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Response of residential electricity demand to price: The effect of measurement error

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  • Alberini, Anna
  • Filippini, Massimo

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. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell-Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LSDV are 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 a carbon tax or other price-based policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants.

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  • Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
  • Handle: RePEc:eee:eneeco:v:33:y:2011:i:5:p:889-895
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    1. 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(1), pages 1-17, April.
    2. Massimo Filippini, 1999. "Swiss residential demand for electricity," Applied Economics Letters, Taylor & Francis Journals, vol. 6(8), pages 533-538.
    3. Fell, Harrison & Li, Shanjun & Paul, Anthony, 2014. "A new look at residential electricity demand using household expenditure data," International Journal of Industrial Organization, Elsevier, vol. 33(C), pages 37-47.
    4. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
    5. 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.
    6. Bruno, Giovanni S.F., 2005. "Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models," Economics Letters, Elsevier, vol. 87(3), pages 361-366, June.
    7. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    8. Halvorsen, Robert, 1975. "Residential Demand for Electric Energy," The Review of Economics and Statistics, MIT Press, vol. 57(1), pages 12-18, February.
    9. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    10. Shin, Jeong-Shik, 1985. "Perception of Price When Price Information Is Costly: Evidence from Residential Electricity Demand," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 591-598, November.
    11. Filippini, Massimo, 1995. "Swiss residential demand for electricity by time-of-use," Resource and Energy Economics, Elsevier, vol. 17(3), pages 281-290, November.
    12. 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.
    13. Massimo, Filippini, 2011. "Short- and long-run time-of-use price elasticities in Swiss residential electricity demand," Energy Policy, Elsevier, vol. 39(10), pages 5811-5817, October.
    14. 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 205-220, December.
    15. Hayakawa, Kazuhiko, 2007. "Small sample bias properties of the system GMM estimator in dynamic panel data models," Economics Letters, Elsevier, vol. 95(1), pages 32-38, April.
    16. 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.
    17. Flaig, Gebhard, 1990. "Household production and the short- and long-run demand for electricity," Energy Economics, Elsevier, vol. 12(2), pages 116-121, April.
    18. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053.
    19. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 853-883.
    20. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    21. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    22. A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, March.
    23. Kamerschen, David R. & Porter, David V., 2004. "The demand for residential, industrial and total electricity, 1973-1998," Energy Economics, Elsevier, vol. 26(1), pages 87-100, January.
    24. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    25. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762.
    26. Hendrik S. Houthakker, 1980. "Residential Electricity Revisited," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    27. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
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    More about this item

    Keywords

    Residential electricity Gas demand US states Panel data Dynamic panel data models Partial adjustment model;

    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

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