IDEAS home Printed from https://ideas.repec.org/p/eth/wpswif/13-181.html
   My bibliography  Save this paper

'Underlying Energy Efficiency' in the US

Author

Abstract

The promotion of US energy efficiency policy is seen as a very important activity by the Energy Information Agency (EIA). Generally, the level of energy efficiency of a state is approximated by energy intensity, commonly calculated as the ratio of energy use to GDP. However, energy intensity is not an accurate proxy for energy efficiency, because changes in energy intensity are a function of changes in several factors including the structure of the economy, climate, efficiency in the use of resources and technical change. The aim of this paper is to measure the ‘underlying energy efficiency’ for the whole economy of 49 ‘states’ in the US using a stochastic frontier energy demand approach. A total US energy demand frontier function is estimated using panel data for 49 ‘states’ over the period 1995 to 2009 using several panel data models: the pooled model; the random effects model; true fixed effects model; the true random effects model; and the Mundlak versions of the pooled and random effects models. The analysis confirms that energy intensity is not a good indicator of energy efficiency; whereas, by controlling for a range of economic and other factors, the measure of ‘underlying energy efficiency’ obtained via the approach adopted here (based on the microeconomic theory of production) is.

Suggested Citation

  • 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.
    • Handle: RePEc:eth:wpswif:13-181
    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-13-181.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    2. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    3. Kenneth Gillingham & Richard G. Newell & Karen Palmer, 2009. "Energy Efficiency Economics and Policy," Annual Review of Resource Economics, Annual Reviews, vol. 1(1), pages 597-620, September.
    4. Efthymios G. Tsionas & Subal C. Kumbhakar, 2014. "FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY: A GENERALIZED TRUE RANDOM‐EFFECTS model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 110-132, January.
    5. 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.
    6. 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.
    7. 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.
    8. Massimo Filippini, 1999. "Swiss residential demand for electricity," Applied Economics Letters, Taylor & Francis Journals, vol. 6(8), pages 533-538.
    9. Jimenez, Raul & Mercado, Jorge, 2014. "Energy intensity: A decomposition and counterfactual exercise for Latin American countries," Energy Economics, Elsevier, vol. 42(C), pages 161-171.
    10. 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.
    11. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    12. 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.
    13. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    14. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    15. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    16. Bossanyi, Ervin, 1979. "UK primary energy consumption and the changing structure of final demand," Energy Policy, Elsevier, vol. 7(3), pages 253-258, September.
    17. 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.
    18. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters, in: Lester C. Hunt (ed.), Energy in a Competitive Market, chapter 9, Edward Elgar Publishing.
    19. Sudarshan, Anant, 2013. "Deconstructing the Rosenfeld curve: Making sense of California's low electricity intensity," Energy Economics, Elsevier, vol. 39(C), pages 197-207.
    20. Roger Fouquet (ed.), 2013. "Handbook on Energy and Climate Change," Books, Edward Elgar Publishing, number 14429.
    21. 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.
    22. Marvin J. Horowitz, 2007. "Changes in Electricity Demand in the United States from the 1970s to 2003," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 93-120.
    23. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    24. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    25. Joanne Evans & Lester C. Hunt (ed.), 2009. "International Handbook on the Economics of Energy," Books, Edward Elgar Publishing, number 12764.
    26. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2006. "Cost Efficiency in Regional Bus Companies: An Application of Alternative Stochastic Frontier Models," Journal of Transport Economics and Policy, University of Bath, vol. 40(1), pages 95-118, January.
    27. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    28. Stijn Reinhard & C.A. Knox Lovell & Geert Thijssen, 1999. "Econometric Estimation of Technical and Environmental Efficiency: An Application to Dutch Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(1), pages 44-60.
    29. A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
    30. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    31. 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.
    32. 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.
    33. Gale A. Boyd and Joseph M. Roop, 2004. "A Note on the Fisher Ideal Index Decomposition for Structural Change in Energy Intensity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 87-102.
    34. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    35. 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.
    36. Ang, B.W., 2006. "Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index," Energy Policy, Elsevier, vol. 34(5), pages 574-582, March.
    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. Chenyu Lu & Peng Meng & Xueyan Zhao & Lu Jiang & Zilong Zhang & Bing Xue, 2019. "Assessing the Economic-Environmental Efficiency of Energy Consumption and Spatial Patterns in China," Sustainability, MDPI, vol. 11(3), pages 1-17, January.
    2. Arik Levinson, 2017. "Energy Intensity: Prices, Policy, or Composition in US States," Development Working Papers 414, Centro Studi Luca d'Agliano, University of Milano.
    3. Turki Alajmi & Patrick Phelan, 2020. "Modeling and Forecasting End-Use Energy Consumption for Residential Buildings in Kuwait Using a Bottom-Up Approach," Energies, MDPI, vol. 13(8), pages 1-19, April.
    4. 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.
    5. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    6. Sergej Vojtovic & Alina Stundziene & Rima Kontautiene, 2018. "The Impact of Socio-Economic Indicators on Sustainable Consumption of Domestic Electricity in Lithuania," Sustainability, MDPI, vol. 10(2), pages 1-21, January.
    7. Mohammad Imdadul Haque, 2021. "Oil price shocks and energy consumption in GCC countries: a system-GMM approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 9336-9351, June.
    8. Aam S. Rusydiana & Nisful Laila & Naelati Tubastuvi & Mohamad Andri Ibrahim & Lina Marlina, 2021. "Energy Efficiency in OIC Countries: SDG 7 Output," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 74-81.
    9. Nisful Laila & Aam S. Rusydiana & Muhamad Iqbal Irfany & Imron HR & Popon Srisusilawati & Muhamad Taqi, 2021. "Energy Economics in Islamic Countries: A Bibliometric Review," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 88-95.
    10. Macharia, Kenneth Kigundu & Gathiaka, John Kamau & Ngui, Dianah, 2022. "Energy efficiency in the Kenyan manufacturing sector," Energy Policy, Elsevier, vol. 161(C).
    11. Massimo Filippini & Luis Orea, 2014. "Applications of the stochastic frontier approach in Energy Economics," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 35-42.
    12. Ricardo F. Díaz & Blanca Sanchez-Robles, 2020. "Non-Parametric Analysis of Efficiency: An Application to the Pharmaceutical Industry," Mathematics, MDPI, vol. 8(9), pages 1-27, September.
    13. Massimo Filippini & Lin Zhang, 2013. "Measurement of the “Underlying energy efficiency” in Chinese provinces," CER-ETH Economics working paper series 13/183, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.

