Are the USDA forecasts rational?

Are the USDA forecasts rational?  This is the question that AEDE’s Siddhartha Bora and Ani Katchova, together with Todd Kuethe, have answered in their recently published article in the American Journal of Agricultural Economics (AJAE).  Ani Katchova is the Farm Income Enhancement Chair and Siddhartha Bora is a Ph.D. student working with the Farm Income Enhancement team.

Background

Their AJAE study builds upon another recently published paper in the Applied Economic Perspectives and Policy by Isengildina-Massa, Karali, Kuethe, and Katchova which found evidence of an underprediction bias in the USDA farm income forecasts. The bias toward underprediction has been especially prominent in the early farm income forecasts. These prior results seem to suggest that USDA may not want to paint a rosy picture of the farm economy in the beginning of the year. However, as the year progresses, they revise their forecasts, and these revised forecasts tend to be less biased.  This evidence of an under-prediction bias in the USDA forecasts, which is also reported in several other studies, raises the question whether the USDA forecasters are “rational” in producing such forecasts.

USDA forecasts and their importance

Forecasters may produce biased forecasts but may yet be “rational” if they are minimizing their loss due to forecast errors. Bora, Katchova, and Kuethe (2020) evaluate the “rationality” of two major series of USDA forecasts, the farm income forecasts released by the Economic Research Service and the World Agricultural Supply and Demand Estimates (WASDE) price and production forecasts produced by the World Agricultural Outlook Board.  The farm income forecasts for a given calendar year are first released in February, and subsequently revised three times before producing the actual values in August of the following year. These forecasts have important implications for farm policy, as they are frequently mentioned in policy debates in the media and in Congress. WASDE forecasts released between 9-12th day of each month. These forecasts are very important for commodity markets, and previous studies have shown that WASDE announcements significantly impact commodity futures prices.  Both the farm income and WASDE forecasts are heavily cited statistics produced by the USDA, and eagerly awaited by farmers and stakeholders in the agricultural sector.

Findings and main contributions

Using a novel multivariate asymmetric framework, Bora, Katchova, and Kuethe find that USDA forecasts are rational under the assumption that USDA places different weights on under- and over-prediction errors. For example, in case of net cash income forecasts, the USDA forecasters tend to under-predict the actual net cash income since they have a higher cost associated with over-prediction errors. This approach is different from traditional studies, which typically do not differentiate between under- and over-prediction errors by minimizing a mean square (MSE) loss.  “Instead of using traditional approaches of finding bias, by assuming rationality with different costs of over-prediction versus under-prediction, we are able to show that the USDA forecasters are rational,” Katchova said.  This novel framework provides a new direction to similar lines of research on bias.

Another contribution of their study is that they jointly evaluate a series of forecasts of several variables. This makes sense since the USDA releases several variables as part of the same report. Evaluating each variable separately might ignore any interactions between them. Finally, while the results are mostly consistent with previous findings, they yield an alternative interpretation of the results of prior research.  Their study tells the story of “why” the USDA forecasters produce biased forecasts.

A timely and relevant research

This research on the rationality of the USDA forecasts is very timely given the recent economic downturn in the agricultural sector.  Due to the recent pandemic and resulting uncertainty about farm income, and the farm economy in general, USDA forecasts have received additional scrutiny from a variety of forecast users.  Bora, Katchova, and Kuethe address questions that are relevant to a wide range of players in the agricultural sector who use the USDA forecasts, including farmers, lenders, agricultural business leaders, and agricultural policymakers.

Another implication of their findings is that they may help inform future revisions of USDA forecast models and procedures.  Katchova served as a chair of the review panel for the USDA Farm Income Forecast and Wealth Program which provided recommendations for improving the estimation methods to the USDA Farm Income team.  Such revisions might improve the accuracy of the forecasts, and increase the transparency of the forecasting process. “Given the importance of the farm income and WASDE forecasts to farm policy and markets, an investigation into rationality the USDA forecasts was long warranted, and our study fills this gap,” Bora said.

 

References:

Bora, S.S., A.L. Katchova, and T.H. Kuethe. “The Rationality of USDA Forecasts under Multivariate Asymmetric Loss.American Journal of Agricultural Economics (2020), https://doi.org/10.1111/ajae.12142

Isengildina-Massa, O., B. Karali, T.H. Kuethe, A.L. Katchova. “Joint Evaluation of the System of USDA’s Farm Income Forecasts.”  Applied Economics Perspectives and Policy (2020),  https://doi.org/10.1002/aepp.13064