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Fuel demand in Brazil in a dynamic panel data approach

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  • Santos, Gervásio F.

Abstract

The purpose of this paper is to evaluate the sensitivity of fuel consumers regarding price and income, taking recent changes in the Brazilian fuel market into account. In this market, new market rules, energy policy towards fuel diversification and introduction of flex-fuel engines have determined fuel competition among gasoline, ethanol and compressed natural gas. Using a dynamic panel data model, demand equations for these three fuels are econometrically estimated to obtain consumer adjustment coefficients, price, cross-price and income elasticities in the short and long-run. In addition, the effect of the introduction of flex-fuel engines in the market and the rationality of consumers towards efficiency constraints of the engines were tested. Apart from considerable competition, results show that the dynamics of the Brazilian fuel market revolves around ethanol instead of gasoline. While demands for gasoline and natural gas are inelastic to price, demand for ethanol is elastic in Brazil. Furthermore, after the introduction of the flex-fuel technology the sensitivity of consumers to fuel prices changed, and ethanol consumers take efficiency constrains into account when ethanol prices reach the threshold of 70% of gasoline prices.

Suggested Citation

  • Santos, Gervásio F., 2013. "Fuel demand in Brazil in a dynamic panel data approach," Energy Economics, Elsevier, vol. 36(C), pages 229-240.
    • Handle: RePEc:eee:eneeco:v:36:y:2013:i:c:p:229-240
    DOI: 10.1016/j.eneco.2012.08.012
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    as
    1. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Ethanol demand under the flex-fuel technology regime in Brazil," Energy Economics, Elsevier, vol. 33(6), pages 1146-1154.
    2. Jörg Breitung & Samarjit Das, 2005. "Panel unit root tests under cross‐sectional dependence," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 414-433, November.
    3. Gang Liu, 2004. "Estimating Energy Demand Elasticities for OECD Countries. A Dynamic Panel Data Approach," Discussion Papers 373, Statistics Norway, Research Department.
    4. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    5. 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.
    6. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    7. Robert S. Pindyck & Julio J. Rotemberg, 1982. "Dynamic Factor Demands Under Rational Expectations," NBER Working Papers 1015, National Bureau of Economic Research, Inc.
    8. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    9. 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.
    10. Bentzen, Jan, 1994. "An empirical analysis of gasoline demand in Denmark using cointegration techniques," Energy Economics, Elsevier, vol. 16(2), pages 139-143, April.
    11. 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.
    12. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    13. 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.
    14. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    15. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    16. Espey, Molly, 1998. "Gasoline demand revisited: an international meta-analysis of elasticities," Energy Economics, Elsevier, vol. 20(3), pages 273-295, June.
    17. 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.
    18. 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.
    19. Watkins, G. C., 1991. "Short-and long-term equilibria : Relationships between first and third generation dynamic factor demand models," Energy Economics, Elsevier, vol. 13(1), pages 2-9, January.
    20. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    21. 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.
    22. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    23. Dahl, Carol & Sterner, Thomas, 1991. "Analysing gasoline demand elasticities: a survey," Energy Economics, Elsevier, vol. 13(3), pages 203-210, July.
    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. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    26. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

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    2. Pessoa, Joao Paulo & Santos, Roberto Amaral & Chimeli, Ariaster, 2023. "Natural Gas Vehicles: Consequences to Fuel Markets and the Environment," SocArXiv 7tvgy, Center for Open Science.
    3. Nascimento Filho, A.S. & Pereira, E.J.A.L. & Ferreira, Paulo & Murari, T.B. & Moret, M.A., 2018. "Cross-correlation analysis on Brazilian gasoline retail market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 550-557.
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    9. Frederico Uch a & Cleiton Silva de Jesus & Leonardo Chaves Borges Cardoso, 2020. "Fuel Demand Elasticities in Brazil: A Panel Data Analysis with Instrumental Variables," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 450-457.
    10. 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.
    11. 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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    13. Debnath, Deepayan & Whistance, Jarrett & Thompson, Wyatt & Binfield, Julian, 2017. "Complement or substitute: Ethanol’s uncertain relationship with gasoline under alternative petroleum price and policy scenarios," Applied Energy, Elsevier, vol. 191(C), pages 385-397.
    14. Hector M. Nuñez and Jesús Otero, 2017. "Integration in Gasoline and Ethanol Markets in Brazil over Time and Space under the Flex-fuel Technology," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    15. Leonid Galchynskyi, 2020. "Estimation of the price elasticity of petroleum products’ consumption in Ukraine," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 15(2), pages 315-339, June.
    16. Huntington, Hillard G. & Barrios, James J. & Arora, Vipin, 2019. "Review of key international demand elasticities for major industrializing economies," Energy Policy, Elsevier, vol. 133(C).
    17. Ryu, Jun-Yeol & Kim, Dae-Wook & Kim, Man-Keun, 2021. "Household differentiation and residential electricity demand in Korea," Energy Economics, Elsevier, vol. 95(C).
    18. 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].
    19. Khanna, Madhu & Hector, Nunez & David, Zilberman, 2014. "The Political-Economy of Biofuel and Cheap Oil Policies in Brazil," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169471, Agricultural and Applied Economics Association.
    20. Mauricio Vaz Lobo Bittencourt & Leonardo Chaves Borges Cardoso & Elena Grace Irwin, 2016. "Biofuels Policies And Fuel Demand Elasticities In Brazil: An Iv Approach," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 181, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    21. Khanna, Madhu & Nuñez, Hector M. & Zilberman, David, 2016. "Who pays and who gains from fuel policies in Brazil?," Energy Economics, Elsevier, vol. 54(C), pages 133-143.
    22. Guedes, Gilvan & Magalhaes, Aline & Curran, Sara & Domingues, Edson, 2018. "Greening the Brazilian energy grid as a sustainable response to increasing consumption: how feasible and how costly?," Conference papers 332968, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    23. Cardoso, Leonardo C.B. & Bittencourt, Maurício V.L. & Litt, Wade H. & Irwin, Elena G., 2019. "Biofuels policies and fuel demand elasticities in Brazil," Energy Policy, Elsevier, vol. 128(C), pages 296-305.
    24. Roberto Amaral-Santos & Ariaster Chimeli & Joao Paulo Pessoa, 2023. "Natural Gas Vehicles: Consequences to Fuel Markets and the Environment," Working Papers, Department of Economics 2023_07, University of São Paulo (FEA-USP).
    25. Chi, Junwook, 2016. "Long- and short-run asymmetric responses of motor-vehicle travel to fuel price variations: New evidence from a nonlinear ARDL approach," Transport Policy, Elsevier, vol. 50(C), pages 126-134.

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    More about this item

    Keywords

    Fuel demand; Energy policy; Ethanol; Flex-fuel vehicle; Dynamic panel data model;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices

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