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Forecasting Agricultural Commodity Prices With Limited Data Sets

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  • Jacque, Andrew Eliel

Abstract

Many developing countries wish to, but do not publish forecasts of commodity prices. One difficulty often cited is the length (shortness) of the data series. This study tried to determine whether this was a valid reason. Price data for two commodities in a specific country, where the problem is acknowledged were utilized in a case study approach. Existing models were evaluated for applicability to the data series. The identified models were estimated with estimation data and then while keeping the model parameters constant, prices were forecasted in the out-of-sample period. The error associated with the forecast of each model was calculated and the relationship between quantity of data and model accuracy evaluated. The error values of all the models were high. The results of the analyses were inconclusive in terms of the study objectives.

Suggested Citation

  • Jacque, Andrew Eliel, 1991. "Forecasting Agricultural Commodity Prices With Limited Data Sets," Graduate Research Master's Degree Plan B Papers 10998, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    • Handle: RePEc:ags:midagr:10998
    DOI: 10.22004/ag.econ.10998
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    Keywords

    Demand and Price Analysis;

    Statistics

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