Conservation Reserve Program: relationships between agricultural commodity output prices, input costs, and slippage in Kansas

• Main Author: George, Jacob H.
• Language: en_US
• Published: Kansas State University 2009
• Subjects: Conservation Reserve Program; Slippage; Geography (0366)
• Online Access: http://hdl.handle.net/2097/1475

Master of Arts === Department of Geography === Lisa M. Harrington === The Conservation Reserve Program (CRP) was established by the Food Security Act of 1985 for the purpose of retiring environmentally sensitive cropland for a period of ten to fifteen years. The initial focus of the program was to reduce on-site soil erosion and excess crop production, however the program benefits were later expanded to include water quality and wildlife habitat among others. The overall success of the CRP has been questioned due to the occurrence of slippage. The term ‘slippage’ as it relates to the CRP occurs when producers plant newly cultivated land or fallow acres, offsetting acreage that is retired through enrollment in the reserve program. The goal of this study is to measure the degree to which slippage has affected the CRP within the state of Kansas; and to analyze the relationship between agricultural commodity output prices and input cost with respect to county level slippage rates. Annual slippage calculations for all one-hundred and five counties within Kansas for the period of 1995-2005 reveal significant spatial disparity, with the vast majority of slippage occurring in the western two-thirds of the state. Annual fluctuations in slippage rates varied both regionally and at the county level. Maximum annual slippage was seen in the northwest, with slippage rates in excess of 100 percent; thus the CRP was entirely ineffective in regards to reducing overall land in production. Minimums were located primarily in the southeast and included slippage values below zero percent; indicating a reduction in acreage beyond that of the CRP. To analyze the relationship between agricultural commodity output prices and input costs with CRP slippage, a multivariate regression model was used. The regression analysis ultimately showed a significant lack of fit within the model, indicating the need for additional predictor variables in order to account for variations in CRP slippage rates. Although the model does indicate the presence of a minor relationship between the selected variables of agricultural commodity output prices and input costs with CRP slippage rates, further analysis is needed to identify additional county level variables impacting slippage.