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The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets

Author

Listed:
  • MacDonald, Stephen
  • Ash, Mark
  • Cooke, Bryce

Abstract

We derive a set of stylized facts about USDA’s soybean supply and demand forecasts and draw implications from these results for efforts to improve the accuracy of these forecasts. USDA’s short run soybean supply and demand forecasts are inefficient, with several key variables significantly biased throughout much of the annual forecast cycle. Bias and other characteristics have varied significantly over recent decades, and evaluation efforts intended to guide forecast improvement need to focus on very recent sample years and seasonally disaggregated data. USDA should expand the information set used in its forecasting of U.S. soybean yields, take note of its mid-season downward bias in its Brazilian production forecasts, and shift the weight of its early-season focus for China’s soybean consumption estimates towards forecasts of growth rates and reduce the weight it applies to forecasting consumption and trade by China in terms of levels. During 2004-2015, downward-biased U.S. production forecasts and upward-biased foreign excess supply forecasts resulted in downward-biased U.S. export forecasts throughout much of USDA’s annual forecasting cycle. Twenty years earlier, this downward bias was confined to the end of the forecasting cycle, whereas U.S. soybean ending stock forecasts have been upward biased for decades across much of the forecasting cycle. The forecasts for U.S. soybean exports are also characterized by smoothing, with strong correlation between month-to-month forecast revisions towards the later months of USDA’s annual forecasting cycle.

Suggested Citation

  • MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017. "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper 87545, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:87545
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    References listed on IDEAS

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    More about this item

    Keywords

    Forecast evaluation; overlapping forecasts; bias; smoothing; agriculture; soybeans; China; United States; Brazil; Argentina; USDA; WASDE;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q17 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agriculture in International Trade

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