IDEAS home Printed from https://ideas.repec.org/p/sek/iacpro/2804383.html
   My bibliography  Save this paper

An Estimation of Natural Gas Demand in Household Sector of Iran; the Structural Time Series Approach

Author

Listed:
  • Mir Hossein Mousavi

    (Alzahra University)

Abstract

Natural gas is one of the most important energy for household sector in entire the world. Iran has rich gas reserves and after Russia, Iran has the largest natural gas reserves in entire the world. A study of natural gas demand is very important and crucial for policy makers of energy sources in Iran. With a good estimation of natural gas demand as a result a good forecasting of natural gas demand, policy makers of energy sources can to plan an accurate energy planning. The aim of this paper is analyzing the effective factors on natural gas demand in household sector of Iran. For do it, we have used structural time series method with Kalman Filter algorithm during 1974-2010 period. Results indicate that time trend as a proxy for technology and non-economic factors is non-linear process and the elasticity of demand to price of natural gas is -0.50. Also, the elasticity of natural gas demand to price of electricity as a substitute commodity for natural gas is 0.48. The elasticity of gas demand to gas splits and real GDP per capita is 2.37 and 0.72 respectively. Conclusion: The elasticity of demand to price of natural gas is -0.50 that it shows that natural gas is an essential commodity for household sector in Iran.

Suggested Citation

  • Mir Hossein Mousavi, 2015. "An Estimation of Natural Gas Demand in Household Sector of Iran; the Structural Time Series Approach," Proceedings of International Academic Conferences 2804383, International Institute of Social and Economic Sciences.
  • Handle: RePEc:sek:iacpro:2804383
    as

