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Estimating Consumer Energy Demand Using International Data: Theoretical and Policy Implications

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  • Dale S. Rothman
  • J. Ho Hong
  • Timothy D. Mount

Abstract

In this paper, consumer energy demand is estimated as part of a complete demand system using a consistent set of international data on prices, and expenditures for 53 countries ranging from the poorest to the wealthiest. We compare three models: the Translog, the Deaton-Muellbauer Almost Ideal! Demand System (DM), and the Generalized Logit (Logit), and two levels of commodity aggregation (6-good and 9-good). The estimation results indicate that the model specification and level of aggregation are important. The Logit model performs better than the Translog and D-M models which provide illogical! elasticity estimates for many countries. The 9-good model shows that the demand for electricity is significantly more price and income elastic than the demand for primary energy.

Suggested Citation

  • Dale S. Rothman & J. Ho Hong & Timothy D. Mount, 1994. "Estimating Consumer Energy Demand Using International Data: Theoretical and Policy Implications," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 67-88.
  • Handle: RePEc:aen:journl:1994v15-02-a04
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    Cited by:

    1. Narayan, Paresh Kumar & Smyth, Russell, 2007. "A panel cointegration analysis of the demand for oil in the Middle East," Energy Policy, Elsevier, vol. 35(12), pages 6258-6265, December.
    2. Zhang, Xiaobo & Mount, Timothy D. & Boisvert, Richard N., 2001. "The Demand For Food Grain In China : New Insights Into A Controversy," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 30(1), April.
    3. Xavier Labandeira & Baltazar Manzano, 2012. "Some Economic Aspects of Energy Security," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 47-64.
    4. Nourah Al Yousef, 2013. "Demand for Oil Products in OPEC Countries: A Panel Cointegration Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 3(2), pages 168-177.
    5. repec:ers:journl:v:xv:y:2012:i:sie:p:47-64 is not listed on IDEAS
    6. Berkhout, Peter H. G. & Ferrer-i-Carbonell, Ada & Muskens, Jos C., 2004. "The ex post impact of an energy tax on household energy demand," Energy Economics, Elsevier, vol. 26(3), pages 297-317, May.
    7. Dumagan, Jesus C. & Mount, Timothy D., 1996. "Global properties of well-behaved demand systems: A generalized logit model specification," Economic Modelling, Elsevier, vol. 13(2), pages 235-256, April.
    8. Olatubi, Williams O. & Zhang, Yan, 2003. "A Dynamic Estimation of Total Energy Demand for the Southern States," The Review of Regional Studies, Southern Regional Science Association, vol. 33(2), pages 206-228.
    9. Seale, James L. & Solano, Alexis A., 2012. "The changing demand for energy in rich and poor countries over 25years," Energy Economics, Elsevier, vol. 34(6), pages 1834-1844.
    10. Castro Martins, Maria Lurdes, 2003. "International differences in telecommunications demand," Information Economics and Policy, Elsevier, vol. 15(3), pages 291-303, September.
    11. Dumagan, Jesus C. & Mount, Timothy D., 1997. "Approximating compensated income from ordinary demand functions1," Economics Letters, Elsevier, vol. 55(2), pages 191-201, August.

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    JEL classification:

    • F0 - International Economics - - General

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