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Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis

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  • Hasanov, Akram Shavkatovich
  • Do, Hung Xuan
  • Shaiban, Mohammed Sharaf

Abstract

This paper focuses on examining the impact of crude oil price volatility on the price changes of major edible oils (rapeseed, soybean, and sunflower), which are the main feedstock for the biodiesel industry in the European Union. For this purpose, a four-variate version of non-diagonal GARCH-in-mean model that allows for asymmetry in the variance–covariance matrix is used. An important conclusion that emerges from this study is that the crude oil price uncertainty appears to be responsible for a significant decline in price returns of major feedstock edible oils considered in this study. The volatility impulse response analyses support the conclusion that the conditional variances of both edible and crude oil and covariances between them are generally highly responsive to historical shock. However, the size of the impacts is mainly commodity specific. Finally, we investigate the causality from crude oil price volatility to edible oil prices and the effects of oil price shocks on edible oil prices by using the Granger causality test and generalized impulse response function analysis, respectively. The empirical results show that there is strong evidence of causality from crude oil price volatility to all edible oil prices under study, and generalized impulse response analysis shows that the edible oil markets significantly respond to the shocks in oil prices.

Suggested Citation

  • Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.
    • Handle: RePEc:eee:eneeco:v:57:y:2016:i:c:p:16-27
    DOI: 10.1016/j.eneco.2016.04.015
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    More about this item

    Keywords

    Oil/food price uncertainty; Crude oil; Edible oil; Multivariate GARCH; VIRF;
    All these keywords.

    JEL classification:

    • 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
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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