IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/722.html
   My bibliography  Save this paper

Heterogeneity in residential electricity consumption: A quantile regression approach

Author

Listed:
  • Frondel, Manuel
  • Sommer, Stephan
  • Vance, Colin

Abstract

Drawing on the most recent wave of the German Residential Energy Survey (GRECS), this paper estimates the contribution of individual appliances to household electricity consumption. Moving beyond the standard focus of estimating mean effects, we combine the conditional demand approach with quantile regression methods to capture the heterogeneity in the contribution of each appliance to the distribution of household electricity consumption. While reflecting correlations, rather than causal relationships, our results indicate substantial differences in the end-use shares across households originating from the opposite tails of the electricity consumption distribution, highlighting the added value of applying quantile regression methods in estimating consumption rates of electric appliances.

Suggested Citation

  • Frondel, Manuel & Sommer, Stephan & Vance, Colin, 2017. "Heterogeneity in residential electricity consumption: A quantile regression approach," Ruhr Economic Papers 722, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:722
    DOI: 10.4419/86788842
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/172474/1/rep_17_722.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4419/86788842?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    3. Frondel, Manuel & Ritter, Nolan & Vance, Colin, 2012. "Heterogeneity in the rebound effect: Further evidence for Germany," Energy Economics, Elsevier, vol. 34(2), pages 461-467.
    4. Michael Parti & Cynthia Parti, 1980. "The Total and Appliance-Specific Conditional Demand for Electricity in the Household Sector," Bell Journal of Economics, The RAND Corporation, vol. 11(1), pages 309-321, Spring.
    5. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    6. Hanne Marit Dalen and Bodil M. Larsen, 2015. "Residential End-use Electricity Demand: Development over Time," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    7. Halvorsen, Bente & Larsen, Bodil M., 2001. "The flexibility of household electricity demand over time," Resource and Energy Economics, Elsevier, vol. 23(1), pages 1-18, January.
    8. Dennis J. Aigner & Cynts Sorooshian & Pamela Kerwin, 1984. "Conditional Demand Analysis for Estimating Residential End-Use Load Profiles," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 81-98.
    9. Larsen, Bodil Merethe & Nesbakken, Runa, 2004. "Household electricity end-use consumption: results from econometric and engineering models," Energy Economics, Elsevier, vol. 26(2), pages 179-200, March.
    10. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 853-883.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Frondel, Manuel & Kussel, Gerhard & Sommer, Stephan, 2019. "Heterogeneity in the price response of residential electricity demand: A dynamic approach for Germany," Resource and Energy Economics, Elsevier, vol. 57(C), pages 119-134.
    2. Tilov, Ivan & Farsi, Mehdi & Volland, Benjamin, 2020. "From frugal Jane to wasteful John: A quantile regression analysis of Swiss households’ electricity demand," Energy Policy, Elsevier, vol. 138(C).

    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. Frondel, Manuel & Sommer, Stephan & Vance, Colin, 2019. "Heterogeneity in German Residential Electricity Consumption: A quantile regression approach," Energy Policy, Elsevier, vol. 131(C), pages 370-379.
    2. Boogen, Nina & Datta, Souvik & Filippini, Massimo, 2021. "Estimating residential electricity demand: New empirical evidence," Energy Policy, Elsevier, vol. 158(C).
    3. Cao, Jing & Ho, Mun Sing & Li, Yating & Newell, Richard G. & Pizer, William A., 2019. "Chinese residential electricity consumption: Estimation and forecast using micro-data," Resource and Energy Economics, Elsevier, vol. 56(C), pages 6-27.
    4. Frontuto, Vito, 2019. "Forecasting household consumption of fuels: A multiple discrete-continuous approach," Applied Energy, Elsevier, vol. 240(C), pages 205-214.
    5. Hanne Marit Dalen and Bodil M. Larsen, 2015. "Residential End-use Electricity Demand: Development over Time," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    6. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    7. Vesterberg, Mattias, 2016. "The hourly income elasticity of electricity," Energy Economics, Elsevier, vol. 59(C), pages 188-197.
    8. Jia, Jun-Jun & Ni, Jinlan & Wei, Chu, 2023. "Residential responses to service-specific electricity demand: Case of China," China Economic Review, Elsevier, vol. 78(C).
    9. Papineau, Maya & Yassin, Kareman & Newsham, Guy & Brice, Sarah, 2021. "Conditional demand analysis as a tool to evaluate energy policy options on the path to grid decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    10. Nina Boogen & Souvik Datta & Massimo Filippini, 2014. "Going beyond tradition: Estimating residential electricity demand using an appliance index and energy services," CER-ETH Economics working paper series 14/200, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    11. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    12. Shigeru Matsumoto, 2015. "Electric Appliance Ownership and Usage: Application of Conditional Demand Analysis to Japanese Household Data," Proceedings of International Academic Conferences 3105452, International Institute of Social and Economic Sciences.
    13. Matsumoto, Shigeru, 2016. "How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data," Energy Policy, Elsevier, vol. 94(C), pages 214-223.
    14. Heindl, Peter & Löschel, Andreas, 2015. "Social implications of green growth policies from the perspective of energy sector reform and its impact on households," ZEW Discussion Papers 15-012, ZEW - Leibniz Centre for European Economic Research.
    15. 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.
    16. Claudio Agostini & Cecilia Plottier & Eduardo Saavedra, 2009. "La Demanda Residencial por Energía Eléctrica en Chile," ILADES-UAH Working Papers inv240, Universidad Alberto Hurtado/School of Economics and Business.
    17. Çetinkaya, Murat & Başaran, Alparslan A. & Bağdadioğlu, Necmiddin, 2015. "Electricity reform, tariff and household elasticity in Turkey," Utilities Policy, Elsevier, vol. 37(C), pages 79-85.
    18. Claudio A Agostini & Eduardo Saavedra, 2014. "Elasticities of Residential Electricity Demand in Chile," Working Papers wp_034, Adolfo Ibáñez University, School of Government.
    19. Shiraki, Hiroto & Nakamura, Shogo & Ashina, Shuichi & Honjo, Keita, 2016. "Estimating the hourly electricity profile of Japanese households – Coupling of engineering and statistical methods," Energy, Elsevier, vol. 114(C), pages 478-491.
    20. Dorothée Charlier & Sondès Kahouli, 2018. "Fuel poverty and residential energy demand: how fuel-poor households react to energy price fluctuations," Post-Print halshs-01957771, HAL.

    More about this item

    Keywords

    Electricity consumption; conditional demand approach; quantile regression methods;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    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:zbw:rwirep:722. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/rwiesde.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.