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Analyzing FSA Direct Loan Borrower Payback Histories: Predictors of Financial Improvement and Loan Servicing Actions

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  • Landerito, Aiko O.
  • Dixon, Bruce L.
  • Ahrendsen, Bruce L.
  • Hamm, Sandra J.
  • Danforth, Diana M.

Abstract

Classical and count data regression models are estimated to predict improvement in three key financial indicators—net worth, debt-to-asset ratio and current ratio—as well as the number of loan restructurings and delinquencies. Data consist of Farm Service Agency direct loans originated in fiscal years 1994-1996. Models to predict outcomes vary by loan type. Models explaining variation in the financial measures have modest explanatory power but initial levels of debt-to-asset ratio and current ratio are significant in explaining changes in debt-to-asset ratios and current ratios, respectively. Models explaining number of restructurings and delinquencies for operating loans have satisfactory explanatory power. Increasing crop revenues to total farm revenues and increasing farm size lead to increased loan servicing actions

Suggested Citation

  • Landerito, Aiko O. & Dixon, Bruce L. & Ahrendsen, Bruce L. & Hamm, Sandra J. & Danforth, Diana M., 2009. "Analyzing FSA Direct Loan Borrower Payback Histories: Predictors of Financial Improvement and Loan Servicing Actions," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49340, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea09:49340
    DOI: 10.22004/ag.econ.49340
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    References listed on IDEAS

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    1. 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(1), pages 1-15, April.
    2. 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 Limited, vol. 67(1), pages 13-33, May.
    3. 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.
    4. Ani L. Katchova, 2005. "Factors affecting farm credit use," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 65(2), pages 17-29, November.
    5. A. Colin Cameron & Pravin K. Trivedi, 1986. "Econometric models based on count data. Comparisons and applications of some estimators and tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    6. Allen M. Featherstone & Gregory A. Ibendahl & J. Randy Winter & Aslihan Spaulding, 2005. "Farm financial structure," Agricultural Finance Review, Emerald Group Publishing, vol. 65(2), pages 97-117, July.
    7. Ani L. Katchova, 2005. "Factors affecting farm credit use," Agricultural Finance Review, Emerald Group Publishing, vol. 65(2), pages 17-29, July.
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    Keywords

    Agricultural Finance; Farm Management;

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