WASDE: Market impact and accuracy; Oh, really?
Their analysis is that WASDE reports are not always 100% accurate, but they also point to the three reasons they found for the errors.
Tendencies of USDA forecast staff members:
The university economist say, “The first one deals with forecasters’ abilities and reflects behavioral characteristics and tendencies…Thus, forecasting behavior may be different with respect to predicting positive vs. negative change and extreme vs. moderate rate of change.” The economists say there is a personal reaction built into the estimation process that may have a positive or negative reaction to the numbers being calculated. And they surmise, “..reaction to positive vs. negative change in WASDE forecasts would likely be due to mis-calibration of forecasters’ reaction to information and can result in optimism as well as pessimism. Given the public nature of the forecasts and their ability to affect markets, these biases should be unintended.”
They found that, “corn and soybean forecasters tend to overcorrect previous mistakes. For example, a 1% overestimation in corn production in the previous year is likely to be followed by a 0.3% underestimation in current year. On the other hand, wheat forecasters tend to repeat their previous errors. Thus a 1% overestimation in wheat production in the previous year is likely to be followed by a 0.2% overestimation in current year.”
Incorporation of macro-economic data:
According to the university-based study, “The second source reflects data that are not (efficiently) included in the forecasts. Previous studies showed that USDA forecasts do not encompass simple time-series models. In our study we investigate whether USDA forecasts fail to efficiently take into account macroeconomic data and tend to show mistakes during certain economic conditions, which has not been analyzed in previous studies of these forecasts.” They say, “In our study we investigate whether USDA forecasts fail to efficiently take into account macroeconomic data and tend to show mistakes during certain economic conditions.” For example, they point to the economic changes in commodity value and production resulting from changes in policy from one Farm Bill to the next. That has pointed to more corn acreage and less wheat and soybean acres, which they contend the USDA forecasters did not efficiently incorporate into their estimates.
They discovered that not all of the macro-economic factors in the marketplace are efficiently incorporated in the WASDE reports—particularly exchange rate, oil price-related data, and inflation:
- “USDA forecasters appear to overestimate corn and soybean price and underestimate use (corn feed and residual and soybean exports) as well as supply (soybean production) during the periods of increasing oil prices.”
- And regarding the errors related to exchange rates, they said “Appreciation of U.S. exchange rate is associated with overestimation of corn and soybean price, underestimation of some domestic use categories (corn feed and residual, soybean crushings, and seed and residual, wheat food and feed and residual), underestimation in wheat ending stocks, and overestimation in wheat exports and seed use.”
- Higher inflation is associated with underestimation of corn ending stocks and wheat price, overestimation of wheat feed and residual use, as well as overestimation of soybean production and seed and residual use. Increasing tendencies for underestimation of corn exports and ending stocks, soybean production and wheat food, seed and ending stocks are detected during the Renewable Fuel Act (RFA) period (2005-2010), while wheat feed and residual use is increasingly overestimated during this time.”