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Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA

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  • Ladislav Kristoufek
  • Karel Janda
  • David Zilberman

Abstract

We use the wavelet coherence methodology to investigate relations between prices of ethanol and its feedstocks. Our continuous wavelet framework allows for discovering price connections and their evolution in both time and frequency domain in the most important ethanol markets – Brazil and the USA. For both of these markets we show that the long-run relationship between prices of ethanol and corn (in USA) or sugar (in Brazil) is positive, strong and stable in time. Importantly, we show that the prices of feedstock lead the prices of ethanol and not the other way around. The price lead of feedstock is documented for both short and long run horizons. Our qualitative results hold true even when the influence of crude oil prices is accounted for by utilizing partial wavelet coherence approach.

Suggested Citation

  • Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2015-11
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    Cited by:

    1. Capitani, Daniel Henrique Dario & Tonin, Julyerme M. & Cruz, Jose Cesar, 2017. "Integration and hedging efficiency between the Brazilian and the U.S. ethanol markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258520, Agricultural and Applied Economics Association.
    2. Aloisio S. Nascimento Filho & Hugo Saba & Rafael G. O. dos Santos & João Gabriel A. Calmon & Marcio L. V. Araújo & Eduardo M. F. Jorge & Thiago B. Murari, 2021. "Analysis of Hydrous Ethanol Price Competitiveness after the Implementation of the Fossil Fuel Import Price Parity Policy in Brazil," Sustainability, MDPI, vol. 13(17), pages 1-12, September.
    3. Nigatu, Getachew & Adjemian, Michael K., 2016. "The U.S. Role in the Price Determination of Major Agricultural Commodities," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236045, Agricultural and Applied Economics Association.
    4. Tan Ngoc Vu & Duc Hong Vo & Chi Minh Ho & Loan Thi-Hong Van, 2019. "Modeling the Impact of Agricultural Shocks on Oil Price in the US: A New Approach," JRFM, MDPI, vol. 12(3), pages 1-27, September.
    5. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    6. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    7. Derick David Quintino & Heloisa Lee Burnquist & Paulo Jorge Silveira Ferreira, 2021. "Carbon Emissions and Brazilian Ethanol Prices: Are They Correlated? An Econophysics Study," Sustainability, MDPI, vol. 13(22), pages 1-18, November.

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    More about this item

    Keywords

    ethanol; corn; sugar; oil; wavelet coherence;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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