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Informational roles of commodity prices for monetary policy: evidence from the Euro area

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  • Go Tamakoshi

    ()
    (Kobe University)

  • Shigeyuki Hamori

    ()
    (Kobe University)

Abstract

This paper examines the linear and nonlinear causal relationships between commodity price indices and macroeconomic variables such as the consumer price index (CPI) and the industrial production index (IP) in the Euro zone. We use monthly time series data from January 1999 to December 2011 and employ a solid nonparametric, nonlinear causality test by Diks and Panchenko (2006) as well as the linear Granger causality test using Lag Augmented Vector Autoregression (LA-VAR) approach. Main findings of the study include: (i) Oil price only linearly Granger-causes the CPI and hence can be seen as a better information variable for the general price level than non-energy commodity price. (ii) There is a significant one-way linear causality from commodity price to IP. (iii) A significant nonlinear relationship between CPI and IP is identified by the nonparametric causality test. Such results are relevant for monetary policy makers who wish to mitigate the possible future inflation by using commodity or oil price indices as information variables.

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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 32 (2012)
Issue (Month): 2 ()
Pages: 1282-1290

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Handle: RePEc:ebl:ecbull:eb-12-00292

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Related research

Keywords: Monetary policy; Non-parametric nonlinear Granger test; Lag-augmented VAR; Commodity prices; Oil prices;

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  1. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, Elsevier, vol. 27(5), pages 1103-1115, September.
  2. Shigeyuki Hamori, 2007. "The information role of commodity prices in formulating monetary policy: some evidence from Japan," Economics Bulletin, AccessEcon, vol. 5(13), pages 1-7.
  3. Fourcans, Andre & Vranceanu, Radu, 2007. "The ECB monetary policy: Choices and challenges," Journal of Policy Modeling, Elsevier, Elsevier, vol. 29(2), pages 181-194.
  4. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, Elsevier, vol. 30(5), pages 2673-2685, September.
  5. repec:ebl:ecbull:v:5:y:2007:i:13:p:1-7 is not listed on IDEAS
  6. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, Elsevier, vol. 66(1-2), pages 225-250.
  7. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 30(9-10), pages 1647-1669.
  8. Awokuse, Titus O. & Yang, Jian, 2002. "The Informational Role Of Commodity Prices In Formulating Monetary Policy: A Reexamination," Staff Papers, University of Delaware, Department of Food and Resource Economics 15834, University of Delaware, Department of Food and Resource Economics.
  9. Kyrtsou, Catherine & Labys, Walter C., 2006. "Evidence for chaotic dependence between US inflation and commodity prices," Journal of Macroeconomics, Elsevier, Elsevier, vol. 28(1), pages 256-266, March.
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