IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/870.html
   My bibliography  Save this paper

Determining the efficiency of residential electricity consumption

Author

Listed:
  • Andor, Mark Andreas
  • Bernstein, David H.
  • Sommer, Stephan

Abstract

Increasing energy efficiency is a key global policy goal for climate protection. An important step towards an optimal reduction of energy consumption is the identification of energy saving potentials in different sectors and the best strategies for increasing efficiency. This paper analyzes these potentials in the household sector by estimating the degree of inefficiency in the use of electricity and its determinants. Using stochastic frontier analysis and disaggregated household data, we estimate an input requirement function and inefficiency on a sample of 2,000 German households. Our results suggest that the mean inefficiency amounts to around 20%, indicating a notable potential for energy savings. Moreover, we find that the household size and income are among the main determinants of individual inefficiency. This information can be used to increase the cost-efficiency of programs aimed to enhance energy efficiency.

Suggested Citation

  • Andor, Mark Andreas & Bernstein, David H. & Sommer, Stephan, 2020. "Determining the efficiency of residential electricity consumption," Ruhr Economic Papers 870, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  • Handle: RePEc:zbw:rwirep:870
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/226188/1/1738335860.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Blasch, Julia & Boogen, Nina & Filippini, Massimo & Kumar, Nilkanth, 2017. "Explaining electricity demand and the role of energy and investment literacy on end-use efficiency of Swiss households," Energy Economics, Elsevier, vol. 68(S1), pages 89-102.
    2. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    3. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    4. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    5. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    6. 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.
    7. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    8. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    9. Mark Andor & Christopher Parmeter, 2017. "Pseudolikelihood estimation of the stochastic frontier model," Applied Economics, Taylor & Francis Journals, vol. 49(55), pages 5651-5661, November.
    10. Andor, Mark A. & Parmeter, Christopher & Sommer, Stephan, 2019. "Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes," European Journal of Operational Research, Elsevier, vol. 274(1), pages 240-252.
    11. Hunt Allcott & Michael Greenstone, 2012. "Is There an Energy Efficiency Gap?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 3-28, Winter.
    12. Sebastien Houde, 2018. "Bunching with the Stars: How Firms Respond to Environmental Certification," CER-ETH Economics working paper series 18/292, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    13. Elisha R. Frederiks & Karen Stenner & Elizabeth V. Hobman, 2015. "The Socio-Demographic and Psychological Predictors of Residential Energy Consumption: A Comprehensive Review," Energies, MDPI, vol. 8(1), pages 1-37, January.
    14. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    15. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    16. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    17. Todd D. Gerarden & Richard G. Newell & Robert N. Stavins, 2017. "Assessing the Energy-Efficiency Gap," Journal of Economic Literature, American Economic Association, vol. 55(4), pages 1486-1525, December.
    18. Mark A. Andor, Andreas Gerster, and Stephan Sommer, 2020. "Consumer Inattention, Heuristic Thinking and the Role of Energy Labels," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    19. Sébastien Houde and C. Anna Spurlock, 2016. "Minimum Energy Efficiency Standards for Appliances: Old and New Economic Rationales," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    20. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    21. Amjadi, Golnaz & Lundgren, Tommy & Persson, Lars, 2018. "The Rebound Effect in Swedish Heavy Industry," Energy Economics, Elsevier, vol. 71(C), pages 140-148.
    22. John A. List & Robert D. Metcalfe & Michael K. Price & Florian Rundhammer, 2017. "Harnessing Policy Complementarities to Conserve Energy: Evidence from a Natural Field Experiment," NBER Working Papers 23355, National Bureau of Economic Research, Inc.
    23. Kenneth Gillingham & Amelia Keyes & Karen Palmer, 2018. "Advances in Evaluating Energy Efficiency Policies and Programs," Annual Review of Resource Economics, Annual Reviews, vol. 10(1), pages 511-532, October.
    24. Peter Grösche, 2009. "Measuring residential energy efficiency improvements with DEA," Journal of Productivity Analysis, Springer, vol. 31(2), pages 87-94, April.
    25. Buck, J. & Young, D., 2007. "The potential for energy efficiency gains in the Canadian commercial building sector: A stochastic frontier study," Energy, Elsevier, vol. 32(9), pages 1769-1780.
    26. Kenneth Gillingham & David Rapson & Gernot Wagner, 2016. "The Rebound Effect and Energy Efficiency Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 68-88.
    27. Borozan, Djula, 2018. "Technical and total factor energy efficiency of European regions: A two-stage approach," Energy, Elsevier, vol. 152(C), pages 521-532.
