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Response of Residential Electricity Demand to Price: The Effect of Measurement Error

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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)

  • Anna Alberini

    ()
    (Department of Agricultural Economics, university of Maryland, US and Centre for Energy Policy and Economics (CEPE), ETH Zurich, Switzerland)

Abstract

In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. We estimate a dynamic partial adjustment model using the Kiviet corrected LSDV (1995) and the Blundell-Bond (1998) estimators. In addition to the lagged dependent variable, our equation includes energy prices, income, cooling and heating degree days, and average household size. We find that the short-run own price elasticity of consumption is similar across LDSV, bias-corrected LSDV and the variant of the Blundell-Bond where we instrument for price. The short-run elasticity is the lowest when we use the Blundell-Bond GMM approach that treats the price of electricity as exogenous. The long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LDSV is greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell-Bond estimator where we instrument for price imply that there is room, in an electricity system mainly based on coal and gas power plants, for discouraging residential electricity consumption and curbing greenhouse gas emissions by imposing a carbon tax.

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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 10-75.

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Length: 24 pages
Date of creation: Jul 2010
Date of revision:
Handle: RePEc:cee:wpcepe:10-75

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Keywords: residential electricity and gas demand; US states; panel data; dynamic panel data models; partial adjustment model;

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References

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  1. Giovanni S.F. Bruno, 2004. "Approximating the Bias of the LSDV Estimator for Dynamic Unbalanced Panel Data Models," KITeS Working Papers 159, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Jul 2004.
  2. Black, Dan A & Kniesner, Thomas J, 2003. " On the Measurement of Job Risk in Hedonic Wage Models," Journal of Risk and Uncertainty, Springer, vol. 27(3), pages 205-20, December.
  3. A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, April.
  4. Massimo Filippini, 1999. "Swiss residential demand for electricity," Applied Economics Letters, Taylor & Francis Journals, vol. 6(8), pages 533-538.
  5. Paul, Anthony & Myers, Erica & Palmer, Karen, 2009. "A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector," Discussion Papers dp-08-50, Resources For the Future.
  6. Anna Alberini & Will Gans & Daniel Velez-Lopez, 2011. "Residential Consumption of Gas and Electricity in the U.S.: The Role of Prices and Income," Working Papers 2011.01, Fondazione Eni Enrico Mattei.
  7. Espey, James A. & Espey, Molly, 2004. "Turning on the Lights: A Meta-Analysis of Residential Electricity Demand Elasticities," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(01), April.
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  16. Massimo Filippini, 2010. "Short and long-run time-of-use price elasticities in Swiss residential electricity demand," CEPE Working paper series 10-76, CEPE Center for Energy Policy and Economics, ETH Zurich.
  17. Kazuhiko Hayakawa, 2005. "Small Sample Bias Propreties of the System GMM Estimator in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d05-82, Institute of Economic Research, Hitotsubashi University.
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  21. Fell, Harrison & Li, Shanjun & Paul, Anthony, 2010. "A New Look at Residential Electricity Demand Using Household Expenditure Data," Discussion Papers dp-10-57, Resources For the Future.
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  24. Haas, Reinhard & Schipper, Lee, 1998. "Residential energy demand in OECD-countries and the role of irreversible efficiency improvements," Energy Economics, Elsevier, vol. 20(4), pages 421-442, September.
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Citations

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Cited by:
  1. Blázquez Gomez, Leticia M. & Filippini, Massimo & Heimsch, Fabian, 2013. "Regional impact of changes in disposable income on Spanish electricity demand: A spatial econometric analysis," Energy Economics, Elsevier, vol. 40(S1), pages S58-S66.
  2. 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.
  3. Torriti, Jacopo, 2013. "The significance of occupancy steadiness in residential consumer response to Time-of-Use pricing: Evidence from a stochastic adjustment model," Utilities Policy, Elsevier, vol. 27(C), pages 49-56.
  4. Okajima, Shigeharu & Okajima, Hiroko, 2013. "Estimation of Japanese price elasticities of residential electricity demand, 1990–2007," Energy Economics, Elsevier, vol. 40(C), pages 433-440.
  5. Blazquez Leticia & Nina Boogen & Massimo Filippini, 2012. "Residential electricity demand for Spain: new empirical evidence using aggregated data," CEPE Working paper series 12-82, CEPE Center for Energy Policy and Economics, ETH Zurich.

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