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Time-Frequency Dynamics of Biofuels-Fuels-Food System

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  • Lukas Vacha
  • Karel Janda
  • Ladislav Kristoufek
  • David Zilberman

Abstract

For the first time, we apply the wavelet coherence methodology on biofuels (ethanol and biodiesel) and a wide range of related commodities (gasoline, diesel, crude oil, corn, wheat, soybeans, sugarcane and rapeseed oil). This way, we are able to investigate dynamics of correlations in time and across scales (frequencies) with a model-free approach. We show that correlations indeed vary in time and across frequencies. We find two highly correlated pairs which are strongly connected at low frequencies - ethanol with corn and biodiesel with German diesel - during almost the whole analyzed period (2003-2011). Structure of correlations remarkably changes during the food crisis - higher frequencies become important for both mentioned pairs. This implies that during stable periods, ethanol is correlated with corn and biodiesel is correlated with German diesel mainly at low frequencies so that they follow a common long-term trend. However, in the crisis periods, ethanol (biodiesel) is lead by corn (German diesel) even at high frequencies (low scales), which implies that the biofuels prices react more rapidly to the changes in their producing factors.

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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number 1209.0900.

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Date of creation: Sep 2012
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Publication status: Published in Energy Economics 40, pp. 233-241, 2013
Handle: RePEc:arx:papers:1209.0900

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References

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  1. Ladislav Kristoufek & Karel Janda & David Zilberman, 2012. "Regime-Dependent Topological Properties of Biofuels Networks," CAMA Working Papers 2012-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  2. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2010. "The yield curve and the macro-economy across time and frequencies," CEF.UP Working Papers 1004, Universidade do Porto, Faculdade de Economia do Porto.
  3. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
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  8. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
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  14. Teresa Serra & David Zilberman & José Gil, 2011. "Price volatility in ethanol markets," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 38(2), pages 259-280, June.
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  21. Busse, Stefan & Brümmer, Bernard & Ihle, Rico, 2010. "Interdependencies between fossil fuel and renewable energy markets: the German biodiesel market," DARE Discussion Papers 1010, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
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Citations

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Cited by:
  1. Janda, Karel & Krska, Stepan & Prusa, Jan, 2014. "Odhad nákladů na podporu české fotovoltaické energie
    [The Estimation of the Cost of Promotion of the Czech Photovoltaic Energy]
    ," MPRA Paper 54108, University Library of Munich, Germany.
  2. Chrz, Stepan & Hruby, Zdenek & Janda, Karel & Kristoufek, Ladislav, 2013. "Provazanost trhu potravin, biopaliv a fosilnich paliv
    [Interconnections within food, biofuel, and fossil fuel markets]
    ," MPRA Paper 43958, University Library of Munich, Germany.
  3. Ladislav Kristoufek, 2013. "Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence," Papers 1310.1446, arXiv.org.
  4. Trujillo-Barrera, Andres & Pennings, Joost M.E., 2013. "Energy and Food Commodity Prices Linkage: An Examination with Mixed-Frequency Data," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150465, Agricultural and Applied Economics Association.
  5. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.

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