    28. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    29. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    30. Mark Andor & Frederik Hesse, 2014. "The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)," Journal of Productivity Analysis, Springer, vol. 41(1), pages 85-109, February.
    31. Bernstein, David H., 2020. "An updated assessment of technical efficiency and returns to scale for U.S. electric power plants," Energy Policy, Elsevier, vol. 147(C).
    32. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    33. Meredith Fowlie & Michael Greenstone & Catherine Wolfram, 2018. "Do Energy Efficiency Investments Deliver? Evidence from the Weatherization Assistance Program," The Quarterly Journal of Economics, Oxford University Press, vol. 133(3), pages 1597-1644.
    34. Manuel Frondel & Andreas Gerster & Colin Vance, 2020. "The Power of Mandatory Quality Disclosure: Evidence from the German Housing Market," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(1), pages 181-208.
    35. 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.
    36. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    37. Broadstock, David C. & Li, Jiajia & Zhang, Dayong, 2016. "Efficiency snakes and energy ladders: A (meta-)frontier demand analysis of electricity consumption efficiency in Chinese households," Energy Policy, Elsevier, vol. 91(C), pages 383-396.
    38. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    39. Ástmarsson, Björn & Jensen, Per Anker & Maslesa, Esmir, 2013. "Sustainable renovation of residential buildings and the landlord/tenant dilemma," Energy Policy, Elsevier, vol. 63(C), pages 355-362.
    40. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    41. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.
    42. Kumbhakar, Subal C, 1991. "The Measurement and Decomposition of Cost-Inefficiency: The Translog Cost System," Oxford Economic Papers, Oxford University Press, vol. 43(4), pages 667-683, October.
    43. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    44. Mills, Bradford & Schleich, Joachim, 2012. "Residential energy-efficient technology adoption, energy conservation, knowledge, and attitudes: An analysis of European countries," Energy Policy, Elsevier, vol. 49(C), pages 616-628.
    45. Andor, Mark A. & Gerster, Andreas & Peters, Jörg & Schmidt, Christoph M., 2020. "Social Norms and Energy Conservation Beyond the US," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    46. Chu Wei & Jinlan Ni & Manhong Shen, 2009. "Empirical Analysis of Provincial Energy Efficiency in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 17(5), pages 88-103, September.
    47. Lucas W. Davis & Alan Fuchs & Paul Gertler, 2014. "Cash for Coolers: Evaluating a Large-Scale Appliance Replacement Program in Mexico," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 207-238, November.
    48. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    49. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    50. Filippini, Massimo & Hunt, Lester C. & Zorić, Jelena, 2014. "Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector," Energy Policy, Elsevier, vol. 69(C), pages 73-81.
    51. Joanne Evans & Massimo Filippini & Lester C. Hunt, 2013. "The contribution of energy efficiency towards meeting CO2 targets," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 8, pages 175-223, Edward Elgar Publishing.
    52. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    53. Jaffe, Adam B. & Stavins, Robert N., 1994. "The energy-efficiency gap What does it mean?," Energy Policy, Elsevier, vol. 22(10), pages 804-810, October.
    54. Ringel, Marc & Schlomann, Barbara & Krail, Michael & Rohde, Clemens, 2016. "Towards a green economy in Germany? The role of energy efficiency policies," Applied Energy, Elsevier, vol. 179(C), pages 1293-1303.
    55. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    56. Parmeter, Christopher F. & Kumbhakar, Subal C., 2014. "Efficiency Analysis: A Primer on Recent Advances," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(3-4), pages 191-385, December.
    57. Lucas W. Davis, 2008. "Durable goods and residential demand for energy and water: evidence from a field trial," RAND Journal of Economics, RAND Corporation, vol. 39(2), pages 530-546, June.
    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. Chlond, Bettina & Goeschl, Timo & Kesternich, Martin, 2022. "More money or better procedures? Evidence from an energy efficiency assistance program," Working Papers 0716, University of Heidelberg, Department of Economics.
    2. Klára Čermáková & Eduard Hromada, 2022. "Change in the Affordability of Owner-Occupied Housing in the Context of Rising Energy Prices," Energies, MDPI, vol. 15(4), pages 1-18, February.
    3. Subal C. Kumbhakarⓡ & Emir Malikovⓡ & Christopher F. Parmeterⓡ, 2021. "Applications of efficiency and productivity analysis: editors’ introduction," Empirical Economics, Springer, vol. 60(6), pages 2657-2663, June.
    4. Jianmin You & Xiqiang Chen & Jindao Chen, 2021. "Decomposition of Industrial Electricity Efficiency and Electricity-Saving Potential of Special Economic Zones in China Considering the Heterogeneity of Administrative Hierarchy and Regional Location," Energies, MDPI, vol. 14(17), pages 1-22, September.
    5. Chlond, Bettina & Goeschl, Timo & Kesternich, Martin, 2022. "More money or better procedures? Evidence from an energy efficiency assistance program," ZEW Discussion Papers 22-020, ZEW - Leibniz Centre for European Economic Research.

