How USDA Forecasts Retail Food Price Inflation-01

Annemarie Kuhns, Richard Volpe, Ephraim Leibtag, and Ed Roeger

How USDA Forecasts Retail Food

Price Inflation

What Is the Issue?

Each month, USDA's Economic Research Service (ERS) publishes wholesale and retail price

forecasts for various food categories and subcategories, and policymakers, food suppliers, and

researchers rely on these numbers. In recent years, as commodity and food prices have become

more volatile and less easily predicted, users of the forecasts have expressed a greater need for

more accurate forecasts.

ERS continually explores ways to improve its forecasts as new data and methods become avail-

able. In 2011, ERS revised its food price forecast methodology to use more rigorous statistical

techniques and capture the impacts of the multistage U.S. food supply system on wholesale and

retail food price formation. This updated approach incorporates far richer data available for

farm, wholesale, and input prices, which could lead to more accurate forecasts.

What Did the Study Find?

· The precision of ERS food price forecasts has observably improved with the revised meth-

odology. As a result, ERS food price forecasts are, on average, closer to the realized inflation

figures.

· ERS forecasts using the new methodology required fewer and smaller revisions. For a given

year, forecasts are subject to revision during a 17-month period. An average of 3.2 changes

were made per food category using the new, current forecasting methods compared with 3.7

revisions using the previous method, and the average size of the adjustments dropped from

2.6 to 2.1 percentage points.

· Another measure of forecast accuracy was the extent to which initial forecasts differed from

the actual Consumer Price Index (CPI) values. Using revised forecast methodology, the

average difference from CPI values was 2 percentage points, compared with 2.6 percentage

points for the previous methods.

· Although forecast accuracy and precision have improved relative to less rigorous

approaches used by ERS before 2011, more years of data are needed to fully assess forecast

performance.