摘要
本文利用中国30个省级行政区2005-2010年的省级年度数据,基于系统GMM估计法,对我国农村居民电力消费的双对数动态模型进行了估计。估计结果表明,我国农村居民电力需求主要受人均收入、燃料价格、电价、家庭人口规模、家电价格、城镇化水平及年平均气温等因素的影响。要增加农村居民电力消费量,重要的途径是要增加其收入水平,并降低其电用成本。
In this paper, based on systematic GMM estimation method, we estimate Double Logarithmic Dynamic Model of China＇ s rural residential electricity consumption using annual data for 30 provincial-level administrative regions in China from 2005 to 2010. The estimated results indicate that China＇ s rural residential electricity demand is mainly influenced by per capita income, fuel prices, electricity price, family size, home appliances prices, urbanization level, annual mean temperature and so forth. The short-term and long-term income elasticity of rural residential electricity demand are 0.83 and 1.29, the short-term and long-term self price elasticity of demand are 0. 13 and 0.20, respectively, and with short-term price elasticity of.fuel demand being 0. 72 and 0. 36 as the price elasticity of home appliances. These serves to the conclusion that the significant approach to increase rural residential electricity consumption is to increase the income level and decrease the electricity price of rural residents.
出处
《统计研究》
CSSCI
北大核心
2014年第1期84-90,共7页
Statistical Research
关键词
电力需求
农村居民
面板数据
动态面板数据模型
Residential Electricity Demand
Rural China
Panel Data
Dynamic Panel Data Model.
