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The Interdependence Between Commodity-Price and GDP Cycles: A Frequency-Domain Approach

Abstract

In this paper, the interdependence between aggregate commodity prices and world gross domestic product (GDP) is studied by performing two empirical exercises with long-run data that starts in the nineteenth century. Long−term and medium-term cycles are computed and their degree of synchronization measured for different leads and lags. Causality tests are performed on the frequency domain. Both exercises deepen understanding of these macroeconomic relationships by disentangling them on the time and frequency dimensions, respectively. The results show evidence of cycle synchronization only in the case of super cycles. There is causality evidence from GDP to aggregate commodity prices mostly for long-run frequencies. Therefore, commodity-price trends and super-cycles are demand driven. There is causality evidence between oil-prices and GDP in both causation directions. However, oil-price fluctuations are predictive of GDP for business-cycle frequencies only. Overall, a frequency-domain approach is useful for identifying significant variation in the interdependence between commodity prices and GDP across fluctuation horizons.

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Notes

  1. 1.

    An example of this type of assessments is Morgan Stanley (2015). This article forecast an increase in metal and mineral prices due to the predicted industrial recovery in China. However, its authors warned that this prediction could fail if producer companies did not use enough “supply discipline”.

  2. 2.

    Diverse studies estimate the cyclical components of business activity using filtering methodologies based on BP filters. Recent examples of these works are Comin and Gertler (2006), Borio (2014) and Drehmann et al. (2012). The BP filter was developed by Baxter and King (1999) and Christiano and Fitzgerald (2003).

  3. 3.

    Other recent papers have documented the relationship between recent high-growth periods in developing economies and the dynamics of RCP. Collier and Goderis (2012), Garnaut (2012) and Byrne et al. (2013) discuss this relationship. In addition, Baffes and Etienne (2016) as well as Winkelried (2016) provided recent evidence of the Prebisch-Singer hypothesis.

  4. 4.

    We thank Bilge Erten and Jose A. Ocampo for sharing with us their database on commodity prices.

  5. 5.

    The synchronization measure proposed by Harding and Pagan (2006) was also tested with qualitatively similar results.

  6. 6.

    This analysis was also performed with Kendall’s Tau correlations with very similar conclusions.

  7. 7.

    The non-metal components of the commodity-price index are basically agricultural products and raw materials (Online Supplemental Appendix Table 1).

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Acknowledgements

The findings, recommendations, interpretations and conclusions expressed in this paper are those of the authors and do not necessarily reflect the view of the Central Bank of Colombia or its Board of Directors. We are grateful to Luis Fernando Melo, Ana María Fuertes and Lavan Mahadeva, the Editor and anonymous referee for their very useful comments.

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Correspondence to Jair N. Ojeda-Joya.

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Ojeda-Joya, J.N., Jaulin-Mendez, O. & Bustos-Peláez, J.C. The Interdependence Between Commodity-Price and GDP Cycles: A Frequency-Domain Approach. Atl Econ J 47, 275–292 (2019). https://doi.org/10.1007/s11293-019-09635-4

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Keywords

  • Medium-term cycles
  • Commodity prices
  • Frequency domain
  • Super cycles

JEL

  • C22
  • E32
  • Q02