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Does the volatility of commodity prices reflects macroeconomic uncertainty?

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  • Tovonony Razafindrabe

    ()

  • Valérie Mignon

    () (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Marc Joëts

    ()

Abstract

This paper analyzes the impact of macroeconomic uncertainty on a large sample of 19 commodity markets. We rely on a robust measure of macroeconomic uncertainty based on a wide range of monthly macroeconomic and financial indicators, and we estimate a structural threshold VAR (TVAR) model to assess whether the effect of macroeconomic uncertainty on commodity price returns depends on the degree of uncertainty. Our findings show that whereas the safe-haven role of precious metals is confirmed, agricultural and industrial markets are highly sensitive to the variability and the level of macroeconomic uncertainty, respectively. In addition, we show that the recent 2007-09 recession has generated an unprecedented episode of high uncertainty in numerous commodity markets that is not necessarily accompanied by a subsequent volatility in the corresponding prices, highlighting the relevance of our uncertainty measure in linking uncertainty to predictability rather than to volatility.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

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  • Tovonony Razafindrabe & Valérie Mignon & Marc Joëts, 2016. "Does the volatility of commodity prices reflects macroeconomic uncertainty?," Post-Print hal-01667080, HAL.
    • Handle: RePEc:hal:journl:hal-01667080
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-01667080
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    Cited by:

    1. Weshah Razzak, 2018. "The Purchasing Power Parity Puzzle: An Update," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 61(2), pages 77-104.
    2. Bakas, Dimitrios & Triantafyllou, Athanasios, 2018. "The impact of uncertainty shocks on the volatility of commodity prices," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 96-111.
    3. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    4. repec:eee:eneeco:v:72:y:2018:i:c:p:331-340 is not listed on IDEAS
    5. Cunado, Juncal & Gil-Alana, Luis A. & Gupta, Rangan, 2019. "Persistence in trends and cycles of gold and silver prices: Evidence from historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 345-354.
    6. Laurent Ferrara & Pierre Guérin, 2018. "What are the macroeconomic effects of high‐frequency uncertainty shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 662-679, August.
    7. repec:eme:cfripp:cfri-06-2016-0066 is not listed on IDEAS
    8. Bao H. NGUYEN & OKIMOTO Tatsuyoshi & Trung Duc TRAN, 2019. "Uncertainty-Dependent and Sign-Dependent Effects of Oil Market Shocks," Discussion papers 19042, Research Institute of Economy, Trade and Industry (RIETI).
    9. repec:eee:intfin:v:51:y:2017:i:c:p:133-141 is not listed on IDEAS

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    Keywords

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    JEL classification:

    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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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