Price elasticity of electricity demand for various dynamic rate programs

Author(s):  
Mustafa A. Biviji ◽  
W. Maria Wang ◽  
James Ostrowski ◽  
Jianhui Wang
1986 ◽  
Vol 15 (2) ◽  
pp. 123-129 ◽  
Author(s):  
Thomas H. Stevens ◽  
Gail Adams

The demand for electricity in the residential sector is estimated to have become less elastic for the recent period of rising real prices as compared to earlier periods of stable or falling real price. Several possible reasons for this are investigated and we conclude that demand appears to be asymmetric with respect to price in both the short and long run. We then examine whether or not this is an important factor for forecast accuracy and public policy.


2018 ◽  
Vol 201 ◽  
pp. 169-177 ◽  
Author(s):  
Xing Zhu ◽  
Lanlan Li ◽  
Kaile Zhou ◽  
Xiaoling Zhang ◽  
Shanlin Yang

Energy Policy ◽  
2011 ◽  
Vol 39 (6) ◽  
pp. 3709-3719 ◽  
Author(s):  
Shu Fan ◽  
Rob J. Hyndman

2010 ◽  
Vol 15 (Special Edition) ◽  
pp. 75-106 ◽  
Author(s):  
Azam Amjad Chaudhry

This paper looks at the economy-wide demand and the firm level demand for electricity in Pakistan. The economy wide estimation of electricity demand uses panel data from 63 countries from 1998-2008, and finds that the elasticity of demand for electricity with respect to per capita income is approximately 0.69, which implies that a 1% increase in per capita income will lead to a 0.69% increase in the demand for electricity. The firm level analysis uses firm level data from the World Bank’s Enterprise Survey for Pakistan and finds that the price elasticity of demand for electricity across all firms is approximately -0.57, which implies that a 1% increase in electricity prices will lead to a 0.57% decrease in electricity demand across firms. Across sectors, the textile sector has the highest price elasticity of demand (-0.81) while the price elasticity of demand for firms in the electricity and electronics sector is the smallest (-0.31). Finally, firm level data is also used to estimate production functions in order to estimate the impact of electricity shortages on manufacturing output.


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