WICST Commodity Price Analysis

Don Schuster [1]

One of the theories behind the Wisconsin Integrated Cropping Systems Trial is that having multiple crops for an individual farm will help spread out price risk. In mono-cropping systems, a producer is taking the chance that the one crop they grow will return the best profit for them.

In this paper, we exam the sensitivity of cropping systems 1, 2 and 3 with respect to corn, soybeans and winter wheat price correlation.

Commodity prices were taken from the harvest months, October for corn and soybeans and August for winter wheat. The prices for the corn and soybeans were obtained from the Wisconsin Agricultural Statistics Service. Nine regions divide the corn and soybean price, the southeast was used for Lakeland the south central was used for Arlington. The regional price data goes back to 1978.

Unfortunately, Wisconsin Agricultural Statistics Service doesn’t keep regional data for winter wheat. As a result, the state average August cash price for winter wheat was used at both locations.

Results

The basis between Arlington and Lakeland shows a slight price advantage to Arlington in both corn and soybeans. The advantage for Arlington’s corn was $0.01518/bu from 1978-99 and $.0025/bu for the trial years of 1992-99. Soybeans at Arlington averaged $0.01664/bu from 1978-99 over Lakeland and by $0.0275/bu over Lakeland during the trial period.

To examine the price sensitivity for the cropping systems, the Pearson correlation coefficient was used. The Pearson correlation coefficient is a measure of association, or covariation, between two variables, the coefficient (r) ranges between –1 and +1. The correlation coefficient would be +1 for the case of perfect positive correlation, and an r near zero would indicate little or no correlation.[2] The results are as follows:

During the trial years of 1992 –99, the prices of the three commodities at both sites, are positively correlated. Arlington and Lakeland’s corn and soybeans prices are highly correlated (0.92) while soybeans and wheat are the least positively correlated (0.87). This indicates that these commodities did have some price variation over that time period, but not a significant amount.

However, over a 20-year period (1978–99) the correlation is somewhat weaker, but still not significantly difference between the sites. The corn–soybeans correlation drops to 0.83 and corn-wheat combinations to 0.79. The soybean-wheat combination again, had the least amount of correlation of any of the combinations-only 0.66 for both sites.

Conclusion

In the short run, it does not appear that there is much price risk advantage in diversifying rotations. So from a price perspective, planting corn year in and year out should not affect the variation in the bottom-line all that much of any particular farmer.

In the long run, there seems to be enough of a difference that by diversifying, one could protect against some price risk. By adding wheat and soybeans to a corn rotation, a farmer a farm could spread the risk out in hopes of getting a good price for at least one of the commodities.

It should be pointed out that this is only looking at the commodity price, and not any production factors that could greatly affect the outcome of any particular operation and it is based on marketing month prices only.

[1] Email: schuster@aae.wisc.edu

[2] Econometrics Basic and Applied, Aaron C. Johnson, Jr., Marvin B. Johnson, Rueben C. Buse, 1987, p.90

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