The Farm Service Agency (FSA) direct farm loan program provides credit to family‐sized farms including those operated by beginning farmers and socially disadvantaged applicants. Approximately 37% of all U.S. farms are estimated to be eligible for FSA direct loans when farm size, credit needs, farming experience, and occupation are taken into account. However, market penetration rates for various borrower cohorts range from 0.8% to 4.6% for FY 2000S2003. In general, beginning farmers have weaker financial characteristics than non‐beginning farmers. Yet, the same result is not found when comparing socially disadvantaged farmers with non‐socially disadvantaged farmers, such that there are few significant differences or the differences in financial characteristics are mixed. Overall, results indicate FSA direct farm loan borrowers have weaker financial characteristics than eligible, non‐FSA direct farm loan borrowers, implying FSA is serving farmers likely to be denied credit by commercial lenders.
Farm Service Agency (FSA) direct loans are intended to provide transitory credit to creditworthy borrowers unable to obtain conventional credit at reasonable terms. Farm loan program (FLP) effectiveness is measured in part by how readily direct loan borrowers graduate to conventional credit. A survey of FSA borrowers originating direct loans during fiscal years 1994-1996 is used to estimate graduation rates. A majority of 1994-1996 loan originators did exit the direct FLP by November 2004. A multinomial logit model indicates financial strength at origination resulted in greater likelihood of farming without direct loans approximately 9 years after loan origination.
The probability of a business paying various amounts of money for an e-commerce presence ultimately depends on demographic features, experiences with e-commerce from a buyer's and seller's perspective, technological expertise, and knowledge of e-commerce opportunities and limitations. Estimating functions to assign probabilities associated with the willingness to pay for an e-commerce presence will assist in forecasting regional likelihood of certain profiles paying various monetary amounts for an e-commerce presence. In addition, if services are provided at no cost by a third party, value to a society will be maximized by selecting profiles with the highest willingness to pay.
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