Abstract
Pecan price forecasting is important to growers attempting to reduce income variability. Random coefficient regression (RCR) and OLS approaches were applied to annual price forecasts. Variance analysis was conducted to forecast pecan price during harvest. Price variation was postulated to be caused by two sets of variables: structural economic variables and unknown factors. RCR results consistently outperformed OLS results in annual price forecasting. The variation of harvest prices was found to be generated by a different process each year, making accurate predictions difficult. Annual price forecasts, however, can provide additional information to pecan growers and shellers for marketing decision-making.
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Wu, XL., Florkowski, W.J. Forecasting annual and harvest pecan prices. J Econ Finan 17, 131–138 (1993). https://doi.org/10.1007/BF02920644
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DOI: https://doi.org/10.1007/BF02920644