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An Analysis of Lenders' Influence on Agricultural Producers' Risk Management Decisions

Published online by Cambridge University Press:  05 September 2016

Thomas O. Knight ,
Ashley C. Lovell ,
M. Edward Rister  and
Keith H. Coble
Thomas O. Knight
Affiliation:
Texas A&M University System
Ashley C. Lovell
Affiliation:
Texas A&M University System
M. Edward Rister
Affiliation:
Texas A&M University System
Keith H. Coble
Affiliation:
Texas A&M University System
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Abstract

Agricultural lenders have a stake in and are in a position to influence their borrowers' management decisions. Risk management practice adoption is an area in which lenders might want to exercise this influence. This study employs logistic statistical models to estimate lenders' influence on crop producers' decisions regarding use of three alternative risk management practices: federal multiple-peril crop insurance, crop hail and fire insurance, and forward contracting. Results suggest lenders can exert significant influence on these decisions but that poor communication between lenders and borrowers likely reduces this influence.

Keywords

risk managementcrop insuranceforward contracting
Type
Submitted Articles
Information
Journal of Agricultural and Applied Economics , Volume 21 , Issue 2 , December 1989 , pp. 21 - 33
Copyright
Copyright © Southern Agricultural Economics Association 1989

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References

Barry, P.J., and Willmann, D.R.. “A Risk-Programming Analysis of Forward Contracting with Credit Constraints.” Amer. J. Agr. Econ., 58(1976):62–70.CrossRefGoogle Scholar
Boggess, W.G., Anaman, K.A., and Hanson, B.D.. “Importance, Causes, and Management Responses to Farm Risks: Evidence From Florida and Alabama.” So. J. Agr. Econ., 17,2(1985):105–116.Google Scholar
Capps, O.R. and Kramer, R.A.. “Analysis of Food Stamp Participation Using Qualitative Choice Models.” Amer. J. Agr. Econ., 67(1985):49–59.CrossRefGoogle Scholar
Dillman, D. Mailand Telephone Surveys: The Total Design Method. New York: John Wiley and Sons, 1979.Google Scholar
Harris, K.S. and Baker, C.B.. “Does Hedging Increase Credit for Illinois Farmers?” No. Cent. J. Agr. Econ., 3(1981):47–52.Google Scholar
Maddala, G.S. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press, 1983.CrossRefGoogle Scholar
Patrick, G.R. “Producers' Attitudes, Perceptions and Management Responses to Variability.” In Risk Analysis for Agricultural Production Firms: Concepts, Information Requirements and Policy Issues. Department of Agricultural Economics, University of Illinois; AE-4574, July, 1984,197–256.Google Scholar
Pflueger, B.W. and Barry, P.J.. “Crop Insurance and Credit: A Farm Level Simulation Analysis.“ Agr. Fin. Rev., 46(1986):1–12.Google Scholar
Sonka, S.T. Hornbaker, R.H., and Hudson, M.A.. “Managerial Performance and Income Variability for a Sample of Illinois Cash Grain Producers.” No. Cent. J. Agr. Econ., 11(1989):39–47.Google Scholar