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Competing risks models of Farm Service Agency seven-year direct operating loans

Author

Listed:
  • Bruce L. Dixon
  • Bruce L. Ahrendsen
  • Brandon R. McFadden
  • Diana M. Danforth
  • Monica Foianini
  • Sandra J. Hamm

Abstract

Purpose - The purpose of this paper is to apply duration methods to a sample of Farm Service Agency (FSA) direct, seven-year operating loans to identify those variables that influence the time to loan termination and type of termination. Variables include both those known at time of loan origination and those that characterize the changing economic environment over the life of the loan. Also, to examine the impact of various FSA programs promoting policy objectives. Design/methodology/approach - A systematic sample of 877 seven-year, FSA direct loans originated between October 1, 1993 and September 30, 1996 was collected. Cox regression, competing risks models are estimated as a function of borrower and loan characteristics observable at loan origination. Economic indicator variables emphasizing the farm economy and observed quarterly over the life of the loan are also included as explanatory variables. Findings - Loan characteristics, borrower financial characteristics and degree of borrower interaction with FSA observable at origin are significant variables in determining type of loan outcome (default or paid-in-full) and time to outcome. Changes in the economic environment and farm economy during the life of the loan are significant. Research limitations/implications - The sample consists only of FSA direct loans which implies borrowers are at financial margin. Application of method to agricultural loans from conventional commercial lenders could identify different significant factors. Practical implications - Using length of time to loan termination instead of just type of outcome provides for a richer analysis of loan performance. Loan performance over time is influenced by the larger economy and should be incorporated into loan performance modeling. Originality/value - The study described in the paper demonstrates use of competing risks models on intermediate agricultural loans and develops how this technique can be used to learn about dynamic aspects of loan performance. Sample consists of observations on individual FSA direct loan borrowers. The FSA direct loan program is the major source of credit for agricultural borrowers at the financial margin.

Suggested Citation

  • Bruce L. Dixon & Bruce L. Ahrendsen & Brandon R. McFadden & Diana M. Danforth & Monica Foianini & Sandra J. Hamm, 2011. "Competing risks models of Farm Service Agency seven-year direct operating loans," Agricultural Finance Review, Emerald Group Publishing, vol. 71(1), pages 5-24, May.
  • Handle: RePEc:eme:afrpps:v:71:y:2011:i:1:p:5-24
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    References listed on IDEAS

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    1. Glennon, Dennis & Nigro, Peter, 2005. "Measuring the Default Risk of Small Business Loans: A Survival Analysis Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(5), pages 923-947, October.
    2. Escalante, Cesar L. & Brooks, Rodney L. & Epperson, James E. & Stegelin, Forrest E., 2006. "Credit Risk Assessment and Racial Minority Lending at the Farm Service Agency," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(01), April.
    3. Allen M. Featherstone & Christine A. Wilson & Terry L. Kastens & John D. Jones, 2007. "Factors affecting the agricultural loan decision-making process," Agricultural Finance Review, Emerald Group Publishing, vol. 67(1), pages 13-33, May.
    4. Ambrose, Brent W & Capone, Charles A, 2000. "The Hazard Rates of First and Second Defaults," The Journal of Real Estate Finance and Economics, Springer, vol. 20(3), pages 275-293, May.
    5. Sam Hakim & Mahmoud Haddad, 1999. "Borrower attributes and the risk of default of conventional mortgages," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 27(2), pages 210-220, June.
    6. Erik Heitfield & Tarun Sabarwal, 2004. "What Drives Default and Prepayment on Subprime Auto Loans?," The Journal of Real Estate Finance and Economics, Springer, vol. 29(4), pages 457-477, December.
    7. Nwoha, Ogbonnaya John & Ahrendsen, Bruce L. & Dixon, Bruce L. & Chavez, Eddie C. & Hamm, Sandra J. & Settlage, Daniel M. & Danforth, Diana M., 2005. "Farm Service Agency Direct Farm Loan Program Effectiveness Study," Research Reports 15772, University of Arkansas, Arkansas Agricultural Experiment Station.
    8. Jonathan B. Dressler & Jeffrey R. Stokes, 2010. "Survival analysis and mortgage termination at AgChoice ACA," Agricultural Finance Review, Emerald Group Publishing, vol. 70(1), pages 21-36, May.
    9. Jeffrey R. Stokes & Brent A. Gloy, 2007. "Estimating delinquency migration and the probability of default from aggregate data," Agricultural Finance Review, Emerald Group Publishing, vol. 67(1), pages 75-85, May.
    10. Calum G. Turvey & Alfons Weersink, 1997. "Credit Risk and the Demand for Agricultural Loans," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 45(3), pages 201-217, November.
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    Cited by:

    1. Lin He & Dongsheng Liao, 2012. "Credit NGOs' sustainability in rural financial market: a SWOT analysis on DAYBANG," Humanomics: The International Journal of Systems and Ethics, Emerald Group Publishing, vol. 28(3), pages 200-208, August.

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