IDEAS home Printed from https://ideas.repec.org/p/sur/seedps/117.html
   My bibliography  Save this paper

Gasoline Demand, Pricing Policy and Social Welfare in Iran

Author

Listed:
  • Majid Ahmadian

    (Faculty of Economics, University of Tehran)

  • Mona Chitnis

    (Research Group on Lifestyles, Values and Environment (RESOLVE) & Surrey Energy Economics Centre (SEEC), University of Surrey)

  • Lester C Hunt

    (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey)

Abstract

This study estimates a gasoline demand function for Iran using the structural time series model over the period 1968-2002 and uses it to estimate the change in social welfare for 2003 and 2004 of a higher gasoline price policy. It is found that short and long run demand price elasticities are inelastic, although the response is greater in the long run. Hence, social welfare is estimated to fall because of the higher gasoline price (ceteris paribus). However, allowing all variables in the model to change, social welfare is estimated to increase since the changes in the other variables more than compensate for the negative effects of the policy.

Suggested Citation

  • 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.
    • Handle: RePEc:sur:seedps:117
    as

    Download full text from publisher

    File URL: https://repec.som.surrey.ac.uk/seeds/SEEDS117.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lester C. Hunt & Yasushi Ninomiya, 2003. "Unravelling Trends and Seasonality: A Structural Time Series Analysis of Transport Oil Demand in the UK and Japan," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 63-96.
    2. Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-389, October.
    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. Atalla, Tarek N. & Gasim, Anwar A. & Hunt, Lester C., 2018. "Gasoline demand, pricing policy, and social welfare in Saudi Arabia: A quantitative analysis," Energy Policy, Elsevier, vol. 114(C), pages 123-133.
    2. 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).
    3. Moshiri, Saeed, 2015. "The effects of the energy price reform on households consumption in Iran," Energy Policy, Elsevier, vol. 79(C), pages 177-188.
    4. 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.
    5. 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).
    6. 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.
    7. Aliyu Barde Abdullahi, 2014. "Modeling Petroleum Product Demand in Nigeria Using Structural Time Series Model (STSM) Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 427-441.
    8. 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.
    9. Houri Jafari, H. & Baratimalayeri, A., 2008. "The crisis of gasoline consumption in the Iran's transportation sector," Energy Policy, Elsevier, vol. 36(7), pages 2536-2543, July.
    10. 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.
    11. Kakali Kanjilal & Sajal Ghosh, 2018. "Revisiting income and price elasticity of gasoline demand in India: new evidence from cointegration tests," Empirical Economics, Springer, vol. 55(4), pages 1869-1888, December.
    12. Afshin Ghorbani & Mohammad Reza Rahimpour & Younes Ghasemi & Sona Raeissi, 2018. "The Biodiesel of Microalgae as a Solution for Diesel Demand in Iran," Energies, MDPI, vol. 11(4), pages 1-17, April.
    13. Elaheh Jafarnejad & Ahmad Makui & Ashkan Hafezalkotob & Amir Aghsami, 2024. "Governance intervention policies in the production competition of biofuels and fossil fuels: a pathway to sustainable development," Operations Management Research, Springer, vol. 17(2), pages 660-682, June.
    14. 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).
    15. Nourah Al Yousef, 2013. "Demand for Oil Products in OPEC Countries: A Panel Cointegration Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 3(2), pages 168-177.
    16. 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.
    17. Shamaila Aziz & Muhammad Rizwan Yaseen & Sofia Anwar, 2016. "Impact of Rising Energy Prices on Consumer’s Welfare: A Case Study of Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 55(4), pages 605-618.
    18. 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.

    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. Dilaver, Zafer & Hunt, Lester C, 2011. "Modelling and forecasting Turkish residential electricity demand," Energy Policy, Elsevier, vol. 39(6), pages 3117-3127, June.
    2. Dilaver, Zafer & Hunt, Lester C., 2011. "Turkish aggregate electricity demand: An outlook to 2020," Energy, Elsevier, vol. 36(11), pages 6686-6696.
    3. Ringlund, Guro Bornes & Rosendahl, Knut Einar & Skjerpen, Terje, 2008. "Does oilrig activity react to oil price changes An empirical investigation," Energy Economics, Elsevier, vol. 30(2), pages 371-396, March.
    4. 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.
    5. 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.
    6. Broadstock, David C. & Hunt, Lester C., 2010. "Quantifying the impact of exogenous non-economic factors on UK transport oil demand," Energy Policy, Elsevier, vol. 38(3), pages 1559-1565, March.
    7. 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.
    8. Atalla, Tarek N. & Gasim, Anwar A. & Hunt, Lester C., 2018. "Gasoline demand, pricing policy, and social welfare in Saudi Arabia: A quantitative analysis," Energy Policy, Elsevier, vol. 114(C), pages 123-133.
    9. Mona Chitnis & Lester Hunt, 2011. "Modelling UK household expenditure: economic versus noneconomic drivers," Applied Economics Letters, Taylor & Francis Journals, vol. 18(8), pages 753-767.
    10. Javid, Muhammad & Khan, Farzana Naheed & Arif, Umaima, 2022. "Income and price elasticities of natural gas demand in Pakistan: A disaggregated analysis," Energy Economics, Elsevier, vol. 113(C).
    11. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.
    12. Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
    13. Muhammad, Javid & Abdul, Qayyum, 2013. "Electricity consumption-GDP nexus: A structural time series analysis," MPRA Paper 47448, University Library of Munich, Germany.
    14. Broto Carmen & Ruiz Esther, 2009. "Testing for Conditional Heteroscedasticity in the Components of Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-30, May.
    15. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    16. Reema Gh. Alajmi, 2024. "Energy Consumption and Carbon Emissions: An Empirical Study of Saudi Arabia," Sustainability, MDPI, vol. 16(13), pages 1-16, June.
    17. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    18. Barnett, William A. & de Peretti, Philippe, 2009. "Admissible Clustering Of Aggregator Components: A Necessary And Sufficient Stochastic Seminonparametric Test For Weak Separability," Macroeconomic Dynamics, Cambridge University Press, vol. 13(S2), pages 317-334, September.
    19. Matteo Barigozzi & Marc Hallin, 2016. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 33-60, February.
    20. Gabriele Fiorentini & Enrique Sentana & Neil Shephard, 2004. "Likelihood-Based Estimation of Latent Generalized ARCH Structures," Econometrica, Econometric Society, vol. 72(5), pages 1481-1517, September.

    More about this item

    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:sur:seedps:117. 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: Mona Chitnis (email available below). General contact details of provider: https://edirc.repec.org/data/eesuruk.html .

    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.