The Conservation Reserve Program was first established by the Food Security Act of 1985, with the primary purpose of preventing damage to highly erodible soils, made worse by intensified farming practices. Since its inception, the CRP has grown to become the largest federal, private-land retirement program in the United States with an approximately $2 billion annual budget. The Agricultural Act of 2014 mandates a reduction in the enrollment cap from 32 million acres to 24 million acres by 2018. The reduction coupled with the higher than average commodity prices makes the decision of whether or not to reenroll in to the CRP a difficult one for producers with expiring land. Expiring lands will equal almost 2 million acres in the year 2015, and approximately 7.1 million acres over the life of the farm bill.
This research will develop a computer based decision aid that incorporates all major aspects of the decision when considering enrollment in the CRP, to be used by landowners and producers. These considerations include eligibility, the Environmental Benefits Index (EBI), the producers bid level, and evaluation of practice options within the CRP and options outside the CRP. The goals of this research are to produce a computer web based decision aid, as described above, with specific emphasis on a few key outputs. These include a probability of acceptance measure, the Net Present Value of all options available to the landowner/manager, and a measure of what that landowner’s/manager’s optimal bid is.
The methodology of this study relies on the use of simulation using the excel add-in Simetar. Users of the program are allowed to enter details about the land being considered for CRP enrollment that the decision aid then uses to test scenarios for the land. Five hundred randomized point estimates are generated and compiled as a cumulative distribution function comparison chart, stoplight chart, and several other customized output representations for the user’s consideration.
This thesis details a test of an Agriculture and Food Policy Center representative farm. The results, given the input data taken from the farm, suggest that the least risky option for this farm with the highest net returns is to enroll the land in CRP. It is important to note that this is simply a test of one farm and not a recommendation for all producers. Also, the results could be changed given different assumptions about the producer’s goals.
The study concludes that including risk in the decision making process regarding CRP enrollment is a critical factor when determining the most financially rewarding result. Including riskiness in the decision making process warrants the use of a decision tool, like the one presented in this thesis
