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

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  • Dagher, Leila

Abstract

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.

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  • 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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    9. Halim TATLI, 2022. "Long-term price and income elasticity of residential natural gas demand in Turkey," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(630), S), pages 101-122, Spring.
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    13. 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.
    14. Christopher Hannum, 2023. "Effect of Natural Gas Prices on Renewable Portfolio Standard Impacts," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 391-403, March.
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    16. Lin, Boqiang & Li, Zhensheng, 2020. "Analysis of the natural gas demand and subsidy in China: A multi-sectoral perspective," Energy, Elsevier, vol. 202(C).
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    19. Mustafa Akpinar & Nejat Yumusak, 2016. "Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods," Energies, MDPI, vol. 9(9), pages 1-17, September.
    20. 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.
    21. 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.
    22. 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.
    23. Ju-Hee Kim & Byoung-Soh Hwang & Seung-Hoon Yoo, 2022. "Estimating the Demand Function for Residential City Gas in South Korea: Findings from a Price Sensitivity Measurement Experiment," Sustainability, MDPI, vol. 14(12), pages 1-13, June.
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    More about this item

    Keywords

    Dynamic elasticities; ADL; Natural gas demand; Colorado;
    All these keywords.

    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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