随着非线性定价在公用事业中的广泛使用,对其参数的政策评估与优化设计成为学术界与政策界均关心的重要问题。本文以我国正在实施的居民递增阶梯电价为例,利用2010—2016年CFPS数据,在识别居民所响应电价类型的基础上,通过门槛模型及Stone-Geary函数对居民递增阶梯电价政策的数量参数进行优化设计。主要研究结论为:(1)由于非线性定价参数的复杂性,价格参数会影响数量参数特征,有限理性的居民用户普遍仅对平均价格响应,数量参数设定时需要考虑用户对复杂定价的认知行为特征;(2)当前全国各省份居民电价参数中的阶梯长度参数偏大,为有效识别用户的差异化特征,需要适当缩短阶梯长度;(3)与现行全国各省份的阶梯数量均为“一刀切”式的3个阶梯不同,各省份的最优阶梯数量存在差异,为2~3个,政策部门需根据本地用户实际情况进行阶梯数量设置。本文为系统评估和优化调整各省份公用事业非线性定价政策提供了理论支持和现实参考。
Abstract
Nonlinear pricing has many advantages and can be very helpful if the government uses it correctly.We use the CFPS data form 2010 to 2016 to evaluate and optimize the increasing block pricing(IBP)policy in China.Firstly,we identify which type of electricity price that the residents respond to.Then we optimize the quantitative parameters of the IBP policy through threshold model and Stone-Geary function.It is shown that the limited rational residents generally only respond to average price since the parameter complexity of nonlinear pricing and the cross effect of quantitative parameters and price parameters.The cognitive behavior characteristics of the users for complex pricing should be considered when the quantitative parameters are set; the block length parameters in china are currently too large,we need to cut down the block length appropriately so that we can effectively identify the differentiation characteristics of users;it is not a good choice for the government to set a unified 3 blocks in every province since they have many differences,government could set the number of blocks 2 or 3 according to their differences.This paper provides theoretical support and practical reference for the system to evaluate and optimize the nonlinear pricing policy of public utilities in various provinces.
关键词
非线性定价 /
数量参数 /
平均价格 /
阶梯长度 /
阶梯数量
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Key words
IBP /
Quantitative parameter /
Average price /
Block length /
Number of blocks
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中图分类号：
F062.9
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参考文献
[1] 吴建宏.基于社会均衡的居民阶梯电价定价模型及政策模拟研究[D].北京:华北电力大学,2013.
[2] 张昕竹,田露露,马源.居民对递增阶梯电价更敏感吗——基于加总DCC模型的分析[J].经济学动态,2016(2):17-30.
[3] Zhang Z,Cai W,Feng X.How Do Urban Households in China Respond to Increasing Block Pricing in Electricity？Evidence from a Fuzzy Regression Discontinuity Approach[J].Energy Policy,2017,105:161-172.
[4] Li L,Yao Y,Yang R.Is It More Effective to Bring Time-of-use Pricing into Increasing Block Tariffs？Evidence from Evaluation of Residential Electricity Price Policy in Anhui Province[J].Journal of Cleaner Production,2018,181:703-716.
[5] 刘树杰.价格监管的目标、原则与基本方法[J].经济纵横,2013(9):1-4.
[6] Ma X,Zhang S,Mu Q.How Do Residents Respond to Price under Increasing Block Tariffs？Evidence from Experiments in Urban Residential Water Demand in Beijing[J].Water Resources Management,2014,28(14):4895-4909.
[7] 林伯强,蒋竺均,林静.有目标的电价补贴有助于能源公平和效率[J].金融研究,2009(11):1-18.
[8] Barclay M J,Holderness C G,Sheehan D P.The Block Pricing Puzzle[R].Simon School of Business Working Paper,No.FR,2001:1-5.
[9] 冯永晟.非线性定价组合与电力需求——基于中国居民微观数据的实证研究[J].中国工业经济,2014(2):45-57.
