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Commodity Price Volatility under New Market Orientations

Author

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  • Weaver, Robert D
  • Natcher, William C

Abstract

Recent national and international regulatory reforms (e.g. U.S. FAIR and other GATT compliance reforms) in agricultural markets has led some observers to wonder whether the private sector is able to produce a level of price volatility that is socially acceptable. In this paper, we examine the post reform track record of price volatility and its transmission across vertically linked and geographically linked markets. Livestock, grain, and dairy market data (monthly) are considered across the U.S. and E.C. The standard commodity-pricing model supports the hypothesis that competitive storage acts to reduce the volatility of cash prices. Further, speculative attacks and stock outs have been shown to induce increased volatility. This motivates a scope of consideration that includes prices as well as stock levels to assess their contribution to price volatility. The paper considers evidence based on three decades of monthly data and advanced time series techniques. First, univariate volatility estimates based on the autoregressive conditional heteroskedasticity (GARCH) model are evaluated and compared to historical temporal variation to highlight the importance of well grounded estimation of volatility. Next, the relationships between stocks and the conditional mean, as well as the conditional and unconditional variances of the price series, are assessed for dairy and grain products. Finally, reform associated changes in the structure of the transmission of volatility through vertical markets are considered for dairy products and across geographic markets is considered for grains.

Suggested Citation

  • Weaver, Robert D & Natcher, William C, 2000. "Commodity Price Volatility under New Market Orientations," MPRA Paper 9862, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:9862
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    File URL: https://mpra.ub.uni-muenchen.de/9862/1/MPRA_paper_9862.pdf
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    References listed on IDEAS

    as
    1. Brunetti, Celso & Gilbert, Christopher L., 1995. "Metals price volatility, 1972-1995," Resources Policy, Elsevier, vol. 21(4), pages 237-254, December.
    2. Chou, Ray Yeutien, 1988. "Volatility Persistence and Stock Valuations: Some Empirical Evidence Using Garch," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 279-294, October-D.
    3. Aradhyula, Satheesh V. & Holt, Matthew T., 1988. "Garch Time-Series Models: An Application To Retail Livestock Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(02), December.
    4. Cho, David Chinhyung & Frees, Edward W, 1988. " Estimating the Volatility of Discrete Stock Prices," Journal of Finance, American Finance Association, vol. 43(2), pages 451-466, June.
    5. Locke, P R & Sayers, C L, 1993. "Intra-day Futures Price Volatility: Information Effects and Variance Persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 15-30, Jan.-Marc.
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    Citations

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    Cited by:

    1. Shaun K. Roache, 2010. "What Explains the Rise in Food Price Volatility?," IMF Working Papers 10/129, International Monetary Fund.

    More about this item

    Keywords

    Price volatility; price risk; inventories; commodity prices;

    JEL classification:

    • 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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