摘要
论文介绍了GMM方法原理,应用GMM估计方法对城市水价预测长期边际成本数学模型的参数估计进行了研究,通过用水人数、用水量、用水结构、可变成本及固定成本等水价相关因子的参数估计,实现水价长期边际成本的预测,并以苏州市为实例进行了案例研究。研究结果表明:应用GMM的样本估计解决了长期边际成本数学模型需求数据量较大的要求,提高了水价长期边际成本预测模型的实用性。
This paper described the principle of GMM Methods and studied the parameter estimation of urban water price forecasting mathematical model on long-term marginal cost using the GMM estimation methods. By the parameter estimation for water user number, water consumption, water structure, water supply variable costs and water supply fixed costs, it aims to achieve the long-term marginal cost forecasting of water price by taking Suzhou City as a case. The results showed that by application of GMM sample estimation, the demand of a large amount of data required for mathematical model was resolved and the long-term marginal cost of water price forecasting model＇ s practicality was improved.
出处
《自然资源学报》
CSSCI
CSCD
北大核心
2010年第9期1589-1595,共7页
Journal of Natural Resources
基金
国家自然科学基金创新研究群体项目(50721006)
住房与城乡建设部科学技术项目“城市供水边际成本定价模型与应用关键技术研究”(2010-K7-3)
江苏省环境科学与工程重点实验室开放课题(Zd081204)
江苏省高校自然科学基金(08KJD610008)阶段性成果