[10] Ito K.Do Consumers Respond to Marginal or Average Price？Evidence from Nonlinear Electricity Pricing[J].Social Science Electronic Publishing,2012,104(2):537-63.
[11] Hanemann J A H M.A Discrete/Continuous Choice Approach to Residential Water Demand under Block Rate Pricing[J].Land Economics,1995,71(2):173-192.
[12] Monteiro H,Catarina R P.Pricing for Scarcity？An Efficiency Analysis of Increasing Block Tariffs[J].Water Resources Research,2011,47(6):6510.
[13] Clarke A J,Colby B G,Thompson G D.Household Water Demand Seasonal Elasticities:A Stone-Geary Model under an Increasing Block Rate Structure[J].Land Economics,2017,93(4):608-630.
[14] Fotros M H,Yari H,Maboudi R.The Impact of Increasing Block Pricing on the Residential Water Consumption in Iranian Provinces[J].Photosynthesis Research,2013,63(1):1-8.
[15] 张昕竹,田露露.阶梯电价实施及结构设计——基于跨国数据的经验分析[J].财经问题研究,2014(7):23-29.
[16] 朱柯丁,宋艺航,谭忠富,吴海林.居民生活阶梯电价设计优化模型[J].华东电力,2011,39(6):862-867.
[17] 梁慧芳,曹静.中国城镇居民用电需求估算及阶梯电价方案设计[J].技术经济,2015,34(6):85-94,127.
[18] 刘自敏,杨丹,冯永晟.递增阶梯定价政策评价与优化设计——基于充分统计量方法[J].经济研究,2017,52(3):181-194.
[19] 黄海涛,张粒子,乔慧婷,杜宁.基于变密度聚类的居民阶梯分段电量制定方法[J].电网技术,2010,34(11):111-116.
[20] 刘自敏,张昕竹,杨丹.纯分时定价与分时阶梯定价对政策目标实现的对比分析[J].数量经济技术经济研究,2015,32(6):120-134.
[21] 张昕竹,刘自敏.分时与阶梯混合定价下的居民电力需求——基于DCC模型的分析[J].经济研究,2015,50(3):146-158.
[22] 李成仁,余嘉明.日韩居民阶梯电价经验与启示[J].能源技术经济,2010,22(7):56-61.
[23] Hung M F,Huang T H.Dynamic Demand for Residential Electricity in Taiwan under Seasonality and Increasing-block Pricing[J].Energy Economics,2015,48:168-177.
[24] 刘满平.天然气价格形成机制该如何改革[J].中国石化,2018(5):50-52.
[25] 杨娟,刘树杰.有关“降电价”的看法和建议[J].价格理论与实践,2018(1):15-17.
[26] Meran G,Hirschhausen C V.Increasing Block Tariffs in the Water Sector:A Semi-Welfarist Approach[J].Discussion Papers of DIW Berlin,2009(902).
[27] Schoengold K,Zilberman D.The Economics of Tiered Pricing and Cost Functions:Are Equity,Cost Recovery,and Economic Efficiency Compatible goals？[J].Water Resources and Economics,2014,7:1-18.
[28] 谭真勇.负荷率电价的理论依据、计算方法与政策选择[D].长沙:湖南大学,2013.
[29] Hansen B E.Threshold Effects in Non-dynamic Panels:Estimation,Teshing,and Inference[J].Journal of Econometrics,1999,93(2):345-368.
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基金
国家自然科学基金青年项目“递增阶梯定价的政策评估与优化设计研究”(项目编号:71603218);2017年重庆市社科规划“研究阐释党的十九大精神”项目“重庆市构建现代农业产业体系、生产体系、经营体系研究”;西南大学中央高校基本科研重大项目“交叉补贴视角下的中国能源价格机制设计”(项目编号:SWU1809022);西南大学中央基本高校科研项目“我国农业经济发展中的重大理论与现实问题研究”(项目编号:SWU1709115)。
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