How Price Responsive is Industrial Electricity Demand in the US?

Accurate projections of electricity demand growth by end-use customer class (residential, commercial, industrial) are necessary for energy policy modelling, resource planning, and electricity pricing and procurement. Motivated by the expected trend of rising retail electricity prices in the US and diverse price elasticity estimates found by extant studies, we answer the substantive policy question: how price responsive is industrial electricity demand in the US? Based on a comprehensive panel data analysis that uses five parametric specifications and monthly data for the lower 48 states in 2001-2019, our answer comprises: (1) the statistically significant (p-value ≤ 0.05) static own-price elasticity estimates are -0.029 to -0.130, short-run -0.021 to -0.133 and long-run -0.043 to -0.214; (2) the size of these estimates varies by elasticity type, sample period, parametric specification, and assumption of partial adjustment; (3) erroneously ignoring the highly significant (p-value < 0.01) cross-section dependence does not materially alter these elasticity estimates; (4) these elasticity estimates vary by region though not season and their size has been slowly declining over time. Hence, price-induced conservation’s future effect on the US industrial electricity demand is likely small, justifying policy continuation of energy efficiency standards and demand side management programs for deep decarbonization.

[1]  C. Woo,et al.  How price-responsive is residential retail electricity demand in the US? , 2021 .

[2]  F. Hasanov,et al.  Industry electricity price and output elasticities for high-income and middle-income countries , 2021, Empirical Economics.

[3]  David P. Brown,et al.  Residential electricity pricing in Texas's competitive retail market , 2020 .

[4]  Elisa Trujillo-Baute,et al.  Smart meters and consumer behaviour: Insights from the empirical literature , 2020, Energy Policy.

[5]  M. Pesaran.  General diagnostic tests for cross-sectional dependence in panels , 2020 .

[6]  J. Zarnikau,et al.  Determinants of the wholesale prices of energy and ancillary services in the U.S. Midcontinent electricity market , 2020 .

[7]  J. Zarnikau,et al.  Texas's operating reserve demand curve's generation investment incentive , 2020 .

[8]  Hung-po Chao,et al.  Coordination of electricity transmission and generation investments , 2020 .

[9]  A. Tishler,et al.  A wholesale electricity market design sans missing money and price manipulation , 2019, Energy Policy.

[10]  J. Zarnikau,et al.  Renewable energy's vanishing premium in Texas's retail electricity pricing plans , 2019, Energy Policy.

[11]  M. Frondel,et al.  Heterogeneity in the price response of residential electricity demand: A dynamic approach for Germany , 2019, Resource and Energy Economics.

[12]  J. Zarnikau,et al.  Market price behavior of wholesale electricity products: Texas , 2019, Energy Policy.

[13]  K. Paudel,et al.  Estimating sectoral demands for electricity using the pooled mean group method , 2018, Applied Energy.

[14]  Chi-Keung Woo,et al.  Carbon trading’s impact on California’s real-time electricity market prices , 2018, Energy.

[15]  Y. Liu,et al.  Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016 , 2018, Applied Energy.

[16]  Jay Zarnikau,et al.  Consumption effects of an electricity decarbonization policy: Hong Kong , 2018 .

[17]  Yu-Wen Su.  Electricity demand in industrial and service sectors in Taiwan , 2018, Energy Efficiency.

[18]  Chi-Keung Woo,et al.  Consumption effects of electricity decarbonization: Evidence from California and the Pacific Northwest , 2017 .

[19]  A. Olson,et al.  Does California's CO2 price affect wholesale electricity prices in the Western U.S.A.? , 2017 .

[20]  A. Olson,et al.  Electricity price behavior and carbon trading: New evidence from California , 2017 .

[21]  Paul J. Burke,et al.  The Price Elasticity of Electricity Demand in the United States: A Three-Dimensional Analysis , 2017 .

[22]  Frances R. Homans,et al.  Price Responsiveness in Electricity Markets: Implications for Demand Response in the Midwest , 2017 .

[23]  A. Ros.  An Econometric Assessment of Electricity Demand in the United States Using Utility-specific Panel Data and the Impact of Retail Competition on Prices , 2017 .

[24]  R. Roberts,et al.  Effects of electricity-price policy on electricity demand and manufacturing output , 2016 .

[25]  José M. Labeaga,et al.  A Meta-Analysis on the Price Elasticity of Energy Demand , 2016 .

[26]  Oar,et al.  National Action Plan for Energy Efficiency , 2015 .

[27]  Fulvio Fontini,et al.  The Long-Run Oil-Natural Gas Price Relationship and the Shale Gas Revolution , 2015 .

[28]  Benjamin Sovacool.  Cornucopia or Curse? Reviewing the Costs and Benefits of Shale Gas Hydraulic Fracturing (Fracking) , 2014 .

[29]  R. Weron.  Electricity price forecasting: A review of the state-of-the-art with a look into the future , 2014 .

[30]  G. Barbose,et al.  Survey of Western U.S. electric utility resource plans , 2014 .

[31]  Ira Horowitz,et al.  A review of electricity product differentiation , 2014 .

[32]  Yiyong Cai,et al.  U.S. Natural Gas Exports and Their Global Impacts , 2014 .

[33]  Katrina Jessoe,et al.  Knowledge is (Less) Power: Experimental Evidence from Residential Energy Use , 2012 .

