Farm Program Selection Using a Risk Programming Approach

U.S. crop producers have historically managed risk by participating in federal price and income support programs. While early farm programs focused on reducing agricultural output, programs in the last two decades have become structured more like insurance. Calculating payments from current programs has become more involved and deciding which programs will best fit a producer’s needs is, unfortunately, not always straightforward. The choice of which Title I farm program to enroll in is modeled as a quadratic integer programming problem. This framework is used to determine optimum program selection for representative upland cotton production in Hale County, Texas.

Authors

Publication Details

Journal
AgEcon Search (University of Minnesota, USA)
Published
2026-09-04
DOI
https://doi.org/10.22004/ag.econ.410251
Primary Topic
Agricultural risk and resilience
Type
article
Field-Weighted Citation Impact
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article

Farm Program Selection Using a Risk Programming Approach

John R.C. Robinson, Jeffrey R. Wright
AgEcon Search (University of Minnesota, USA)
Agricultural risk and resilience
article

Farm Program Selection Using a Risk Programming Approach

John R.C. Robinson, Jeffrey R. Wright
article en

Abstract

U.S. crop producers have historically managed risk by participating in federal price and income support programs. While early farm programs focused on reducing agricultural output, programs in the last two decades have become structured more like insurance. Calculating payments from current programs has become more involved and deciding which programs will best fit a producer’s needs is, unfortunately, not always straightforward. The choice of which Title I farm program to enroll in is modeled as a quadratic integer programming problem. This framework is used to determine optimum program selection for representative upland cotton production in Hale County, Texas.

AgEcon Search (University of Minnesota, USA)
No poverty
Openalex Percentile: Top 13%
Agricultural risk and resilience
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