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Spatial Panel Data Models and Fuel Demand in Brazil

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  • dos Santos, Gervásio
  • Faria, Weslem

Abstract

The objective of this paper is to estimate the price and income elasticity for gasoline and ethanol in the fuel market for light vehicles in Brazil using spatial panel data models. Besides diversification, there are spatial features of fuel demand and supply that might influence heterogeneity in the behavior of regional consumers. Consumer behavior is heterogeneous and directly and indirectly influenced by different supply gaps and transportation and distribution costs. Thus, spatial panel data models are used to estimate price and income elasticities of gasoline and ethanol. The spatial heterogeneity and autocorrelation in the regional consumer preferences are controlled. Results showed that, aside strong evidence of the influence of spatial autocorrelation in the consumption of gasoline and ethanol, there also is a considerable competition between these fuels, mainly due to the flex-fuel technology.

Suggested Citation

  • dos Santos, Gervásio & Faria, Weslem, 2012. "Spatial Panel Data Models and Fuel Demand in Brazil," TD NEREUS 10-2012, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
    • Handle: RePEc:ris:nereus:2012_010
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    References listed on IDEAS

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    1. Espey, Molly, 1998. "Gasoline demand revisited: an international meta-analysis of elasticities," Energy Economics, Elsevier, vol. 20(3), pages 273-295, June.
    2. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    3. Alberto Salvo & Cristian Huse, 2011. "Is Arbitrage Tying the Price of Ethanol to that of Gasoline? Evidence from the Uptake of Flexible-Fuel Technology," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 119-148.
    4. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    5. Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
    6. 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.
    7. Georges Bresson & Badi H. Baltagi & Alain Pirotte, 2007. "Panel unit root tests and spatial dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 339-360.
    8. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 1-25, January.
    9. Bentzen, Jan, 1994. "An empirical analysis of gasoline demand in Denmark using cointegration techniques," Energy Economics, Elsevier, vol. 16(2), pages 139-143, April.
    10. Baltagi, Badi H. & Griffin, James M., 1983. "Gasoline demand in the OECD : An application of pooling and testing procedures," European Economic Review, Elsevier, vol. 22(2), pages 117-137, July.
    11. Puller, Steven L. & Greening, Lorna A., 1999. "Household adjustment to gasoline price change: an analysis using 9 years of US survey data," Energy Economics, Elsevier, vol. 21(1), pages 37-52, February.
    12. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    13. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    14. Baltagi, Badi H. & Liu, Long, 2008. "Testing for random effects and spatial lag dependence in panel data models," Statistics & Probability Letters, Elsevier, vol. 78(18), pages 3304-3306, December.
    15. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    16. Baltagi, Badi H. & Egger, Peter & Pfaffermayr, Michael, 2007. "Estimating models of complex FDI: Are there third-country effects?," Journal of Econometrics, Elsevier, vol. 140(1), pages 260-281, September.
    17. Espey, Molly, 1996. "Watching the fuel gauge: An international model of automobile fuel economy," Energy Economics, Elsevier, vol. 18(1-2), pages 93-106, April.
    18. 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.
    19. Dahl, Carol & Sterner, Thomas, 1991. "Analysing gasoline demand elasticities: a survey," Energy Economics, Elsevier, vol. 13(3), pages 203-210, July.
    20. Molly Espey, 1996. "Explaining the Variation in Elasticity Estimates of Gasoline Demand in the United States: A Meta-Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 49-60.
    21. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    22. Baltagi, Badi H. & Heun Song, Seuck & Cheol Jung, Byoung & Koh, Won, 2007. "Testing for serial correlation, spatial autocorrelation and random effects using panel data," Journal of Econometrics, Elsevier, vol. 140(1), pages 5-51, September.
    23. Kelley Pace, R. & Barry, Ronald, 1997. "Sparse spatial autoregressions," Statistics & Probability Letters, Elsevier, vol. 33(3), pages 291-297, May.
    24. 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.
    25. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
    26. Badi Baltagi & Dong Li, 2006. "Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 175-185.
    27. 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.
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    3. Ahmad, Mahyudin & Hall, Stephen G. & Law, Siong Hook & Nayan, Sabri, 2023. "The spillover effects of financial development and institutions on economic growth in emerging economies: new insights from spatial Durbin approach," MPRA Paper 118966, University Library of Munich, Germany.
    4. Leonardo Chaves Borges Cardoso & Maurício Vaz Lobo Bittencourt & Alexandre Alves Porsse, 2014. "Demanda Por Combustíveis Leves No Brasil: Uma Abordagem Utilizando Painéis Espaciais Dinâmicos," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 194, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. Mahyudin Ahmad & Stephen G. Hall, 2023. "The growth effects of economic and political institutions: new evidence from spatial econometrics analysis using historical-based institutional matrix," Economic Change and Restructuring, Springer, vol. 56(2), pages 749-780, April.

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    More about this item

    Keywords

    income elasticity; fuel demand; spatial panel data; Brazil;
    All these keywords.

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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