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US residential energy demand and energy efficiency: A stochastic demand frontier approach

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  • Filippini, Massimo
  • Hunt, Lester C.

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 modeled 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

Article provided by Elsevier in its journal Energy Economics.

Volume (Year): 34 (2012)
Issue (Month): 5 ()
Pages: 1484-1491

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Handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1484-1491

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Web page: http://www.elsevier.com/locate/eneco

Related research

Keywords: US residential energy demand; Efficiency and frontier analysis; State energy efficiency;

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References

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Citations

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Cited by:
  1. 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.
  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. 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.
  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. 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. Ricardo Fenochietto & Carola Pessino, 2013. "Understanding Countries’ Tax Effort," IMF Working Papers 13/244, International Monetary Fund.
  7. 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.
  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. 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.

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