IDEAS home Printed from https://ideas.repec.org/a/eaa/aeinde/v15y2015i1_11.html
   My bibliography  Save this article

Estimating Demand Function For Electricity In Industrial Sector Of Iran Using Structural Time Series Model (Stsm)

Author

Listed:
  • SHIRANI-FAKHR, Zohreh
  • KHOSHAKHLAGH, Rahman
  • SHARIFI, Alimorad

Abstract

This case study estimated an electricity demand function for industrial sector of Iran by applying the structural time series technique to quarterly data for 2000q1-2011q4. In addition to identifying the size and significance of the price and output elasticities, this technique also uncovers UEDT. It is found that the estimated long-run and short-run industrial output elasticities are respectively, 0.85 and 0.36 and the estimated long-run and short-run industrial energy price elasticities are -0.47 and -0.27, respectively. The results suggest that the nature of the trend is not linear and deterministic but stochastic in form. The UEDT for the electricity usage of the industrial sector shows an upward slope.

Suggested Citation

  • SHIRANI-FAKHR, Zohreh & KHOSHAKHLAGH, Rahman & SHARIFI, Alimorad, 2015. "Estimating Demand Function For Electricity In Industrial Sector Of Iran Using Structural Time Series Model (Stsm)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(1), pages 143-160.
  • Handle: RePEc:eaa:aeinde:v:15:y:2015:i:1_11
    as

    Download full text from publisher

    File URL: http://www.usc.es/economet/reviews/aeid15111.pdf
    Download Restriction: No.
    ---><---

    References listed on IDEAS

    as
    1. Lester C Hunt & Guy Judge, 1996. "Evolving Seasonal Patterns In Uk Energy Series," World Scientific Book Chapters, in: G MacKerron & P Pearson (ed.), The Uk Energy Experience A Model or A Warning?, chapter 19, pages 259-270, World Scientific Publishing Co. Pte. Ltd..
    2. Amarawickrama, Himanshu A. & Hunt, Lester C., 2008. "Electricity demand for Sri Lanka: A time series analysis," Energy, Elsevier, vol. 33(5), pages 724-739.
    3. Jones, Clifton T, 1994. "Accounting for technical progress in aggregate energy demand," Energy Economics, Elsevier, vol. 16(4), pages 245-252, October.
    4. Dilaver, Zafer & Hunt, Lester C, 2011. "Modelling and forecasting Turkish residential electricity demand," Energy Policy, Elsevier, vol. 39(6), pages 3117-3127, June.
    5. Claudio Morana, 2000. "Modelling Evolving Long‐run Relationships: An Application to the Italian Energy Market," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 72-93, February.
    6. Beenstock, Michael & Goldin, Ephraim & Nabot, Dan, 1999. "The demand for electricity in Israel," Energy Economics, Elsevier, vol. 21(2), pages 168-183, April.
    7. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters, in: Lester C. Hunt (ed.), Energy in a Competitive Market, chapter 9, Edward Elgar Publishing.
    8. Beenstock, Michael & Wilcocks, Patrick, 1983. "Energy and economic activity: a reply to Kouris," Energy Economics, Elsevier, vol. 5(3), pages 212-212, July.
    9. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    10. Harvey, A C, et al, 1986. "Stochastic Trends in Dynamic Regression Models: An Application to the Employment-Output Equations," Economic Journal, Royal Economic Society, vol. 96(384), pages 975-985, December.
    11. Geller, Howard & Harrington, Philip & Rosenfeld, Arthur H. & Tanishima, Satoshi & Unander, Fridtjof, 2006. "Polices for increasing energy efficiency: Thirty years of experience in OECD countries," Energy Policy, Elsevier, vol. 34(5), pages 556-573, March.
    12. David F. Hendry & Katarina Juselius, 2001. "Explaining Cointegration Analysis: Part II," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-120.
    13. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
    14. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    15. Muhammad, Javid & Abdul, Qayyum, 2013. "Electricity consumption-GDP nexus: A structural time series analysis," MPRA Paper 47448, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Balcilar, Mehmet & Usman, Ojonugwa & Ike, George N., 2023. "Operational behaviours of multinational corporations, renewable energy transition, and environmental sustainability in Africa: Does the level of natural resource rents matter?," Resources Policy, Elsevier, vol. 81(C).
    2. Fakhri J. Hasanov & Zeeshan Khan & Muzzammil Hussain & Muhammad Tufail, 2021. "Theoretical Framework for the Carbon Emissions Effects of Technological Progress and Renewable Energy Consumption," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(5), pages 810-822, September.

    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. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    2. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    3. Dilaver, Zafer & Hunt, Lester C., 2011. "Industrial electricity demand for Turkey: A structural time series analysis," Energy Economics, Elsevier, vol. 33(3), pages 426-436, May.
    4. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters, in: Lester C. Hunt (ed.), Energy in a Competitive Market, chapter 9, Edward Elgar Publishing.
    5. Dilaver, Zafer & Hunt, Lester C, 2011. "Modelling and forecasting Turkish residential electricity demand," Energy Policy, Elsevier, vol. 39(6), pages 3117-3127, June.
    6. Alkhathlan, Khalid & Javid, Muhammad, 2015. "Carbon emissions and oil consumption in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 105-111.
    7. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.
    8. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    9. Dilaver, Zafer & Hunt, Lester C., 2011. "Turkish aggregate electricity demand: An outlook to 2020," Energy, Elsevier, vol. 36(11), pages 6686-6696.
    10. John Dimitropoulos & Lester Hunt & Guy Judge, 2005. "Estimating underlying energy demand trends using UK annual data," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 239-244.
    11. Sa'ad, Suleiman, 2011. "Underlying energy demand trends in South Korean and Indonesian aggregate whole economy and residential sectors," Energy Policy, Elsevier, vol. 39(1), pages 40-46, January.
    12. Olaniyan, Monisola J. & Evans, Joanne, 2014. "The importance of engaging residential energy customers' hearts and minds," Energy Policy, Elsevier, vol. 69(C), pages 273-284.
    13. Sa'ad, Suleiman, 2010. "Improved technical efficiency and exogenous factors in transportation demand for energy: An application of structural time series analysis to South Korean data," Energy, Elsevier, vol. 35(7), pages 2745-2751.
    14. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    15. Maria Jesus Herrerias and Eric Girardin, 2013. "Seasonal Patterns of Energy in China," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    16. Inglesi-Lotz, R., 2011. "The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application," Energy Policy, Elsevier, vol. 39(6), pages 3690-3696, June.
    17. 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.
    18. Hunt, Lester C. & Ryan, David L., 2015. "Economic modelling of energy services: Rectifying misspecified energy demand functions," Energy Economics, Elsevier, vol. 50(C), pages 273-285.
    19. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
    20. Rodrigues, Niágara & Losekann, Luciano & Silveira Filho, Getulio, 2018. "Demand of automotive fuels in Brazil: Underlying energy demand trend and asymmetric price response," Energy Economics, Elsevier, vol. 74(C), pages 644-655.

    More about this item

    Keywords

    Industrial Electricity Demand; Underlying Energy Demand Trend (UEDT); Structural Time Series Model (STSM); Elasticities.;
    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
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

    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:eaa:aeinde:v:15:y:2015:i:1_11. 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: M. Carmen Guisan (email available below). General contact details of provider: http://www.usc.es/economet/eaa.htm .

    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.