[34]  José M. Labeaga,et al.  Estimation of Elasticity Price of Electricity with Incomplete Information , 2012 .

[35]  L. Suganthi,et al.  Energy models for demand forecasting—A review , 2012 .

[36]  W. R. Morrow,et al.  The Technology Path to Deep Greenhouse Gas Emissions Cuts by 2050: The Pivotal Role of Electricity , 2012, Science.

[37]  Ren Orans,et al.  What drives renewable energy development , 2011 .

[38]  A. Faruqui,et al.  Household response to dynamic pricing of electricity: a survey of 15 experiments , 2010 .

[39]  Jay Zarnikau,et al.  Aggregate industrial energy consumer response to wholesale prices in the restructured Texas electricity market , 2008 .

[40]  Brian P. Macfie.  The Impact of Utility Deregulation in Arizona , 2008 .

[41]  P. Damien,et al.  Testing functional forms in energy modeling: An application of the Bayesian approach to U.S. electricity demand , 2007 .

[42]  R. Weron.  Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach , 2006 .

[43]  Chi-Keung Woo,et al.  Designing Pareto-superior demand-response rate options , 2006 .

[44]  Fushuan Wen,et al.  Transmission investment and expansion planning in a restructured electricity market , 2006 .

[45]  M. Pesaran.  Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure , 2004, SSRN Electronic Journal.

[46]  M. Pesaran.  A Simple Panel Unit Root Test in the Presence of Cross Section Dependence , 2003 .

[47]  F. Wolak,et al.  Estimating the Customer-Level Demand for Electricity Under Real-Time Market Prices , 2001 .

[48]  C. Kao,et al.  Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey , 2000 .

[49]  Stan Lipovetsky,et al.  The Flexible CES-GBC Family of Cost Functions: Derivation and Application , 1997, Review of Economics and Statistics.

[50]  Dewey Seeto,et al.  Time-of-use rates vs. Hopkinson tariffs redux: an analysis of the choice of rate structures in a regulated electricity distribution company , 1997 .

[51]  Chi-Keung Woo,et al.  Pareto-superior time-of-use rate option for industrial firms , 1995 .

[52]  M. Pesaran,et al.  Estimating Long-Run Relationships From Dynamic Heterogeneous Panels , 1995 .

[53]  Benjamin F. Hobbs,et al.  Optimization methods for electric utility resource planning , 1995 .

[54]  Chi-Keung Woo,et al.  Managing water supply shortage Interruption vs. pricing , 1994 .

[55]  J. MacKinnon,et al.  Estimation and inference in econometrics , 1994 .

[56]  Carol A. Dahl,et al.  A survey of energy demand elasticities in support of the development of the NEMS , 1993 .

[57]  Masood A. Badri,et al.  Analysis of demand for electricity in the united states , 1992 .

[58]  F. Fisher,et al.  Due diligence and the demand for electricity: A cautionary tale , 1992 .

[59]  Winston T. Lin,et al.  The demand for natural gas, electricity and heating oil in the United States , 1987 .

[60]  D. R. Bohi,et al.  An Update on Econometric Studies of Energy Demand , 1984 .

[61]  Dennis J. Aigner,et al.  The welfare econometrics of peak-load pricing for electricity: Editor's Introduction , 1984 .

[62]  J. Robert Malko,et al.  The residential demand for electricity by time-of-use: A survey of twelve experiments with peak load pricing☆ , 1983 .

[63]  Alan S. Manne,et al.  Feature Article - Energy Policy Modeling: A Survey , 1979, Oper. Res..

[64]  Ernst R. Berndt,et al.  Reconciling Alternative Estimates of the Elasticity of Substitution , 1976 .

[65]  Walter Diewert,et al.  An Application of the Shephard Duality Theorem: A Generalized Leontief Production Function , 1971, Journal of Political Economy.

[66]  J. C. Bonbright.  Principles of Public Utility Rates , 1962 .

[67]  K. Paudel,et al.  THE DEMAND FOR ELECTRICITY AND NATURAL GAS IN THE NORTHEASTERN UNITED STATES , 2016 .

[68]  J. Zarnikau,et al.  Consumer support for a public utilities commission in Hong Kong , 2015 .

[69]  A. Chudik,et al.  UNIVERSITY OF SOUTHERN CALIFORNIA Center for Applied Financial Economics (CAFE) Common Correlated Effects Estimation of Heterogenous Dynamic Panel Data Models with Weakly Exogenous Regressors , 2013 .

[70]  F. Wua,et al.  Transmission investment and expansion planning in a restructured electricity market , 2006 .

[71]  D. Kamerschen,et al.  The demand for residential, industrial and total electricity, 1973-1998 , 2004 .

[72]  Jeffrey M. Woodbridge.  Econometric Analysis of Cross Section and Panel Data , 2002 .

[73]  J. Hausman.  Exact Consumer's Surplus and Deadweight Loss , 1981 .

[74]  L. R. Christensen,et al.  Global Properties of Flexible Functional Forms , 1980 .

[75]  R. Hartman,et al.  FRONTIERS IN ENERGY DEMAND MODELING , 1979 .

[76]  Lester D. Taylor,et al.  The demand for electricity: a survey , 1975 .