Estimating sectoral demands for electricity using the pooled mean group method
© 2018 Elsevier Ltd 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.
Publication Source (Journal or Book title)
Gautam, T., & Paudel, K. (2018). Estimating sectoral demands for electricity using the pooled mean group method. Applied Energy, 54-67. https://doi.org/10.1016/j.apenergy.2018.09.023