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An Analysis of Factors that Affect the Quality of Federal Land Bank Loans

Published online by Cambridge University Press:  05 September 2016

William E. Hardy Jr. ,
Stanley R. Spurlock ,
Donnie R. Parrish  and
Lee A. Benoist
William E. Hardy Jr.
Affiliation:
Department of Agricultural Economics and Rural Sociology, Alabama Agricultural Experiment Station, Auburn University
Stanley R. Spurlock
Affiliation:
Department of Agricultural Economics, Mississippi Agricultural Experiment Station, Mississippi State University
Donnie R. Parrish
Affiliation:
Alabama Cooperative Extension Service
Lee A. Benoist
Affiliation:
Federal Land Bank of Jackson
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Abstract

Financial conditions existing in agriculture are placing severe pressure on lenders as well as borrowers. Data from both good and foreclosed Federal Land Bank loans were analyzed to determine the most important characteristics leading to the failure of loans. The analysis was completed by comparing means through t-tests and the development of a discriminant model. The ratio of total debt service to total income, the debt to asset ratio, the ratio of total loan amount to appraised value, and the ratio of acres in security to acres owned were determined to be the most important discriminating variables.

Keywords

financial analysiscredit scoringdiscriminant analysisloan evaluation
Type
Submitted Articles
Information
Journal of Agricultural and Applied Economics , Volume 19 , Issue 2 , December 1987 , pp. 175 - 182
Copyright
Copyright © Southern Agricultural Economics Association 1987

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References

Bauer, L. L., and Jordan, J. P.. “A Statistical Technique for Classifying Loan Applications.” University of Tennessee Agr. Exp. Sta. Bull. 476, 1971.Google Scholar
Dunn, D. J., and Frey, T. L.. “Discriminant Analysis of Loans for Cash Grain Farms.” Agr. Finan. Rev., 36(1976):60–66.Google Scholar
Durand, D. Risk Elements in Consumer Installment Financing. Nat. Bur. Econ. Res., New York, 1941.Google Scholar
Fisher, R. A. “The Use of Multiple Measurements in Taxonomic Problems.” Annals of Eugenics, 8(1936):179–188.Google Scholar
Hardy, W. E. Jr, and Patterson, J. E.. “An Objective Evaluation of Federal Land Bank Borrowers.” Highlights of Agricultural Research, Alabama Agr. Exp. Sta., 30,2(1983):3.Google Scholar
Hardy, W. E. Jr, and Weed, J. B.. “Objective Evaluation for Agricultural Lending.” So. J. Agr. Econ., 12(1980):159–163.Google Scholar
Hora, S.C, and Wilcox, J. B.. “Estimation of Error Rates in Several Population Discriminant Analysis.” J. Mkt. Res., 19(1982):57–61.Google Scholar
Johnson, R. B., and Hagan, A. R.. “Agricultural Loan Evaluation with Discriminant Analysis.” So. J. Agr. Econ., 5, 2(1973):57–62.Google Scholar
Nath, R., and Pavur, R.. “Error Rate Estimation in Discriminant Analysis Via Simulation.” Proceedings Sixteenth Annual Meeting of Southeast American Institute for Decision Sciences, 1986:144–146.Google Scholar
Raufner, B., and Pelzer, D.. “Land Changing Hands.” Agri Finance, 27,12(1985):26–29.Google Scholar