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Best of NAMA 2024


By Dr. Scott Irwin, University of Illinois-Champaign

Projecting the size of the U.S. corn crop depends on two components--harvested acreage and yield per acre. The USDA Prospective Planting report released near the end of March provides a starting point in making this important projection. The report showed that U.S. farmers intend to plant 90 million acres of corn during the 2024 planting season. Combined with an estimate of the difference between planted and harvested acreage, this can be used to project harvested acreage. Yield is then the only remaining component needed to project crop size. Given the difficulty of forecasting summer weather conditions so far in advance, a simple "trend" projection is typically used at this point in the season. Despite the seeming simplicity of making a trend projection, there is always debate about the best way of going about it. Currently, there is more than the usual amount of debate because U.S. average corn yields have moved in a fairly narrow range for more than a decade. Some argue that the growth of trend corn yield in the U.S. has slowed considerably since 2013 (Boussios, 2024), while others caution about projecting trend yields from a small sample of years (farmdoc daily, April 16, 2024). The purpose of this article is to use a crop weather model of the U.S. average yield of corn to formally test whether the trend rate of growth in the U.S. average corn yield has slowed in recent years.


We begin by reviewing the history of U.S. corn yields over 1980 through 2023 in Figure 1. The dashed blue line is the estimated trend line using all the observations over this time period. The trend coefficient is 1.92, which indicates that, on average, the U.S. average corn yield trnds to increase slightly less than two bushels per year. The red dashed line uses only the observations for 2013 through 2023 to estimate trend, and the slope of this line is much flatter, around one bushel per year. Projecting the lines forward a year in the future results in trend yield estimates for 2024 of 181.3 bushels per acre using the entire 1980 through 2023 sample and 178.2 bushels using the smaller 2013 through 2023 sample. The 3.1-bushel difference in trend yield projections is not large, but one can easily see that it would not take very many more years for the difference to become pronounced.

There is not enough information in Figure 1 to determine which of the two lines to use in projecting trend yield for 2024. The reason is that weather is not considered, and variation in weather is the dominant factor driving corn yields from year-to-year (farmdoc daily, October 9, 2023). For example, it is possible that what appears to be a slowing of the rate of growth in the U.S. average corn yield since 2013 is in fact simply a run of less than stellar growing season weather. This issue is not new and has been debated and analyzed for many years (e.g., Thompson, 1975; Tannura, Irwin, and Good, 2008).

To disentangle trend changes from weather impacts, a model is needed that considers both factors simultaneously. Fortunately, this type of crop weather model was developed and presented in several recent farmdoc daily articles (October 9, 2023; April 8, 2024; April 29, 2024). The "Thompson-style" regression model used in these articles relates the U.S. average corn yield to a time trend, the percentage of the crop planted late, and an array of weather variables. The updated version of the model estimated here uses data from 1980 through 2023 and includes the following explanatory variables: i) a linear time trend variable to represent technological change, ii) the percentage of the corn crop planted late, iii) linear functions of preseason (September-March), April, and August precipitation, iv) quadratic functions of June and July precipitation, and v) linear functions of April, May, June, July, and August temperatures. The late planting variable is defined as the percentage of U.S. corn acreage planted after May 30th from 1980 through 1985 and after May 20th from 1986 onwards. While there are certainly other specifications that could be considered, the model explains 98 percent of the variability in the U.S. average yield of corn, and therefore captures the most important factors that drive yield at this level of aggregation. Complete details on the model specification can be found in the October 9th article.

The monthly weather data are collected for 10 key corn-producing states (Iowa, Illinois, Indiana, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin). These 10 states typically accounted for about 75-80 percent of total U.S harvested acreage of corn during the sample period. An aggregate measure for the 10 states was constructed using harvested corn acres to weight state-specific observations. The weighted-average monthly weather variables are used to represent weather observations for the entire U.S. corn crop. Precipitation data are monthly totals and temperature data are monthly averages. The National Weather Service is the source for the weather data via the Midwest Regional Climate Center.

Table 1 presents the regression estimates for the crop weather model for 1980 through 2023. The model has a high explanatory power, with an R2 of 98 percent. The signs of the coefficient estimates are as expected. The time trend coefficient indicates that the trend rate of growth in the U.S. average corn yield is slightly less than two bushels per year, very close to the unconditional trend coefficient presented in Figure 1. Each percentage of the U.S. corn crop planted late is estimated to reduce corn yield by 0.35 bushels per acre. The crop weather variables are statistically significant at the ten percent level or better except for pre-season precipitation and April-June temperature.

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