IDEAS home Printed from https://ideas.repec.org/a/aen/journl/1996v17-04-a02.html
   My bibliography  Save this article

Gas or Electricity, which is Cheaper? An Econometric Approach with Application to Australian Expenditure Data

Author

Listed:
  • Robert Bartels
  • Denzil G. Fiebig
  • Michael H. Plumb

Abstract

The question of whether it is cheaper for households to use electricity or gas for space heating, water heating and cooking, generates much debate in Australia. Generally, gas appliances are technically less efficient than electrical appliances, but on a per MJ basis, gas is cheaper than electricity. The trade-off between these two factors has typically been assessed using an engineering approach which ignores the fact that gas and electric appliances might be used in different ways in the home and that there may be price effects. This paper utilises an alternative perspective based on econometric methods. We analyse the actual energy expenditures of a large sample of Australian households and estimate the expenditure on the main end-uses for households using different fuel types. We find that households using electricity for main heating spend considerably less than households using gas. For cooking, households using gas generally spend less, while for water heating the results are mixed. We discuss several possible interpretations of these results in terms of consumer preferences and running costs.

Suggested Citation

  • Robert Bartels & Denzil G. Fiebig & Michael H. Plumb, 1996. "Gas or Electricity, which is Cheaper? An Econometric Approach with Application to Australian Expenditure Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 33-58.
  • Handle: RePEc:aen:journl:1996v17-04-a02
    as

    Download full text from publisher

    File URL: http://www.iaee.org/en/publications/ejarticle.aspx?id=1234
    Download Restriction: Access to full text is restricted to IAEE members and subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Robert Bartels & Denzil G. Fiebig, 1990. "Integrating Direct Metering and Conditional Demand Analysis for Estimating End-Use Loads," The Energy Journal, , vol. 11(4), pages 79-98, October.
    2. Hwang, Hae-shin, 1990. "Estimation of a Linear SUR Model with Unequal Numbers of Observations," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 510-515, August.
    3. Fiebig, Denzil G. & Bartels, Robert & Aigner, Dennis J., 1991. "A random coefficient approach to the estimation of residential end-use load profiles," Journal of Econometrics, Elsevier, vol. 50(3), pages 297-327, December.
    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. Smith, Michael & Kohn, Robert, 2000. "Nonparametric seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 98(2), pages 257-281, October.
    2. Tilov, Ivan & Farsi, Mehdi & Volland, Benjamin, 2019. "Interactions in Swiss households’ energy demand: A holistic approach," Energy Policy, Elsevier, vol. 128(C), pages 136-149.
    3. Muhammad, Akmal, 2002. "The structure of consumer energy demand in Australia: an application of a dynamic almost ideal demand system," 2002 Conference (46th), February 13-15, 2002, Canberra, Australia 125050, Australian Agricultural and Resource Economics Society.
    4. Robert Bartels & Denzil G. Fiebig, 2000. "Residential End-Use Electricity Demand: Results from a Designed Experiment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 51-81.
    5. Raymond Li & Chi-Keung Woo & Asher Tishler & Jay Zarnikau, 2022. "Price Responsiveness of Residential Demand for Natural Gas in the United States," Energies, MDPI, vol. 15(12), pages 1-22, June.

    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. Mattias Vesterberg and Chandra Kiran B. Krishnamurthy, 2016. "Residential End-use Electricity Demand: Implications for Real Time Pricing in Sweden," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. Muhammad Akmal & David I. Stern, 2001. "Residential energy demand in Australia: an application of dynamic OLS," Working Papers in Ecological Economics 0104, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
    3. 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).
    4. Muhammad Akmal & David I. Stern, 2001. "The structure of Australian residential energy demand," Working Papers in Ecological Economics 0101, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
    5. 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.
    6. Mattias Vesterberg & Chandra Kiran B. Krishnamurthy, 2016. "Residential End-use Electricity Demand: Implications for Real Time Pricing in Sweden," The Energy Journal, , vol. 37(4), pages 141-164, October.
    7. Narayan, Paresh Kumar & Smyth, Russell, 2005. "The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration," Energy Policy, Elsevier, vol. 33(4), pages 467-474, March.
    8. Robert Bartels & Denzil G. Fiebig & Daehoon Nahm, 1996. "Regional End‐Use Gas Demand in Australia," The Economic Record, The Economic Society of Australia, vol. 72(219), pages 319-331, December.
    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. Bartels, Robert & Fiebig, Denzil G., 1995. "Optimal design in end-use metering experiments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 305-309.
    11. Muhammad, Akmal, 2002. "The structure of consumer energy demand in Australia: an application of a dynamic almost ideal demand system," 2002 Conference (46th), February 13-15, 2002, Canberra, Australia 125050, Australian Agricultural and Resource Economics Society.
    12. 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).
    13. Aydinalp-Koksal, Merih & Ugursal, V. Ismet, 2008. "Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector," Applied Energy, Elsevier, vol. 85(4), pages 271-296, April.
    14. Aydinalp, Merih & Ismet Ugursal, V. & Fung, Alan S., 2002. "Modeling of the appliance, lighting, and space-cooling energy consumptions in the residential sector using neural networks," Applied Energy, Elsevier, vol. 71(2), pages 87-110, February.
    15. 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).
    16. Vesterberg, Mattias, 2016. "The hourly income elasticity of electricity," Energy Economics, Elsevier, vol. 59(C), pages 188-197.
    17. Yildiz, B. & Bilbao, J.I. & Dore, J. & Sproul, A.B., 2017. "Recent advances in the analysis of residential electricity consumption and applications of smart meter data," Applied Energy, Elsevier, vol. 208(C), pages 402-427.
    18. Amaral, Luiz Felipe & Souza, Reinaldo Castro & Stevenson, Maxwell, 2008. "A smooth transition periodic autoregressive (STPAR) model for short-term load forecasting," International Journal of Forecasting, Elsevier, vol. 24(4), pages 603-615.
    19. 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.
    20. Hannah Goozee, 2017. "Energy, poverty and development: a primer for the Sustainable Development Goals," Working Papers 156, International Policy Centre for Inclusive Growth.

    More about this item

    JEL classification:

    • F0 - International Economics - - General

    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:aen:journl:1996v17-04-a02. 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: David Williams (email available below). General contact details of provider: https://edirc.repec.org/data/iaeeeea.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.