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Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment

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  • Nicola, Francesca de
  • De Pace, Pierangelo
  • Hernandez, Manuel A.

Abstract

Using monthly data between 1970 and 2013, we provide a comprehensive analysis of the extent of co-movement (measured by correlation coefficients) among the nominal price returns of 11 major energy, agricultural, and food commodities. We study the degree and the time evolution of unconditional and conditional correlations using a uniform-spacings estimation and testing approach, multivariate dynamic conditional correlation models, and a rolling regression procedure. We find that (1) the price returns of energy and agricultural commodities are highly correlated; (2) the overall level of co-movement among commodities increased in recent years, especially between energy and agricultural commodities, and in particular in the cases of maize and soybean oil, which are important inputs in the production of biofuels; and (3) the stock market volatility is positively associated with the co-movement of price returns across markets, especially after 2007.

Suggested Citation

  • Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    • Handle: RePEc:eee:eneeco:v:57:y:2016:i:c:p:28-41
    DOI: 10.1016/j.eneco.2016.04.012
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    More about this item

    Keywords

    Commodity prices; Co-movement; Time-series models;
    All these keywords.

    JEL classification:

    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • 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

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