Yield Adjustment Factor in Dairy Revenue Protection

Nate Donnay, StoneX

Nate Donnay

There are a lot of great things about Dairy Revenue Protection (DRP) program and I am generally a fan of it to help dairy farmers hedge their milk price risk. One of the complicated factors in the DRP payout calculation is the “yield adjustment factor.” The program is designed to hedge the milk price for farmers, not protect them against a drop in milk production, so the final payout each quarter is adjusted based on how milk production per cow came in at the state level versus the USDA forecast for production per cow in each state or region. If production per cow is higher than the USDA was forecasting, then the payment (indemnity) is reduced for the quarter since farmers made up for some of the short-fall in prices with higher production, at least in the eyes of the DRP formula.

The system should work fine as long as the USDA can accurately predict milk production per cow.

The USDA has not disclosed the methodology they are using to create the expected milk per cow that is used in the DRP formula, but it appears that they are using a model that takes into account the long-run trend, seasonality, and whether recent production has been running above or below trend. For decades, the uptrend in production per cow was relatively stable, which made it simple to forecast, but the trend is no longer stable and there are large underlying changes in the structure of the industry that make it harder to forecast.

Some dairy farmers in California have been upset about the yield adjustment factor in DRP, because California production per cow keeps coming in higher than the USDA was forecasting which reduces the indemnity payment. If you look at the trend in production per cow for California, it trended down from 2011 to 2017 as high feed costs, drought and supplier base programs all worked to limit growth in the state. The USDA forecast model is taking all that into account and forecasting relatively weak growth for the state, but the trend has shifted and is running quite strong recently. That means actual production is coming in above expected production per cow on a consistent basis and reducing the indemnity. However, the forecast error has gotten smaller for 2020, so it’s possible the USDA recognizes this issue and maybe the forecasts going forward will take into account the big shift in trend better.

While production in California is consistently coming in higher than the expected level, yields in Wisconsin have consistently been coming in lower than the USDA was expecting and that is consistently boosting the DRP indemnity in that state. Poor quality feed and a shift from Holstein toward Jersey and Jersey crosses are likely keeping yield growth in the state lower than the long-run trend.

 





 

Forecasting is hard. I should know, I generate hundreds of forecasts every month for all kinds of global supply, demand and price variables. On top of trying to build the best forecast possible, the forecasters inside of the USDA have to deal with all of the bureaucracy and create forecasting models that can stand up to scrutiny. Sometimes the best models from a long-run perspective, or the best models from an academically defendable perspective don’t give the best short-term forecasts. On top of that, DRP is a relatively new program and the USDA probably doesn’t have a lot of experience generating these detailed quarterly state-by-state forecasts.

 





 

So, I’m not going to be overly critical that the forecasts have been consistently biased for some states. I don’t think the USDA is intentionally biasing their forecasts to benefit one state or another. As a user of DRP it might be worthwhile to track the yield adjustment factor for your state/region over time. If it has been negative in recent quarters, then it will probably be negative in the next quarter or two and you can expect your indemnity to be adjusted down a little.

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Editor’s note: Nate Donnay is the Director of Dairy Market Insight at StoneX (INTL FCStone Financial Inc.) and has been applying his interest in large complicated systems and statistical analysis to the international and U.S. dairy markets since 2005. As a consultant, he has worked with clients at all levels of the dairy marketing chain from the farm level up to processors and packaged foods companies, food distributors and restaurants as well as connected industries like banks, private equity groups, government agencies, and industry associations. Through ongoing reports or one-off client specific projects, he helps them understand the short and long-term trends and the underlying relationships driving the market and what that means to their businesses.

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