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An analysis of the impact of Flex-Fuel vehicles on fuel consumption in Brazil, applying Cointegration and the Kalman Filter

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  • Gomez, José M.A.
  • Legey, Luiz F.L.

Abstract

The aim of this article is to analyze the impact of Flex-Fuel technology on the consumption of fuels in Brazil. Applying the methodology suggested by Hall (1993), combining an Error Correction Model (ECM) with the Kalman Filter (KF), we studied the influence of the relative prices of Hydrous Ethanol and Gasoline C on the consumption of these fuels. We analyzed structural breaks in the time series and the evolution of parameters over periods of time. We found that the introduction of Flex-Fuel technology into the Brazilian fleet of light passenger and cargo vehicles had a significant impact on the pattern of demand for fuel in the country. In particular, we noted the following: (i) the existence of a structural break in the time series of demand for Hydrous Ethanol and Gasoline C; (ii) the marked effect of situations in which there was a reduction in the availability of Hydrous Ethanol for the fuel market; (iii) the increasing importance, in terms of demand, of the ‘Ethanol-Gasoline C relative price’ variable. We concluded that all these factors are due to the technological advance in Flex-Fuel vehicles, which enables consumers to choose between Ethanol and Gasoline C when refueling vehicles – the decision for most vehicle drivers being essentially based on cost-benefit considerations. We consider the findings relevant given that several economic and climatic factors indicate that there is a strong likelihood of long term variation in the relative price of Ethanol and Gasoline C in Brazil. Government and key players in the energy field will consequently need to adopt a clear strategy, based on reliable data, in order to deal with fluctuating supply and demand for both fuels. Furthermore, the methodology used in this study and the findings obtained are relevant to future studies into the likely impact of future technological and economic developments in the Brazilian fuel market, such as the introduction of electric vehicles.

Suggested Citation

  • Gomez, José M.A. & Legey, Luiz F.L., 2015. "An analysis of the impact of Flex-Fuel vehicles on fuel consumption in Brazil, applying Cointegration and the Kalman Filter," Energy, Elsevier, vol. 81(C), pages 696-705.
    • Handle: RePEc:eee:energy:v:81:y:2015:i:c:p:696-705
    DOI: 10.1016/j.energy.2015.01.015
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    References listed on IDEAS

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    1. Hall, Stephen G, 1993. "Modelling Structural Change Using the Kalman Filter," Economic Change and Restructuring, Springer, vol. 26(1), pages 1-13.
    2. Polemis, Michael L., 2006. "Empirical assessment of the determinants of road energy demand in Greece," Energy Economics, Elsevier, vol. 28(3), pages 385-403, May.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    4. Eltony, M. N. & Al-Mutairi, N. H., 1995. "Demand for gasoline in Kuwait : An empirical analysis using cointegration techniques," Energy Economics, Elsevier, vol. 17(3), pages 249-253, July.
    5. Bentzen, Jan, 1994. "An empirical analysis of gasoline demand in Denmark using cointegration techniques," Energy Economics, Elsevier, vol. 16(2), pages 139-143, April.
    6. 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.
    7. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    8. Ramanathan, R., 1999. "Short- and long-run elasticities of gasoline demand in India: An empirical analysis using cointegration techniques," Energy Economics, Elsevier, vol. 21(4), pages 321-330, August.
    9. Alves, Denisard C. O. & De Losso da Silveira Bueno, Rodrigo, 2003. "Short-run, long-run and cross elasticities of gasoline demand in Brazil," Energy Economics, Elsevier, vol. 25(2), pages 191-199, March.
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    Cited by:

    1. Laurini, Márcio Poletti, 2017. "The spatio-temporal dynamics of ethanol/gasoline price ratio in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1-12.
    2. 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.
    3. Chanthawong, Anuman & Dhakal, Shobhakar & Jongwanich, Juthathip, 2016. "Supply and demand of biofuels in the fuel market of Thailand: Two stage least square and three least square approaches," Energy, Elsevier, vol. 114(C), pages 431-443.

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