IDEAS home Printed from https://ideas.repec.org/a/ksp/journ1/v3y2016i1p134-141.html
   My bibliography  Save this article

Decomposition of Natural Gas Intensity in Energy-Intensive Industries in Iran

Author

Listed:
  • Lotfali AGHELI
  • Fatemeh ABDI

    (Tarbiat Modares University, Iran.)

Abstract

Natural gas is main energy carrier used across industrial sector in Iran. The macro-level policy is to substitute natural gas for other oil products due to environmental and economic impacts. In this article, the natural gas intensity in energy-intensive industries is decomposed into output, structural and pure intensity effects in Iran during the period 1971 to 2011. The increasing share of value added as a proxy for structural changes represents a significant impact on reducing natural gas intensity. The output effect is of the high estmagnitude in changing natural gas consumption, and the pure intensity and structural effects rank the second and third in terms of the overall change in natural gas use, respectively.

Suggested Citation

  • Lotfali AGHELI & Fatemeh ABDI, 2016. "Decomposition of Natural Gas Intensity in Energy-Intensive Industries in Iran," Journal of Economics and Political Economy, KSP Journals, vol. 3(1), pages 134-141, March.
    • Handle: RePEc:ksp:journ1:v:3:y:2016:i:1:p:134-141
    as

    Download full text from publisher

    File URL: http://www.kspjournals.org/index.php/JEPE/article/download/643/795
    Download Restriction: no
    File URL: http://www.kspjournals.org/index.php/JEPE/article/view/643
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huntington, Hillard G., 2007. "Industrial natural gas consumption in the United States: An empirical model for evaluating future trends," Energy Economics, Elsevier, vol. 29(4), pages 743-759, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Soltanisarvestani, A. & Safavi, A.A., 2021. "Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map," Utilities Policy, Elsevier, vol. 72(C).
    3. Whistance, Jarrett & Thompson, Wyatt, 2010. "How does increased corn-ethanol production affect US natural gas prices?," Energy Policy, Elsevier, vol. 38(5), pages 2315-2325, May.
    4. Anis Hoayek & Hassan Hamie & Hans Auer, 2020. "Modeling the Price Stability and Predictability of Post Liberalized Gas Markets Using the Theory of Information," Energies, MDPI, vol. 13(11), pages 1-20, June.
    5. Peñasco, Cristina & del Río, Pablo & Romero-Jordán, Desiderio, 2017. "Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators," Utilities Policy, Elsevier, vol. 45(C), pages 45-60.
    6. Gatfaoui, Hayette, 2015. "Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas," Energy Policy, Elsevier, vol. 87(C), pages 270-283.
    7. Potočnik, Primož & Soldo, Božidar & Šimunović, Goran & Šarić, Tomislav & Jeromen, Andrej & Govekar, Edvard, 2014. "Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia," Applied Energy, Elsevier, vol. 129(C), pages 94-103.
    8. 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.
    9. Jarrett Whistance & Wyatt W. Thompson & Seth D. Meyer, 2010. "Ethanol Policy Effects on U.S. Natural Gas Prices and Quantities," American Economic Review, American Economic Association, vol. 100(2), pages 178-182, May.
    10. Feijoo, Felipe & Huppmann, Daniel & Sakiyama, Larissa & Siddiqui, Sauleh, 2016. "North American natural gas model: Impact of cross-border trade with Mexico," Energy, Elsevier, vol. 112(C), pages 1084-1095.
    11. Palma, Alessia & Paltrinieri, Andrea & Goodell, John W. & Oriani, Marco Ercole, 2024. "The black box of natural gas market: Past, present, and future," International Review of Financial Analysis, Elsevier, vol. 94(C).
    12. Huntington, Hillard G., 2010. "Short- and long-run adjustments in U.S. petroleum consumption," Energy Economics, Elsevier, vol. 32(1), pages 63-72, January.
    13. Anis Hoayek & Hassan Hamie & Hans Auer, 2020. "Modeling the Price Stability and Predictability of Post Liberalized Gas Markets Using the Theory of Information," Post-Print emse-03604655, HAL.
    14. Li, Raymond & Woo, Chi-Keung & Tishler, Asher & Zarnikau, Jay, 2022. "Price responsiveness of commercial demand for natural gas in the US," Energy, Elsevier, vol. 256(C).
    15. Greening, Lorna A. & Boyd, Gale & Roop, Joseph M., 2007. "Modeling of industrial energy consumption: An introduction and context," Energy Economics, Elsevier, vol. 29(4), pages 599-608, July.
    16. Jean Gaston Tamba & Salom Ndjakomo Essiane & Emmanuel Flavian Sapnken & Francis Djanna Koffi & Jean Luc Nsouand l & Bozidar Soldo & Donatien Njomo, 2018. "Forecasting Natural Gas: A Literature Survey," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 216-249.
    17. Bruno R. Delaribera & Rafael SerranoQuintero & Guilherme G. Zimmermann, 2023. "Reforms in the Natural Gas Sector and Economic Development," UB School of Economics Working Papers 2023/446, University of Barcelona School of Economics.
    18. Federico Scarpa & Vincenzo Bianco, 2017. "Assessing the Quality of Natural Gas Consumption Forecasting: An Application to the Italian Residential Sector," Energies, MDPI, vol. 10(11), pages 1-13, November.
    19. Bertrand, Jean-Louis & Parnaudeau, Miia, 2019. "Understanding the economic effects of abnormal weather to mitigate the risk of business failures," Journal of Business Research, Elsevier, vol. 98(C), pages 391-402.
    20. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.

    More about this item

    Keywords

    Decomposition; Output effect; Structural effect; Energy-intensive manufacturing sector.;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ksp:journ1:v:3:y:2016:i:1:p:134-141. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bilal KARGI (email available below). General contact details of provider: http://www.kspjournals.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.