    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. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    2. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.
    3. Giovanni Marin & Alessandro Palma, 2015. "Technology invention and diffusion in residential energy consumption. A stochastic frontier approach," IEFE Working Papers 81, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    4. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    5. Calvin Nsangou, Jean & Kenfack, Joseph & Nzotcha, Urbain & Tamo, Thomas Tatietse, 2020. "Assessment of the potential for electricity savings in households in Cameroon: A stochastic frontier approach," Energy, Elsevier, vol. 211(C).
    6. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    7. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    8. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    9. Gale A. Boyd and Jonathan M. Lee, 2020. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 39-62.
    10. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
    11. Akihiro Otsuka, 2020. "How do population agglomeration and interregional networks improve energy efficiency?," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 1-25, February.
    12. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.
    13. Manuel Llorca & José Baños & José Somoza & Pelayo Arbués, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    14. Huaping Sun & Bless Kofi Edziah & Xiaoqian Song & Anthony Kwaku Kporsu & Farhad Taghizadeh-Hesary, 2020. "Estimating Persistent and Transient Energy Efficiency in Belt and Road Countries: A Stochastic Frontier Analysis," Energies, MDPI, vol. 13(15), pages 1-19, July.
    15. Gale Boyd & Matt Doolin, 2020. "The Energy Efficiency Gap and Energy Price Responsiveness in Food Processing," Working Papers 20-18, Center for Economic Studies, U.S. Census Bureau.
    16. Romero-Jordán, Desiderio & del Río, Pablo, 2022. "Analysing the drivers of the efficiency of households in electricity consumption," Energy Policy, Elsevier, vol. 164(C).
    17. Twerefou, Daniel Kwabena & Abeney, Jacob Opantu, 2020. "Efficiency of household electricity consumption in Ghana," Energy Policy, Elsevier, vol. 144(C).
    18. Blasch, Julia & Boogen, Nina & Filippini, Massimo & Kumar, Nilkanth, 2017. "Explaining electricity demand and the role of energy and investment literacy on end-use efficiency of Swiss households," Energy Economics, Elsevier, vol. 68(S1), pages 89-102.
    19. Boyd, Gale A. & Lee, Jonathan M., 2019. "Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis," Energy Economics, Elsevier, vol. 81(C), pages 159-174.
    20. Anna Alberini & Massimo Filippini, 2015. "Transient and Persistent Energy Efficiency in the US Residential Sector: Evidence from Household-level Data," CER-ETH Economics working paper series 15/220, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.

    More about this item

    Keywords

    household electricity consumption; stochastic frontier analysis; technical efficiency;
    All these keywords.

    JEL classification:

    • D1 - Microeconomics - - Household Behavior
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

    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:870. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/rwiesde.html .

    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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.