ETHANOL IN BRAZIL: A PREDICTIVE PRICING APPROACH
DOI:
https://doi.org/10.56238/ERR01v10n3-024Keywords:
Ethanol, Commodities, Forecasting, Time SeriesAbstract
The production of liquid biofuels has emerged as an alternative to the use of fossil fuels for transportation purposes. Ethanol is described as a renewable energy fuel. In 2021, Brazil produced 27.46% of the world's ethanol, ranking second among producing countries. The introduction of light commercial and passenger vehicles with Flex Fuel technology, which uses both Type C gasoline and hydrous ethanol, into the Brazilian market, began in March 2003, significantly impacting ethanol demand in the Brazilian consumer market. This study aims to compare the predictive accuracy of the ARFIMA, ARIMA, and Smoothed Exponential models for Brazilian ethanol prices over a four-year period.
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References
TRIANA, Carlos Ariel Ramírez. Energetics of Brazilian ethanol: Comparison between assessment approaches. Energy Policy, v. 39, n. 8, p. 4605-4613, 2011.
BENITES-LAZARO, L. L.; MELLO-THÉRY, N. A.; LAHSEN, M. Business storytelling about energy and climate change: The case of Brazil’s ethanol industry. Energy Research & Social Science, v. 31, p. 77-85, 2017.
Renewable Fuels Association. Ethanolrfa. 2022. Disponível em: . Acesso em: 15 mar. 2022.
DIAS DE OLIVEIRA, Marcelo E.; VAUGHAN, Burton E.; RYKIEL, Edward J. Ethanol as fuel: energy, carbon dioxide balances, and ecological footprint. AIBS Bulletin, v. 55, n. 7, p. 593-602, 2005.
GOMEZ, José MA; LEGEY, Luiz FL. An analysis of the impact of Flex-Fuel vehicles on fuel consumption in Brazil, applying Cointegration and the Kalman Filter. Energy, v. 81, p. 696-705, 2015.
EL MONTASSER, Ghassen et al. Are there multiple bubbles in the ethanol–gasoline price ratio of Brazil?. Renewable and Sustainable Energy Reviews, v. 52, p. 19-23, 2015.
ASSOCIAÇÃO NACIONAL DOS FABRICANTES DE VEÍCULOS AUTOMOTORES (São Paulo). ANFAVEA. 2022. Disponível em: <http://www.anfavea.com.br/>. Acesso em: 15 mar. 2022.
DAVID, S. A. et al. Fractional dynamic behavior in ethanol prices series. Journal of Computational and Applied Mathematics, v. 339, p. 85-93, 2018.
R Foundation. The Comprehensive R Archive Network. 2018. Disponível em: <https://cran.r-project.org/>. Acesso em: 15 jul. 2018.
sso em: 19 set. 1998.
CEPEA (São Paulo). Centro de Estudos Avançados em Economia Aplicada. 2018. Disponível em: <https://www.cepea.esalq.usp.br/br>. Acesso em: 15 mar. 2022.
Box, G.E.P. ET AL. Time Series analysis forecasting and control. 3rd ed, New Jersey: Prentice Hall, 1994.
MORETTIN, P. A. Econometria Financeira: um curso em Séries Temporais Financeiras. 1ª ed. São Paulo: Blucher, 2008.
MAÇAIRA, P. M. ET AL. Modelling and Forecasting the Residencial Eletricity Consumption in Brazil with Pegels Exponentials Smoothing Techniques, Procedia Computer Science, Volume 55, 2015.
