Commodity Price Volatility under New Market Orientations
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.
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"GARCH Time Series Models: An Application to Retail Livestock Prices,"
Food and Agricultural Policy Research Institute (FAPRI) Publications
88-wp29, Food and Agricultural Policy Research Institute (FAPRI) at Iowa State University.
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