@article{Isengildina:285801,
      recid = {285801},
      author = {Isengildina, Olga and MacDonald, Stephen and Xie, Ran and  Sharp, Julia},
      title = {Smoothing in USDA’s Commodity Forecasts},
      address = {2013-04},
      series = {NCCC-134 Applied Commodity Price Analysis, Forecasting,  and Market Risk Management},
      year = {2013},
      abstract = {This study investigates the rationality of monthly  revisions in annual forecasts of supply, demand, and price  for U.S. corn, cotton, soybeans, and wheat, published in  the World Agricultural Supply and Demand Estimates over  1984/85 through 2011/12. The findings indicate that USDA’s  forecast revisions are not independent across months, and  that forecasts are typically smoothed. Adjustment for  smoothing in a subset of forecasts (2002/03 – 2011/12)  showed weak results: marginal improvements in accuracy were  limited to wheat production and cotton production and  domestic use while deterioration in accuracy was observed  in all other cases. Smoothing coefficients were highly  unstable over time. Case studies for corn focused on  correction for a structural break and the impact of  forecast size and direction, but did not lead to  improvements in accuracy. Case studies for October  revisions of soybean production forecasts suggest that ten  year rolling estimation and correcting for outliers using  leverage may help improve accuracy in the adjusted  forecasts.},
      url = {http://ageconsearch.umn.edu/record/285801},
      doi = {https://doi.org/10.22004/ag.econ.285801},
}