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US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach

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  • Massimo Filippini

    ()
    (Centre for Energy Policy and Economics (CEPE), Department of Management, Technology and Economics, ETH Zurich and Department of Economics, University of Lugano, Switzerland)

  • Lester Hunt

    ()
    (Department of Economics, University of Surrey, UK)

Abstract

This paper estimates a US frontier residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2007 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in)efficiency of each state is modelled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.

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Bibliographic Info

Paper provided by CEPE Center for Energy Policy and Economics, ETH Zurich in its series CEPE Working paper series with number 12-83.

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Length: 25 pages
Date of creation: Apr 2012
Date of revision:
Handle: RePEc:cee:wpcepe:12-83

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Keywords: US residential energy demand; efficiency and frontier analysis; state energy efficiency;

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References

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  1. Hunt, L.C. & Judge, G. & Ninomiya, Y., 2000. "Underlying Trends and Seasonality in UK Energy Demands: A Sectorial Analysis," Papers 134, Portsmouth University - Department of Economics.
  2. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2005. "Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2127-2141.
  3. 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.
  4. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, 01.
  5. Silvia Banfi & Massimo Filippini & Lester C. Hunt, 2003. "Fuel tourism in border regions," CEPE Working paper series 03-23, CEPE Center for Energy Policy and Economics, ETH Zurich.
  6. Olutomi I Adeyemi & Lester C. Hunt, 2006. "Modelling OECD Industrial Energy Demand: Asymmetric Price Responses and Energy – Saving Technical Change," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 115, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
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  16. Massimo Filippini & Lester Hunt, 2009. "Energy demand and energy efficiency in the OECD countries: a stochastic demand frontier approach," CEPE Working paper series 09-68, CEPE Center for Energy Policy and Economics, ETH Zurich.
  17. Mehdi Farsi & Massimo Filippini & William Greene, 2004. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," CEPE Working paper series 04-32, CEPE Center for Energy Policy and Economics, ETH Zurich.
  18. Banfi, Silvia & Filippini, Massimo & Hunt, Lester C., 2005. "Fuel tourism in border regions: The case of Switzerland," Energy Economics, Elsevier, vol. 27(5), pages 689-707, September.
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  20. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  21. 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.
  22. 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.
  23. 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.
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  25. 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, London School of Economics and University of Bath, vol. 40(1), pages 95-118, January.
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Citations

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Cited by:
  1. Massimo Filippini & Lester C Hunt, 2010. "US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 130, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
  2. Rabindra Nepal & Tooraj Jamasb & Clement Allan Tisdell, 2013. "Market-Related Reforms and Increased Energy Efficiency in Transition Countries: Empirical Evidence," Energy Economics and Management Group Working Papers 8-2013, School of Economics, University of Queensland, Australia.
  3. Massimo Filippini & Elisa Tosetti, 2014. "Stochastic Frontier Models for Long Panel Data Sets: Measurement of the Underlying Energy Efficiency for the OECD Countries," CER-ETH Economics working paper series 14/198, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
  4. 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.
  5. Massimo Filippini & Lester C Hunt & Jelena Zoric, 2013. "Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 139, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
  6. 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.
  7. Rabindra Nepal & Tooraj Jamasb, 2013. "Energy efficiency in Market vs Planned Economies: Evidence from Transition Countries," Cambridge Working Papers in Economics 1345, Faculty of Economics, University of Cambridge.
  8. Wang, H. & Zhou, P. & Zhou, D.Q., 2013. "Scenario-based energy efficiency and productivity in China: A non-radial directional distance function analysis," Energy Economics, Elsevier, vol. 40(C), pages 795-803.
  9. Ricardo Fenochietto & Carola Pessino, 2013. "Understanding Countries’ Tax Effort," IMF Working Papers 13/244, International Monetary Fund.

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