An experiment in own-price elasticity estimation for non-residential electricity demand in the U.S. (April 2023)

• Record Type: Journal Article
• Authors: Cao, K.H.; Qi, H.S.; Li, R.; Woo, C.K.; Tishler, A.; Zarnikau, J.
• Is Part Of: Utilities policy. Volume 81(2023)
• Publication Date: 2023-04
• Subjects: Price elasticity -- Estimation experiment -- Non-residential electricity demand -- U.S; Public utilities -- United States -- Periodicals; Public utilities -- Government policy -- United States -- Periodicals; 363.6
• DOI: 10.1016/j.jup.2023.101489
• Languages: English
• ISSNs: 0957-1787

Abstract

Abstract: This paper uses an experiment to identify what modeling decisions significantly affect estimates of own-price elasticity for non-residential (commercial and industrial) electricity demand in the United States (U.S.). Based on 174, 240 panel data model runs involving 10, 944 monthly state-level observations from the Energy Information Administration for 2001–2019, these decisions are parametric specification, estimation method, and treatment of cross-section dependence. As most of the many generated elasticity estimates are between 0.0 and −0.2, price-induced conservation is likely modest, thus justifying continued policy support for energy efficiency standards and demand-side management in the U.S. path to deep decarbonization. Highlights: There is great variation among prior estimates of the U.S. price elasticity of demand for electricity. An experimental approach is used to determine the sources of this variation. Modeling decisions affect the resulting elasticity estimates. Numerous modeling approaches are tested and most resulting elasticity estimates are between 0.0 and −0.2