao Weiyun. Effectiveness of water protection policy in China:A case study of Jiaxing[J]. Science of The Total Environment, 2010,408(4):690-701.
[9] Deunert F, Lennartz B, Tiemeyer B. Legislative effects on the development of surface water quality in rural areas in Northern Germany[J]. Journal of Cleaner Production, 2007,15(16):1507-1513.
[10] Semaan J, Flichman G, Scardigno A, et al. Analysis of nitrate pollution control policies in the irrigated agriculture of Apulia Region (Southern Italy):A bio-economic modelling approach[J]. Agricultural Systems, 2007,94(2):357-367.
[11] 梁流涛, 曲福田, 冯淑怡. 基于环境污染约束视角的农业技术效率测度[J]. 自然资源学报, 2012,27(9):1580-1589.
[12] 刘鸿渊, 闫泓. 农业面源污染形成机理的实证研究——以四川省1982~2006年统计数据为例[J]. 农村经济, 2010,21(5):98-101.
[13] 葛继红. 江苏省农业面源污染及治理的经济学研究[D]. 南京:南京农业大学, 2011.
[14] 陈敏鹏, 陈吉宁, 赖斯芸. 中国农业和农村污染的清单分析与空间特征识别[J]. 中国环境科学, 2006,26(6):751-755.
[15] 赖斯芸, 杜鹏飞, 陈吉宁. 基于单元分析的非点源污染调查评估方法[J]. 清华大学学报:自然科学版, 2004,44(9):1184-1187.
[16] 朱建军, 刘思峰, 张里, 等. 基于灰色组合预测的节能政策能源节约量测算模型[J]. 软科学, 2009,23(5):42-45.
[17] 花玲, 谢乃明. 政策冲击影响下中国能源消费预测分析及控制策略[J]. 中国管理科学, 2014,22(7):87-95.
[18] 李太平, 张锋, 胡浩. 中国化肥面源污染EKC验证及其驱动因素[J]. 中国人口.资源与环境, 2011,21(11):118-123.
[19] 沈能, 周晶晶, 王群伟. 考虑技术差距的中国农业环境技术效率库兹涅茨曲线再估计:地理空间的视角[J]. 中国农村经济, 2013(12):72-83.
[20] 梁流涛, 冯淑怡, 曲福田. 农业面源污染形成机制:理论与实证[J]. 中国人口·资源与环境, 2010,20(4):74-80.
[21] 金书秦, 沈贵银. 中国农业面源污染的困境摆脱与绿色转型[J]. 改革, 2013,23(5):79-87.
[22] Schader C, Lampkin N, Muller A, et al. The role of multi-target policy instruments in agri-environmental policy mixes[J]. Journal of Environmental Management, 2014,145(2):180-190.
[23] 龙冬平, 李同昇, 苗园园, 等. 中国农业现代化发展水平空间分异及类型[J]. 地理学报, 2014,69(2):213-226.
[24] 吴玉鸣. 中国区域农业生产要素的投入产出弹性测算——基于空间计量经济模型的实证[J]. 中国农村经济, 2010,(6):25-37.
[25] 赵良仕, 孙才志, 郑德凤. 中国省际水资源利用效率与空间溢出效应测度[J]. 地理学报, 2014,69(1):121-133.
[26] 孙才志, 赵良仕, 邹玮. 中国省际水资源全局环境技术效率测度及其空间效应研究[J]. 自然资源学报, 2014,29(4):553-563.
[27] 王新成, 王斌之, 黄建毅. 基于空间自相关的水污染空间聚类研究[J]. 环境工程技术学报, 2014,4(4):293-298.
[28] 梁流涛. 农村生态环境时空特征及其演变规律研究[D]. 南京:南京农业大学, 2009.
[29] Song Malin, Zhang Wei, Wang Shuhong. Inflection point of environmental Kuznets curve in Mainland China[J]. Energy Policy, 2013,57:14-20.