    Download full text from publisher

    File URL: https://iises.net/proceedings/19th-international-academic-conference-florence/table-of-content/detail?cid=28&iid=092&rid=4383
    File Function: First version, 2015
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sun, Mei & Wang, Xiaofang & Chen, Ying & Tian, Lixin, 2011. "Energy resources demand-supply system analysis and empirical research based on non-linear approach," Energy, Elsevier, vol. 36(9), pages 5460-5465.
    2. Majid Ahmadian & Mona Chitnis & Lester C. Hunt, 2007. "Gasoline demand, pricing policy and social welfare in the Islamic Republic of Iran," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 31(2), pages 105-124, June.
    3. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    4. Dongfeng Chang & Apostolos Serletis, 2014. "The Demand For Gasoline: Evidence From Household Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 291-313, March.
    5. Azadeh, A. & Asadzadeh, S.M. & Ghanbari, A., 2010. "An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments," Energy Policy, Elsevier, vol. 38(3), pages 1529-1536, March.
    6. Sun, Mei & Zhang, Pei-Pei & Shan, Tian-Hua & Fang, Cui-Cui & Wang, Xiao-Fang & Tian, Li-Xin, 2012. "Research on the evolution model of an energy supply–demand network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(19), pages 4506-4516.
    7. Yoo, Seung-Hoon & Lim, Hea-Jin & Kwak, Seung-Jun, 2009. "Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias," Applied Energy, Elsevier, vol. 86(4), pages 460-465, April.
    8. Athukorala, P.P.A Wasantha & Wilson, Clevo, 2010. "Estimating short and long-term residential demand for electricity: New evidence from Sri Lanka," Energy Economics, Elsevier, vol. 32(Supplemen), pages 34-40, September.
    9. Payne, James E. & Loomis, David G. & Wilson, Renardo, 2011. "Residential Natural Gas Demand in Illinois: Evidence from the ARDL Bounds Testing Approach," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 41(2), pages 1-10.
    10. repec:ags:jrapmc:133220 is not listed on IDEAS
    11. Majid Ahmadian & Mona Chitnis & Lester C Hunt, 2007. "Gasoline Demand, Pricing Policy and Social Welfare in Iran," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 117, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    12. Murata, Akinobu & Kondou, Yasuhiko & Hailin, Mu & Weisheng, Zhou, 2008. "Electricity demand in the Chinese urban household-sector," Applied Energy, Elsevier, vol. 85(12), pages 1113-1125, December.
    13. Aydinalp-Koksal, Merih & Ugursal, V. Ismet, 2008. "Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector," Applied Energy, Elsevier, vol. 85(4), pages 271-296, April.
    14. Bhattacharyya, Subhes C. & Timilsina, Govinda R., 2009. "Energy demand models for policy formulation : a comparative study of energy demand models," Policy Research Working Paper Series 4866, The World Bank.
    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. 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.
    2. 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.
    3. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
    4. Sen, Doruk & Günay, M. Erdem & Tunç, K.M. Murat, 2019. "Forecasting annual natural gas consumption using socio-economic indicators for making future policies," Energy, Elsevier, vol. 173(C), pages 1106-1118.
    5. Khan, Muhammad Arshad, 2015. "Modelling and forecasting the demand for natural gas in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1145-1159.
    6. Fakhri J. Hasanov & Jeyhun I. Mikayilov, 2020. "Revisiting Energy Demand Relationship: Theory and Empirical Application," Sustainability, MDPI, vol. 12(7), pages 1-15, April.
    7. 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.
    8. Muhammad Atta-ul-Islam Abrar & Muhsin Ali & Uzma Bashir & Karim Khan, 2019. "Energy Pricing Policies and Consumers’ Welfare: Evidence from Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 24(1), pages 1-28, Jan-June.
    9. Raghoo, Pravesh & Surroop, Dinesh, 2020. "Price and income elasticities of oil demand in Mauritius: An empirical analysis using cointegration method," Energy Policy, Elsevier, vol. 140(C).
    10. Parajuli, Ranjan & Østergaard, Poul Alberg & Dalgaard, Tommy & Pokharel, Govind Raj, 2014. "Energy consumption projection of Nepal: An econometric approach," Renewable Energy, Elsevier, vol. 63(C), pages 432-444.
    11. Mohamad Taghvaee, Vahid & Hajiani, Parviz, 2014. "Price and Income Elasticities of Gasoline Demand in Iran: Using Static, ECM, and Dynamic Models in Short, Intermediate, and Long Run," MPRA Paper 70054, University Library of Munich, Germany.
    12. Wadud, Zia & Dey, Himadri S. & Kabir, Md. Ashfanoor & Khan, Shahidul I., 2011. "Modeling and forecasting natural gas demand in Bangladesh," Energy Policy, Elsevier, vol. 39(11), pages 7372-7380.
    13. Azadeh, A. & Babazadeh, R. & Asadzadeh, S.M., 2013. "Optimum estimation and forecasting of renewable energy consumption by artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 605-612.
    14. Aldubyan, Mohammad & Gasim, Anwar, 2021. "Energy price reform in Saudi Arabia: Modeling the economic and environmental impacts and understanding the demand response," Energy Policy, Elsevier, vol. 148(PB).
    15. Adeyemi, Olutomi I. & Broadstock, David C. & Chitnis, Mona & Hunt, Lester C. & Judge, Guy, 2010. "Asymmetric price responses and the underlying energy demand trend: Are they substitutes or complements? Evidence from modelling OECD aggregate energy demand," Energy Economics, Elsevier, vol. 32(5), pages 1157-1164, September.
    16. Jumah Ahmad Alzyadat, 2022. "The Price and Income Elasticity of Demand for Natural Gas Consumption in Saudi Arabia," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 357-363, November.
    17. Sa'ad, Suleiman, 2009. "An empirical analysis of petroleum demand for Indonesia: An application of the cointegration approach," Energy Policy, Elsevier, vol. 37(11), pages 4391-4396, November.
    18. Di Leo, Senatro & Caramuta, Pietro & Curci, Paola & Cosmi, Carmelina, 2020. "Regression analysis for energy demand projection: An application to TIMES-Basilicata and TIMES-Italy energy models," Energy, Elsevier, vol. 196(C).
    19. Azadeh, A. & Asadzadeh, S.M. & Mirseraji, G.H. & Saberi, M., 2015. "An emotional learning-neuro-fuzzy inference approach for optimum training and forecasting of gas consumption estimation models with cognitive data," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 47-63.
    20. Gately, Dermot & Al-Yousef, Nourah & Al-Sheikh, Hamad M.H., 2013. "The rapid growth of OPEC′s domestic oil consumption," Energy Policy, Elsevier, vol. 62(C), pages 844-859.

    More about this item

    Keywords

    Gas Demand; Household Sector; Structural Time Series; Kalman Filter;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • D19 - Microeconomics - - Household Behavior - - - Other

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:sek:iacpro:2804383. 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: Klara Cermakova (email available below). General contact details of provider: https://iises.net/ .

    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.