The World Agricultural Supply and Demand Estimates (WASDE) reports play a central role in shaping expectations for major agricultural commodities, yet their fixed-event structure limits their use in forward-looking policy analysis. This study develops 12-month-ahead fixed-horizon price forecasts for corn, soybeans, and wheat by applying an optimal-weighting approach and a standard ad hoc aggregation benchmark to overlapping current- and next-year WASDE releases. We evaluate the constructed forecasts against realized prices and futures market expectations using Diebold-Mariano tests, Mincer-Zarnowitz efficiency regressions, and forecast encompassing tests. Optimal weighting improves point accuracy for all three commodities and forecast efficiency for corn. Accuracy gains are most pronounced for soybeans, moderate for corn, and modest but consistent for wheat. We further show that the fixed-horizon transformation eliminates statistically significant seasonal patterns in soybean forecast errors that persist under both ad hoc and futures-based specifications, suggesting that a meaningful share of the forecast error seasonality documented in prior literature reflects the fixed event design rather than the underlying information environment. These results demonstrate that reframing WASDE forecasts at a constant horizon improves accuracy, efficiency, and interpretability, with direct applications to farm budgeting, forward pricing, and revenue planning.
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