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Forecasting automobile petrol demand in Australia: An evaluation of empirical models

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  • Li, Zheng
  • Rose, John M.
  • Hensher, David A.

Abstract

Transport fuel consumption and its determinants have received a great deal of attention since the early 1970s. In the literature, different types of modelling methods have been used to estimate petrol demand, each having methodological strengths and weaknesses. This paper is motivated by an ongoing need to review the effectiveness of empirical fuel demand forecasting models, with a focus on theoretical as well as practical considerations in the model-building processes of different model forms. We consider a linear trend model, a quadratic trend model, an exponential trend model, a single exponential smoothing model, Holt's linear model, Holt-Winters' model, a partial adjustment model (PAM), and an autoregressive integrated moving average (ARIMA) model. More importantly, the study identifies the difference between forecasts and actual observations of petrol demand in order to identify forecasting accuracy. Given the identified best-forecasting model, Australia's automobile petrol demand from 2007 through to 2020 is presented under the "business-as-usual" scenario.

Suggested Citation

  • Li, Zheng & Rose, John M. & Hensher, David A., 2010. "Forecasting automobile petrol demand in Australia: An evaluation of empirical models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(1), pages 16-38, January.
  • Handle: RePEc:eee:transa:v:44:y:2010:i:1:p:16-38
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    References listed on IDEAS

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    Cited by:

    1. Pelinescu, Elena & Anton, Lucian Vasile & Ionescu, Raluca & Tasca, Radu, 2010. "The Analysis of Local Budgets and Their Importance in the Fight Against the Economic Crisis Effects," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(5), pages 17-32.
    2. Bakhat, Mohcine & Rosselló, Jaume, 2013. "Evaluating a seasonal fuel tax in a mass tourism destination: A case study for the Balearic Islands," Energy Economics, Elsevier, vol. 38(C), pages 12-18.
    3. Al-Ghandoor, Ahmed & Jaber, Jamal & Al-Hinti, Ismael & Abdallat, Yousef, 2013. "Statistical assessment and analyses of the determinants of transportation sector gasoline demand in Jordan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 129-138.
    4. Melikoglu, Mehmet, 2013. "Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 393-400.
    5. Odeck, James & Johansen, Kjell, 2016. "Elasticities of fuel and traffic demand and the direct rebound effects: An econometric estimation in the case of Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 1-13.
    6. Gkritza, Konstantina & Karlaftis, Matthew G. & Mannering, Fred L., 2011. "Estimating multimodal transit ridership with a varying fare structure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 148-160, February.
    7. Melo, Patricia C. & Ramli, Ahmad Razi, 2014. "Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 30-46.
    8. Mohcine Bakhat & José M. Labeaga & Xavier Labandeira & Xiral Lñpez, 2013. "Economic Crisis and Elasticities of Car Fuels: Evidence for Spain," Working Papers fa15-2013, Economics for Energy.
    9. Nazneen Ferdous & Abdul Pinjari & Chandra Bhat & Ram Pendyala, 2010. "A comprehensive analysis of household transportation expenditures relative to other goods and services: an application to United States consumer expenditure data," Transportation, Springer, vol. 37(3), pages 363-390, May.
    10. Willem H. Boshoff, 2011. "Gasoline, diesel fuel and jet fuel demand in South Africa," Working Papers 226, Economic Research Southern Africa.
    11. Jian Chai & Shubin Wang & Shouyang Wang & Ju’e Guo, 2012. "Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry," Energies, MDPI, Open Access Journal, vol. 5(3), pages 1-22, March.
    12. Keshavarzian, Maryam & Kamali Anaraki, Sara & Zamani, Mehrzad & Erfanifard, Ali, 2012. "Projections of oil demand in road transportation sector on the basis of vehicle ownership projections, worldwide: 1972–2020," Economic Modelling, Elsevier, vol. 29(5), pages 1979-1985.

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