The Conventional-Organic Crop Yield Gap: Evidence from Farm-Level Data

Timothy A. Delbridge1 and Robert P. King - Department of Applied Economics, University of Minnesota, St. Paul, Minnesota, USA

Farm Table says:

This research paper is highly recommended to be used on any county for the application even though they use Redwood County as it is the site of a University of Minnesota agricultural research and outreach center.

Overview of the Conventional-Organic Yield Gap

Several long-term experimental trials in the Midwestern United States have shown that organic crop production methods can achieve yields nearly as high as those achieved by conventional methods. This yield competitiveness, along with significant price premiums available for organic crops, has led authors of economic studies to conclude that organic cropping systems may be more profitable than conventional systems. It is possible that experimental trials tend to overstate the yield potential of organic farms because relatively small plot sizes facilitate the management of the more complex organic system.

Most of the information that is available on organic crop yields comes from experimental trials. In the Midwest, there have been several long-term cropping system trials that have aimed to compare the crop yields of organic and conventional systems under identical soil and weather conditions.

Data Analysis

The objective of this study is to explore the possibility of a selection effect among organic crop producers, and the implication that self-selection in the transition decision has on farm-level yield data. Using data from partially organic farms in Minnesota that have grown the same crop organically and conventionally in the same year, the conventional corn and soybean yields achieved by these farms are significantly lower than the average yields achieved in their counties. An estimated linear relationship between the conventional yields and the organic yields produced by the same farms. The relationship is statistically significant, suggesting that farms that achieve high conventional yields tend to also achieve high organic yields.

Together, these results indicate that data derived from farms that have chosen to adopt organic management likely understate the organic yield potential of the full population of conventional crop producers. Accurate predictions of organic yield outcomes are particularly important for business planning purposes and the design and implementation of organic crop insurance products.

Conventional farms that transition to organic production, and thus have no organic yield history with which to purchase crop insurance products, could also be affected by low organic yield averages. Although average-yielding conventional crop growers that transition to organic production may have higher yields and thus find organic t-yields less attractive than established organic farms, the effect on expected indemnities is likely to be quite small.

This analysis raises the question: how can data on organic production outcomes are improved?

• Although RMA is well positioned to gather further data on organic yields from those farms that chose to purchase crop insurance, relatively low participation rates among organic crop farms and possible adverse selection problems may make RMA yield data unreliable for many applications.

• Another option would the expansion of existing farm survey programs, such as ARMS, so that individual farms are followed over multiple years. This would allow a panel data structure that could provide information on within-farm temporal variation of organic crop yields that is currently unavailable.

• An alternative approach that could help provide data on farm-level organic production and financial outcomes would be 14 to further encourage (i.e. subsidize) participation in farm business management programs, similar to the program available in Minnesota which gathered the data used in this study.

This comparison was drawn from state-wide crop enterprise reports that included both rented and owned acres. Although several other crops are represented in the primary data, only corn and soybean have an adequate number of observations for statistical analysis. Since land quality can also vary within a farm we cannot be certain that the organic and conventional yield observations come from the land of equal quality. However, there is no reason to suspect that organic cropland on a particular farm is any better or worse than the farm’s conventional cropland. The calculation for corn is: 164.1 × (0.45 + 0.249 × 1) = 114.9, and for soybean is: 41.0×(0.45+0.196×1) = 26.5. This assumes that production costs do not change from the baseline to higher yield scenario. (. Producer premium = total premium − premium subsidy )

2014 - Minnesota - Timothy A. Delbridge1 and Robert P. King - Department of Applied Economics, University of Minnesota, St. Paul, Minnesota, USA
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