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The impact of speculation on commodity prices: A Meta-Granger analysis

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  • Wimmer, Thomas
  • Geyer-Klingeberg, Jerome
  • Hütter, Marie
  • Schmid, Florian
  • Rathgeber, Andreas

Abstract

This paper uses Meta-Granger analysis to explain and summarize the mixed results in the literature on the impact of financial speculation on commodity prices. The sample covers 2106 manually collected p-values from Granger causality (GC) tests reported in 54 prior studies. Our results show that the heterogeneity in previous findings can be largely explained by the commodity type under examination, the sample period of the data, the measurement of the focus variables (return, volatility, or spread), and the inclusion of control variables in the GC model. Even after accounting for 23 observable differences in study and test design, our results indicate that studies published in higher ranked journals present significantly less evidence for speculation to drive commodity prices. Moreover, we use the Meta-Granger results to predict ‘best choice’ models considering preferred model setups. The results reveal that the hypothesis of Granger non-causality between speculation and commodity prices cannot be rejected at standard significance levels when assuming a best choice study design and various variations of it. We conclude that either there is no genuine overall speculation effect in agricultural, energy and metal markets, or the research design of the frequently applied GC testing is not powerful enough to detect those effects.

Suggested Citation

  • Wimmer, Thomas & Geyer-Klingeberg, Jerome & Hütter, Marie & Schmid, Florian & Rathgeber, Andreas, 2021. "The impact of speculation on commodity prices: A Meta-Granger analysis," Journal of Commodity Markets, Elsevier, vol. 22(C).
  • Handle: RePEc:eee:jocoma:v:22:y:2021:i:c:s2405851320300258
    DOI: 10.1016/j.jcomm.2020.100148
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    More about this item

    Keywords

    Speculation; Commodity prices; Non-commercial trader; Meta-analysis; Granger causality;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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