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Commodity price uncertainty in developing countries

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  • Jan Dehn
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    Abstract

    Commodity export price uncertainty is typically measured as the standard deviation of the terms of trade, but this approach encounters at least three objections. First, terms of trade indices are unsuitable as proxies for commodity price movements per se. Secondly, the shortness of terms of trade time series makes them inappropriate as a basis for constructing time varying uncertainty measures. Thirdly, simple standard deviation measures ignore the distinction between predictable and unpredictable elements in the price process, and therefore risk overstating uncertainty. The paper examines the features of commodity price uncertainty in developing countries using a new data set of unique quarterly aggregate commodity price indices for 113 developing countries over the period 1957Q1-1997Q4. A total of six different uncertainty measures are constructed, which confirm the importance of distinguishing between predictable and unpredictable components in the price process when measuring uncertainty. A a positive and highly significant relationship between commodity export concentration and commodity price uncertainty is found for all the measures. No obvious link is found between a country’s regional affiliation and its exposure to uncertainty. Similarly, there is no apparent relationship between a country’s experience of uncertainty and the type of commodities which dominates its exports. The exception is oil producers, which face greater uncertainty. The greater uncertainty faced by these countries can, however, be attributed almost exclusively to discrete and well publicised discrete oil shocks. A GARCH based measure of uncertainty indicates considerable time variation in uncertainty. Uncertainty is sometimes characterised by discrete spikes, while uncertainty in countries exhibits a secular increase in uncertainty over time. The majority of countries have seen uncertainty which exhibits considerable persistence. It is not clear what lies behind the time variation in uncertainty, which cannot be explained with reference to relatively time invarying export concentration

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    File URL: http://www.csae.ox.ac.uk/workingpapers/pdfs/20-12text.pdf
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    Bibliographic Info

    Paper provided by Centre for the Study of African Economies, University of Oxford in its series CSAE Working Paper Series with number 2000-12.

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    Date of creation: 2000
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    Handle: RePEc:csa:wpaper:2000-12

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    1. Angus Deaton & Guy Laroque, 1990. "On The Behavior of Commodity Prices," NBER Working Papers 3439, National Bureau of Economic Research, Inc.
    2. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, October.
    3. Hong Liang & C. John McDermott & Paul Cashin, 1999. "How Persistent Are Shocks to World Commodity Prices?," IMF Working Papers 99/80, International Monetary Fund.
    4. C. John McDermott & Alasdair Scott & Paul Cashin, 1999. "The Myth of Comoving Commodity Prices," IMF Working Papers 99/169, International Monetary Fund.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April.
    7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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