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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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    6. Zhang, Yi & Ji, Qiang & Fan, Ying, 2018. "The price and income elasticity of China's natural gas demand: A multi-sectoral perspective," Energy Policy, Elsevier, vol. 113(C), pages 332-341.
    7. 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.
    8. Ieva Meidute-Kavaliauskiene & Vida Davidaviciene & Shahryar Ghorbani & Iman Ghasemian Sahebi, 2021. "Optimal Allocation of Gas Resources to Different Consumption Sectors Using Multi-Objective Goal Programming," Sustainability, MDPI, vol. 13(10), pages 1-19, May.
    9. Mohamed Jaouad Malzi & Aziz Ettahir & Sa d Hanchane, 2019. "Responsiveness of Residential Natural Gas Demand to Elderly, Urban Population and Density: Evidence from Organization for Economic Co-operation and Development Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 388-395.
    10. 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.
    11. John T. Cuddington & Leila Dagher, 2015. "Estimating Short and Long-Run Demand Elasticities: A Primer with Energy-Sector Applications," The Energy Journal, , vol. 36(1), pages 185-210, January.
    12. 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.
    13. 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.
    14. 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.
    15. Fen Li & Cunyi Yang & Zhenghui Li & Pierre Failler, 2021. "Does Geopolitics Have an Impact on Energy Trade? Empirical Research on Emerging Countries," Sustainability, MDPI, vol. 13(9), pages 1-24, May.
    16. 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.
    17. Gautam, Tej K. & Paudel, Krishna P., 2018. "The demand for natural gas in the Northeastern United States," Energy, Elsevier, vol. 158(C), pages 890-898.
    18. 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.
    19. 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 / Editura Economica, vol. 0(1(630), S), pages 101-122, Spring.
    20. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    21. 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.
    22. Beecher, Janice & Gould, Tom, 2018. "Pricing wastewater to save water: Are theory and practice transferable?," Utilities Policy, Elsevier, vol. 52(C), pages 81-87.
    23. 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.
    24. Malzi, Mohamed Jaouad & Sohag, Kazi & Vasbieva, Dinara G. & Ettahir, Aziz, 2020. "Environmental policy effectiveness on residential natural gas use in OECD countries," Resources Policy, Elsevier, vol. 66(C).
    25. 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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    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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