Forecasting Animal-Feed Use—the Wild Card of Corn Demand

18 April 2019

The USDA’s recent quarterly Grain Stocks report showed a surprisingly large stockpile of corn, highlighting market participants’ difficulty forecasting a key variable in the report—how much grain farm animals consume.

The USDA reported corn stocks of 8.605 billion bushels as of March 1, the third largest on record and well above market expectations. Corn futures prices reacted sharply, dropping 4.6% for the day to a four-month low, the largest decline in almost three years. Animal-feed use was the main reason behind the market’s surprising level of disappearance which, at 3.33 billion bushels for the three months ended February, was 9% lower than for the same period a year earlier.

Animal-feed use is the wild card of grain consumption, routinely confounding financial and physical commodities traders trying to forecast market price directions. Other variables on corn’s demand side of the balance sheet, mainly exports and ethanol production, can be easier to predict, as these activities are regulated and accounted for in great detail.

The animal-feeding industry, on the other hand, is highly fragmented, with thousands of feeders spread around the country. Indeed, analysts generally only deduce animal-feed-use amounts by subtracting other, better-known variables like exports and ethanol from corn demand totals.

However, an examination of factors that determine animal-feed use suggests that a powerful predictive model can be built to help anticipate demand from feedlots on corn stocks. In this Weekly Insight, we explain what’s behind the persistent glut of corn. We also describe how one of the most opaque variables in corn demand—animal-feed use—can be made more transparent.

Read more:

Production Outlook
Corn Demand
Modeling Feed Use
Conclusion

Production Outlook

US corn stocks have soared for the past three years. The USDA’s latest quarterly stocks reading for March 1 of 8.605 billion bushels was the third-largest ever, behind those of 2018 and 2017. Global corn ending stocks have been similarly lofty, down just moderately in the latest year from a record 351 million tonnes in 2016/17. Weak global corn prices—a fallout from the 2012-2013 price spike and subsequent production boom—have spurred the years-long stocks buildup.

Argentina is half way through its corn harvest, while Brazil is planting and growing its corn. Current expectations are for strong production and commensurately strong exports, increasing pressure on US corn prices.

US production indicated by 2019/20 planting intentions could add to the high stocks level. The USDA’s Prospective Plantings report calls for a 4.1% increase in corn acreage this year, marking a pendulum swing from abnormally large soybean plantings last year. However, that corn expansion may turn out to be smaller than the USDA report suggested, since the USDA report was based on farmer surveys from before the recent massive floods in the Midwest. The next few weeks will reveal how much stored corn may have been ruined by the flooding and how many acres may have to be taken out of production or switched to soybeans because of the weather impact.

As indicated by the red line segment in the above price chart, large quarterly corn stocks were a surprise to the market on March 29, causing a reevaluation of usage and precipitating the sharpest selloff in nearly three years.

Corn Demand

Export markets for US corn are expected to get more competitive on solid South American production. The USDA recently raised Brazilian production estimates based on improved yield expectations, and raised Argentine production projections based on greater corn acreage. At current projections, Brazil and Argentina are each expected to export 30-31 million tonnes of corn, compared with the prior year’s 25 million and 21 million tonnes, respectively. Of course, corn crops in the two countries, both of which are geographically vast, are in very different stages of the growing cycle and could still see setbacks. While Argentina is half way through its harvest, southern Brazil is still only about half way through its growing season, and farmers in northeast Brazil are just half done with their planting.

A resolution of the US-China trade war could potentially open the Chinese market for US corn exports. However, China is currently dealing with its own domestic corn stockpiles, and has encouraged its ethanol industry as a means of putting the stocks to good use before they deteriorate. On the other hand, if China were to increase soybean imports from the US, a likely rise in soy prices would help ease pressure on US corn prices.

The US ethanol industry isn’t helping much to draw down US corn stocks. US ethanol use projections have declined in the last two USDA WASDE reports to 5.50 billion bushels in 2018/19. This would mark a roughly 2% decline from last year’s ethanol allocation at 5.605 billion bushels. While the EPA has proposed rules to raise the proportion of ethanol in gasoline, so-called E15, the proposal still has hurdles to overcome before it could take effect.

Modeling Feed Use

Of the various factors that comprise corn demand, animal-feed use is the hardest for market participants to project. The latest quarterly grain stocks report showed a 3.33-billion-bushel disappearance for the period, 9% lower than last year. This implied lower-than-expected feed use, catching the market by surprise. In the April WASDE report, the USDA lowered estimates for feed and residual use to 5.300 billion bushels, the fourth reduction from the November estimate of 5.575 billion bushels. The USDA lumps feed use together with something called “residual,” which includes factors such as grain losses, making it more difficult to forecast. But feed use makes up the bulk of the category.

Forecasting animal-feed use can be tricky, as the industry is highly fragmented and directly measured data is hard to come by. Still, it may be possible to build a predictive model of feed use using available data on the number of head and their weight at slaughter. One possible technique for cattle could start with the number of new heifers entering the herd, the number of cows currently in the herd, and slaughter volumes reported by the USDA. From these, one-month, six-month, or one-year forecasts could be created for how many cattle are on feed, another statistic the USDA reports.

Next is figuring out how much each animal consumes in feed. Starting with an estimate of grain consumption per day per animal, total feed consumed can be approximated by slaughter weight. Cattle are typically slaughtered at 1,200 pounds, although slaughter weights vary depending on a variety of factors, such as beef prices. Backtesting to correlate feed prices, beef prices, number of animals slaughtered, and slaughter weights helps to refine the animal-feed use model. Another factor that determines the amount of corn fed is feed mix, or the proportion of corn to soy and other ingredients. A broad view of the mix can be estimated by comparing stocks reports for the various grains. Backtesting to correlate feed mix to grain prices can improve the predictive ability of the model. The same template of feed-use calculations can be applied to chickens and hogs.

The level of stocks has a strong effect on prices, with larger stocks suppressing prices by suggesting greater production or lower usage.

High US quarterly corn stocks also raise expectations for ending stocks, measured as of Aug. 31. The USDA most recently raised its projected ending stocks to 2.035 billion bushels. If realized, this number would be quite large by historical standards. Aside from the previous two seasons, ending stocks above two billion bushels have only been achieved twice in the past 30 years. The USDA attributed its latest forecast for ending stocks to steady corn supplies and moderate cuts to ethanol, food, seed, exports, and feed use.

Conclusion

Corn stocks remain at lofty levels in the US and worldwide, with little certainty of what will eventually draw them down. Predicting changes in stocks levels, an important exercise for financial and physical commodities traders, is made more difficult by the opacity of demand for animal feed. Using an array of data, including livestock numbers and slaughter weights, it may be possible to build an effective predictive model of animal-feed use. Such a model would bring greater transparency to the demand side of the corn balance sheet. It could also potentially avoid the kind of dramatic market reaction seen in the wake of the USDA’s latest, unexpectedly high, quarterly corn stocks report.

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