Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-29T10:37:53.525Z Has data issue: false hasContentIssue false
  • English
  • Français

Objective Evaluation for Agricultural Lending

Published online by Cambridge University Press:  28 April 2015

William E. Hardy Jr.  and
Johno B. Weed
William E. Hardy Jr.
Affiliation:
Department of Agricultural Economics and Rural Sociology, Auburn University
Johno B. Weed
Affiliation:
Department of Agricultural Economics and Rural Sociology, Auburn University
Get access Rights & Permissions [Opens in a new window]

Extract

One of the more significant changes in the U. S. agricultural industry in recent years has been the increased use of credit to finance production and capital expenditures. Since 1970, outstanding farm debt has more than doubled, rising at an average annual rate of 9.3 percent. However, because net farm income has not increased as fast, the debt burden for farm operators has become relatively higher (Melichar and Waldheger).

This increase in debt load has made financial evaluation more difficult for lenders. Narrow profit margins and increased average loan size have made financial institutions more aware of the need to determine, for their loan portfolio, how borrower and agricultural business characteristics relate to debt repayment ability and loan quality.

Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 12 , Issue 1 , July 1980 , pp. 159 - 164
Copyright
Copyright © Southern Agricultural Economics Association 1980

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderberg, Michael R.Cluster Analysis for Applications. New York: Academic Press, 1973.Google Scholar
Bauer, Larry L. and Jordan, John P.. “A Statistical Technique for Classifying Loan Application.” University of Tennessee Agr. Exp. Sta. Bull. 476, 1971.Google Scholar
Churchill, Gilbert A. Jr., Nevin, John R., and Watson, R. Richard. “Credit Scoring—How Many Systems Do WeNeed?” Credit World 66(Nov. 1977):6–11.Google Scholar
Dunn, Daniel J. and Frey, Thomas L.. “Discriminant Analysis of Loans for Cash Grain Farms.” Agr. Finan. Rev. 36(April 1976).Google Scholar
Eisenbeis, Robert A.Discriminant Analysis and Classification Procedures. Lexington, Ky.: D. C. Heath and Co., 1972.Google Scholar
Johnson, Russell B. and Hagan, Albert R.. “Agricultural Loan Evaluation with Discriminant Analysis.” S. J. Agr. Econ. 5(1973):57–62.Google Scholar
Johnson, Stephen C. “Hierarchial Clustering Schemes.” Psychometrika (Sept. 1967).Google Scholar
Melichar, Emanuel and Waldheger, Martha. Agricultural Finance Databook. Washington, D.C.: Division of Research Statistics, Federal Reserve System, Nov. 1979.Google Scholar
Nelson, Aaron G., Lee, Warren F., and Murray, William G.. Agricultural Finance. Ames: Iowa State Press, 1973.Google Scholar
Peters, William S. and Summers, George W.. Statistical Analysis for Business Decisions. Engle-wood Cliffs, N. J.: Prentice-Hall, Inc., 1968.Google Scholar