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Natural gas demand at the utility level: An application of dynamic elasticities


  • Dagher, Leila


Previous studies provide strong evidence that energy demand elasticities vary across regions and states, arguing in favor of conducting energy demand studies at the smallest unit of observation for which good quality data are readily available, that is the utility level. We use monthly data from the residential sector of Xcel Energy's service territory in Colorado for the period January 1994 to September 2006. Based on a very general Autoregressive Distributed Lag model this paper uses a new approach to simulate the dynamic behavior of natural gas demand and obtain dynamic elasticities. Knowing consumers' response on a unit time basis enables one to answer a number of questions, such as, the length of time needed to reach demand stability. Responses to price and income were found to be much lower–even in the long run–than has been commonly suggested in the literature. Interestingly, we find that the long run equilibrium is reached relatively quickly, around 18months after a change in price or income has occurred, while the literature implies a much longer period for complete adjustments to take place.

Suggested Citation

  • Dagher, Leila, 2012. "Natural gas demand at the utility level: An application of dynamic elasticities," Energy Economics, Elsevier, vol. 34(4), pages 961-969.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:4:p:961-969 DOI: 10.1016/j.eneco.2011.05.010

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    References listed on IDEAS

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    Cited by:

    1. Ishmael Ackah, 2014. "Determinants of natural gas demand in Ghana," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 272-295, September.
    2. Burke, Paul J. & Yang, Hewen, 2016. "The price and income elasticities of natural gas demand: International evidence," Energy Economics, Elsevier, vol. 59(C), pages 466-474.
    3. Gong, Chengzhu & Tang, Kai & Zhu, Kejun & Hailu, Atakelty, 2016. "An optimal time-of-use pricing for urban gas: A study with a multi-agent evolutionary game-theoretic perspective," Applied Energy, Elsevier, vol. 163(C), pages 283-294.
    4. repec:eee:enepol:v:113:y:2018:i:c:p:332-341 is not listed on IDEAS
    5. Valenzuela, Carlos & Valencia, Alelhie & White, Steve & Jordan, Jeffrey A. & Cano, Stephanie & Keating, Jerome & Nagorski, John & Potter, Lloyd B., 2014. "An analysis of monthly household energy consumption among single-family residences in Texas, 2010," Energy Policy, Elsevier, vol. 69(C), pages 263-272.
    6. Mustafa Akpinar & Nejat Yumusak, 2016. "Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods," Energies, MDPI, Open Access Journal, vol. 9(9), pages 1-17, September.
    7. Rowland, Christopher S. & Mjelde, James W. & Dharmasena, Senarath, 2017. "Policy implications of considering pre-commitments in U.S. aggregate energy demand system," Energy Policy, Elsevier, vol. 102(C), pages 406-413.
    8. Li, Lanlan & Gong, Chengzhu & Tian, Shizhong & Jiao, Jianling, 2016. "The peak-shaving efficiency analysis of natural gas time-of-use pricing for residential consumers: Evidence from multi-agent simulation," Energy, Elsevier, vol. 96(C), pages 48-58.
    9. Gautam, Tej & Paudel, Krishna, 2016. "The Demand For Electricity And Natural Gas In The Northeastern United States," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230114, Southern Agricultural Economics Association.
    10. Krauss, Alexander, 2016. "How natural gas tariff increases can influence poverty: Results, measurement constraints and bias," Energy Economics, Elsevier, vol. 60(C), pages 244-254.
    11. Wang, Ting & Lin, Boqiang, 2014. "China's natural gas consumption and subsidies—From a sector perspective," Energy Policy, Elsevier, vol. 65(C), pages 541-551.
    12. repec:eee:eneeco:v:65:y:2017:i:c:p:411-423 is not listed on IDEAS
    13. Galip Altinay & A. Talha Yalta, 2016. "Estimating the evolution of elasticities of natural gas demand: the case of Istanbul, Turkey," Empirical Economics, Springer, vol. 51(1), pages 201-220, August.
    14. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.

    More about this item


    Dynamic elasticities; ADL; Natural gas demand; Colorado;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices


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