IDEAS home Printed from https://ideas.repec.org/p/rff/dpaper/dp-08-50.html
   My bibliography  Save this paper

A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector

Author

Listed:
  • Paul, Anthony

    (Resources for the Future)

  • Myers, Erica

    (Resources for the Future)

  • Palmer, Karen

    (Resources for the Future)

Abstract

Identifying the factors that influence electricity demand in the continental United States and mathematically characterizing them are important for developing electricity consumption projections. The price elasticity of demand is especially important, since the electricity price effects of policy implementation can be substantial and the demand response to policy-induced changes in prices can significantly affect the cost of policy compliance. This paper estimates electricity demand functions with particular attention paid to the demand stickiness that is imposed by the capital-intensive nature of electricity consumption and to regional, seasonal, and sectoral variation. The analysis uses a partial adjustment model of electricity demand that is estimated in a fixed-effects OLS framework. This model formulation allows for the price elasticity to be expressed in both its short-run and long-run forms. Price elasticities are found to be broadly consistent with the existing literature, but with important regional, seasonal, and sectoral differences.

Suggested Citation

  • Paul, Anthony & Myers, Erica & Palmer, Karen, 2009. "A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector," RFF Working Paper Series dp-08-50, Resources for the Future.
  • Handle: RePEc:rff:dpaper:dp-08-50
    as

    Download full text from publisher

    File URL: http://www.rff.org/RFF/documents/RFF-DP-08-50.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hsing, Yu, 1994. "Estimation of residential demand for electricity with the cross-sectionally correlated and time-wise autoregressive model," Resource and Energy Economics, Elsevier, vol. 16(3), pages 255-263, August.
    2. Dahl, Carol A., 1993. "A survey of energy demand elasticities in support of the development of the NEMS," MPRA Paper 13962, University Library of Munich, Germany.
    3. David S. Loughran and Jonathan Kulick, 2004. "Demand-Side Management and Energy Efficiency in the United States," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 19-44.
    4. Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
    5. Kamerschen, David R. & Porter, David V., 2004. "The demand for residential, industrial and total electricity, 1973-1998," Energy Economics, Elsevier, vol. 26(1), pages 87-100, January.
    6. Hendrik S. Houthakker, 1980. "Residential Electricity Revisited," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    7. Espey, James A. & Espey, Molly, 2004. "Turning on the Lights: A Meta-Analysis of Residential Electricity Demand Elasticities," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 36(1), pages 65-81, April.
    8. Beierlein, James G & Dunn, James W & McConnon, James C, Jr, 1981. "The Demand for Electricity and Natural Gas in the Northeastern United States," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 403-408, August.
    9. Marvin J. Horowitz, 2004. "Electricity Intensity in the Commercial Sector: Market and Public Program Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 115-138.
    10. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    11. Lin, Winston T. & Chen, Yueh H. & Chatov, Robert, 1987. "The demand for natural gas, electricity and heating oil in the United States," Resources and Energy, Elsevier, vol. 9(3), pages 233-258, October.
    12. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
    13. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cho, Seong-Hoon & Kim, Taeyoung & Kim, Hyun Jae & Park, Kihyun & Roberts, Roland K., 2015. "Regionally-varying and regionally-uniform electricity pricing policies compared across four usage categories," Energy Economics, Elsevier, vol. 49(C), pages 182-191.
    2. Anin Aroonruengsawat, Maximilian Auffhammer, and Alan H. Sanstad, 2012. "The Impact of State Level Building Codes on Residential Electricity Consumption," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    3. Massimo Filippini & Bettina Hirl & Giuliano Masiero, 2015. "Rational habits in residential electricity demand," IdEP Economic Papers 1506, USI Università della Svizzera italiana.
    4. Filippini, Massimo & Hirl, Bettina & Masiero, Giuliano, 2018. "Habits and rational behaviour in residential electricity demand," Resource and Energy Economics, Elsevier, vol. 52(C), pages 137-152.
    5. Fell, Harrison & Li, Shanjun & Paul, Anthony, 2014. "A new look at residential electricity demand using household expenditure data," International Journal of Industrial Organization, Elsevier, vol. 33(C), pages 37-47.
    6. Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
    7. Kavousian, Amir & Rajagopal, Ram & Fischer, Martin, 2013. "Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior," Energy, Elsevier, vol. 55(C), pages 184-194.
    8. Dorothée CHARLIER & Mouez FODHA & Djamel KIRAT, 2021. "CO2 Emissions from the Residential Sector in Europe: Some Insights form a Country-Level Assessment," LEO Working Papers / DR LEO 2849, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Miller, Mark & Alberini, Anna, 2016. "Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from U.S. Data," Energy Policy, Elsevier, vol. 97(C), pages 235-249.
    10. Bernard, Jean-Thomas & Bolduc, Denis & Yameogo, Nadège-Désirée, 2011. "A pseudo-panel data model of household electricity demand," Resource and Energy Economics, Elsevier, vol. 33(1), pages 315-325, January.
    11. Garcia-Cerrutti, L. Miguel, 2000. "Estimating elasticities of residential energy demand from panel county data using dynamic random variables models with heteroskedastic and correlated error terms," Resource and Energy Economics, Elsevier, vol. 22(4), pages 355-366, October.
    12. Cao, K.H. & Qi, H.S. & Li, R. & Woo, C.K. & Tishler, A. & Zarnikau, J., 2023. "An experiment in own-price elasticity estimation for non-residential electricity demand in the U.S," Utilities Policy, Elsevier, vol. 81(C).
    13. Ivan Faiella & Luciano Lavecchia, 2021. "Households' energy demand and the effects of carbon pricing in Italy," Questioni di Economia e Finanza (Occasional Papers) 614, Bank of Italy, Economic Research and International Relations Area.
    14. Papineau, Maya, 2017. "Setting the standard? A framework for evaluating the cost-effectiveness of building energy standards," Energy Economics, Elsevier, vol. 64(C), pages 63-76.
    15. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2018. "A discrete/continuous choice model on a nonconvex budget set," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 89-113, February.
    16. Woo, C.K. & Liu, Y. & Zarnikau, J. & Shiu, A. & Luo, X. & Kahrl, F., 2018. "Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016," Applied Energy, Elsevier, vol. 222(C), pages 460-474.
    17. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    18. Derya Eryilmaz, Timothy M. Smith, and Frances R. Homans, 2017. "Price Responsiveness in Electricity Markets: Implications for Demand Response in the Midwest," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    19. Yueming Qiu, 2014. "Energy Efficiency and Rebound Effects: An Econometric Analysis of Energy Demand in the Commercial Building Sector," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(2), pages 295-335, October.
    20. Payne, James E. & Loomis, David G. & Wilson, Renardo, 2011. "Residential Natural Gas Demand in Illinois: Evidence from the ARDL Bounds Testing Approach," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 41(2), pages 1-10.

    More about this item

    Keywords

    electricity; demand elasticities; energy demand; partial adjustment;
    All these keywords.

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rff:dpaper:dp-08-50. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Resources for the Future (email available below). General contact details of provider: https://edirc.repec.org/data/rffffus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.