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An examination of the relationship between biodiesel and soybean oil prices using an asset pricing model

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  • Miguel Carriquiry

    (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economí­a)

Abstract

This work utilized a discrete time return model of finance to analyze whether prices changes of soybean oil, the main feedstock for biodiesel production in the US affect the prices of biodiesel. Empirical models of asset pricing attempt to extract information about latent state variables and structural parameters from observed prices. These models, which often involve high dimension latent state variables, can be conveniently estimated using Bayesian methods. Results from this study indicate the price of soybean oil does not have a strong direct impact on the price of biodiesel in the short run, or in a daily basis.

Suggested Citation

  • Miguel Carriquiry, 2015. "An examination of the relationship between biodiesel and soybean oil prices using an asset pricing model," Documentos de Trabajo (working papers) 15-17, Instituto de Economía - IECON.
    • Handle: RePEc:ulr:wpaper:dt-17-15
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    File URL: https://hdl.handle.net/20.500.12008/7166
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    References listed on IDEAS

    as
    1. Miguel Carriquiry, 2007. "Comparative Analysis of the Development of the United States and European Union Biodiesel Industries, A," Center for Agricultural and Rural Development (CARD) Publications 07-bp51, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    2. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
    3. Mallory, Mindy L. & Irwin, Scott H. & Hayes, Dermot J., 2012. "How market efficiency and the theory of storage link corn and ethanol markets," Energy Economics, Elsevier, vol. 34(6), pages 2157-2166.
    4. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    5. Balagtas, Joseph V. & Gruere, Guillaume P. & Sanders, Daniel J., 2012. "Revisiting the palm oil boom in Southeast Asia: The role of fuel versus food demand drivers," IFPRI discussion papers 1167, International Food Policy Research Institute (IFPRI).
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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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