1. Estimating sectoral demands for electricity using the pooled mean group method.
- Author
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Gautam, Tej K. and Paudel, Krishna P.
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ELECTRIC power consumption , *ELASTICITY , *COINTEGRATION , *ENERGY conservation , *NATURAL gas - Abstract
Highlights • We estimate sectoral electricity demand in the Northeastern U.S. using panel data. • Cooling degree days have a positive effect in electricity demand in all three sectors. • Long run own price elasticities are negative in residential and industrial sectors. • Natural gas has long run substitution effect in residential and commercial sectors. • Heating oil price has short run positive effect in residential and commercial sectors. Abstract This paper examines the demand for electricity in the residential, commercial, and industrial sectors of the Northeastern United States using state-level panel data over the period from 1997 to 2011. It applies panel unit root and cointegration tests and then estimates the parameters using the pooled mean group method. The panel unit root and cointegration tests show that the series are integrated of order one and cointegrated. The electricity demand for the residential sector is responsive to its own price in the long run, with own price elasticity being −0.11, but irresponsive to own price in the short run. The long run income elasticities of electricity demand for the residential, commercial, and industrial sectors are 0.93, 0.53, and 1.95, respectively. Higher income elasticity implies that energy efficient appliances and the regulation of housing structures might be effective policy tools to promote energy conservation. The short run impact of fuel oil price is significant in the residential and commercial sectors. Cooling degree days have significant positive effects on the demand for electricity in the residential and commercial sectors. The long run cross price elasticities for natural gas in the residential and commercial sectors are 0.095 and 0.105, respectively. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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