Credit risk-rating system for agricultural leases

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dc.contributor.authorJarvis, Marilyn Adamsen
dc.contributor.committeecochairMcGuirk, Anya M.en
dc.contributor.committeecochairKohl, David M.en
dc.contributor.committeememberWhite, Alexander B.en
dc.contributor.departmentAgricultural Economicsen
dc.date.accessioned2014-03-14T21:52:26Zen
dc.date.adate2009-12-23en
dc.date.available2014-03-14T21:52:26Zen
dc.date.issued1992-12-05en
dc.date.rdate2009-12-23en
dc.date.sdate2009-12-23en
dc.description.abstractAgricultural leases issued to forestry, dairy and cash crops operators from 1980-1992 are reviewed to determine factors statistically significant in predicting risk level (probability of default and/or probability of late payment) of the lessee for each industry. From a previous study of Telmark, 1990, literature review and the Recommendations of the Farm Financial Standards Task Force financial, operator/lessee and farmer/operator variables are selected for analysis. Data obtained from Telmark,Inc. are used to develop a model to explain lease risk level of the forestry, dairy, and crops industries. Results show that for forestry the following financial, lessee/operator, and farmer/operator variables are useful in determining riskiness: operating expense to revenue, cash flow coverage, capital turnover, years in business, gross revenue, and owner's equity. The dairy results indicate that the following variables are important: current ratio, cash flow coverage, return on assets, capital turnover, operating expense to revenue, FHA loan secured, owner's equity, and gross revenue. The crop results indicate percent equity, current ratio, cash flow coverage ratio, return on assets, capital turnover, operating expense to revenue, interest to income, real estate owned, years in business, FHA loan-secured, and owner's equity are significant variables for determining lease risk. Using the results from these models, a weighted average cost of misclassifying a lease is calculated. This is used to develop a profit maximizing criterion for determining whether a lease is high or low risk. The need for future work is discussed. In the area of weighted average cost of misclassifying a lease, additional information on the costs of leasing and riskiness of the population would aid in reducing the misclassified leases in the portfolio. Further study exploring some of the unexpected results in this study would be beneficial to both the lessee and the lessor.en
dc.description.degreeMaster of Scienceen
dc.format.extentx, 134 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-12232009-020554en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12232009-020554/en
dc.identifier.urihttp://hdl.handle.net/10919/46406en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V855_1992.J378.pdfen
dc.relation.isformatofOCLC# 27689319en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1992.J378en
dc.subject.lcshAgricultural crediten
dc.subject.lcshCredit ratingsen
dc.subject.lcshCredit -- Managementen
dc.subject.lcshCredit -- Risk factorsen
dc.titleCredit risk-rating system for agricultural leasesen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineAgricultural Economicsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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