IDEAS home Printed from https://ideas.repec.org/p/eth/wpswif/15-220.html
   My bibliography  Save this paper

Transient and Persistent Energy Efficiency in the US Residential Sector: Evidence from Household-level Data

Author

Abstract

In this paper, we measure the energy efficiency in residential energy consumption using a panel dataset comprised of 40,246 observations from US households observed over 1997-2009. We fit a stochastic frontier model of the minimum input of energy needed to meet the level of energy services demanded by the household. This benchmarking exercise produces a transient and a persistent efficiency index for each household and each time period. We estimate that the US residential sector could save approximately 10% of its total energy consumption if it reduced persistent inefficiencies and 17% if it was able to eliminate transient inefficiencies. These figures are in line with the assessment by McKinsey (2008, 2009, 2013) and greater than those indicated by the Electric Power Research Institute (2009). They suggest that savings in energy use and associated emissions of greenhouse gases (and other pollutants) may benefit from both policy measures that attain short-run behavioral changes (e.g., nudges, social norms, display of real-time information about usage, and real-time pricing) as well measures aimed at the long run, such as energy-efficiency regulations, incentives on the purchase of high-efficiency equipment and incentives towards a change of habits in the use of the equipment.

Suggested Citation

  • 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.
    • Handle: RePEc:eth:wpswif:15-220
    as

    Download full text from publisher

    File URL: http://www.cer.ethz.ch/content/dam/ethz/special-interest/mtec/cer-eth/cer-eth-dam/documents/working-papers/WP-15-220.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Alberini, Anna & Towe, Charles, 2015. "Information v. energy efficiency incentives: Evidence from residential electricity consumption in Maryland," Energy Economics, Elsevier, vol. 52(S1), pages 30-40.
    3. 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.
    4. 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.
    5. 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.
    6. Massimo Filippini, 1999. "Swiss residential demand for electricity," Applied Economics Letters, Taylor & Francis Journals, vol. 6(8), pages 533-538.
    7. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    8. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    9. Gans, Will & Alberini, Anna & Longo, Alberto, 2013. "Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland," Energy Economics, Elsevier, vol. 36(C), pages 729-743.
    10. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential consumption of gas and electricity in the U.S.: The role of prices and income," Energy Economics, Elsevier, vol. 33(5), pages 870-881, September.
    11. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528.
    12. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    13. 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.
    14. Roger Fouquet (ed.), 2013. "Handbook on Energy and Climate Change," Books, Edward Elgar Publishing, number 14429.
    15. 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.
    16. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    17. Hunt Allcott & Todd Rogers, 2014. "The Short-Run and Long-Run Effects of Behavioral Interventions: Experimental Evidence from Energy Conservation," American Economic Review, American Economic Association, vol. 104(10), pages 3003-3037, October.
    18. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    19. Flaig, Gebhard, 1990. "Household production and the short- and long-run demand for electricity," Energy Economics, Elsevier, vol. 12(2), pages 116-121, April.
    20. 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.
    21. Huntington, Hillard G., 1994. "Been top down so long it looks like bottom up to me," Energy Policy, Elsevier, vol. 22(10), pages 833-839, October.
    22. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762.
    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. 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.
    2. Eri Nakamura & Fumitoshi Mizutani, 2019. "Necessary demand and extra demand of public utility product: identification using the stochastic frontier model," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 46(1), pages 45-64, March.
    3. 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.
    4. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.
    5. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.

    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. Massimo Filippini & Lester C. Hunt, 2013. "'Underlying Energy Efficiency' in the US," CER-ETH Economics working paper series 13/181, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    2. Mark A. Andor & David H. Bernstein & Stephan Sommer, 2021. "Determining the efficiency of residential electricity consumption," Empirical Economics, Springer, vol. 60(6), pages 2897-2923, June.
    3. 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.
    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. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.
    6. 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).
    7. 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.
    8. 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).
    9. Dolšak, Janez & Hrovatin, Nevenka & Zorić, Jelena, 2022. "Estimating the efficiency in overall energy consumption: Evidence from Slovenian household-level data," Energy Economics, Elsevier, vol. 114(C).
    10. 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.
    11. Ramos, A. & Gago, A. & Labandeira, X. & Linares, P., 2015. "The role of information for energy efficiency in the residential sector," Energy Economics, Elsevier, vol. 52(S1), pages 17-29.
    12. 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.
    13. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    14. Zhang, Lin, 2017. "Correcting the uneven burden sharing of emission reduction across provinces in China," Energy Economics, Elsevier, vol. 64(C), pages 335-345.
    15. Akihiro Otsuka, 2018. "Regional Determinants of Energy Efficiency: Residential Energy Demand in Japan," Energies, MDPI, vol. 11(6), pages 1-14, June.
    16. Kang, Jijun & Yu, Chenyang & Xue, Rui & Yang, Dong & Shan, Yuli, 2022. "Can regional integration narrow city-level energy efficiency gap in China?," Energy Policy, Elsevier, vol. 163(C).
    17. 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.
    18. Wang, Xia & Ding, Chao & Zhou, Mao & Cai, Weiguang & Ma, Xianrui & Yuan, Jiachen, 2023. "Assessment of space heating consumption efficiency based on a household survey in the hot summer and cold winter climate zone in China," Energy, Elsevier, vol. 274(C).
    19. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.
    20. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.

    More about this item

    Keywords

    US residential energy demand; efficiency and frontier analysis; Household data; CO2 emissions reductions;
    All these keywords.

    JEL classification:

    • D - Microeconomics
    • D2 - Microeconomics - - Production and Organizations
    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • 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:eth:wpswif:15-220. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/iwethch.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.