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The Nature and Determinants of Volatility in Agricultural Prices

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  • Balcombe, Kelvin

Abstract

The volatility of 19 agricultural commodity prices are examined at monthly and annual frequencies. All of the price series are found to exhibit persistent volatility (periods of relatively high and low volatility). There is also strong evidence of transmission of volatilities across prices. Volatility in oil prices is found to be a significant determinant of volatilities in the majority of series and, likewise, exchange rate volatility is found to be a predictor of volatility in over half the series. There is also strong evidence that stock levels and yields are influencing price volatility. Most series exhibit significant evidence of trends in their volatility. However, these are in a downward direction for some series and in an upward direction for other series. Thus, there is no general finding of long term increases in volatility across most agricultural prices

Suggested Citation

  • Balcombe, Kelvin, 2009. "The Nature and Determinants of Volatility in Agricultural Prices," MPRA Paper 24819, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:24819
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    File URL: https://mpra.ub.uni-muenchen.de/24819/1/MPRA_paper_24819.pdf
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    References listed on IDEAS

    as
    1. Kelvin Balcombe & George Rapsomanikis, 2008. "Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 658-668.
    2. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Volatility; Agricultural Prices;

    JEL classification:

    • N5 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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