    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. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    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. 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.
    4. 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.
    5. 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.
    6. Victor von Loessl & Heike Wetzel, 2019. "Revenue decoupling and energy consumption: Empirical evidence from the U.S. electric utilities sector," MAGKS Papers on Economics 201918, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. 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.
    8. 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.
    9. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.
    10. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    11. Zhang, Lin, 2017. "Correcting the uneven burden sharing of emission reduction across provinces in China," Energy Economics, Elsevier, vol. 64(C), pages 335-345.
    12. Joanne Evans & Massimo Filippini & Lester C Hunt, 2011. "Measuring energy efficiency and its contribution towards meeting CO2 targets: estimates for 29 OECD countries," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 135, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    13. Tajudeen, Ibrahim A., 2021. "The underlying drivers of economy-wide energy efficiency and asymmetric energy price responses," Energy Economics, Elsevier, vol. 98(C).
    14. 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).
    15. Romero-Jordán, Desiderio & del Río, Pablo, 2022. "Analysing the drivers of the efficiency of households in electricity consumption," Energy Policy, Elsevier, vol. 164(C).
    16. 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).
    17. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.
    18. 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.
    19. Llorca, Manuel & Baños, José & Somoza, José & Arbués, Pelayo, 2014. "A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean," Efficiency Series Papers 2014/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    20. 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.

    More about this item

    Keywords

    US total energy demand; efficiency and frontier analysis; state energy efficiency;
    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:13-181. 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.