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Pre and Post Recession Input Allocation Decisions of Farm Credit System Lending Units

Author

Listed:
  • Cesar Escalante

    (University of Georgia)

  • Minrong Song

    (University of Georgia)

Abstract

This article estimates and analyzes the technical efficiencies and input allocation decisions of lending associations and their own banks under the U.S. Farm Credit System (FCS) during the period 2005-2011. The sample time period allows for the analysis of the operating decisions of FCS lending units under pre- and post-economic recession conditions. Results indicate that even while FCS lending units were plagued with higher funding costs during the recession, their input allocation decisions revealed fund sourcing strategies that leaned towards using more of the cheaper inputs. Moreover, smaller lending associations were found to have maintained relatively higher levels of technical efficiency.

Suggested Citation

  • Cesar Escalante & Minrong Song, 2017. "Pre and Post Recession Input Allocation Decisions of Farm Credit System Lending Units," Proceedings of Economics and Finance Conferences 4807110, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iefpro:4807110
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    File URL: https://iises.net/proceedings/8th-economics-finance-conference-london/table-of-content/detail?cid=48&iid=003&rid=7110
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    References listed on IDEAS

    as
    1. Cesar Escalante & Minrong Song & Charles Dodson, 2016. "FSA farm loan repayment under economic recession and drought conditions," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 76(4), pages 445-461, November.
    2. Hughes, Joseph P. & Mester, Loretta J. & Moon, Choon-Geol, 2001. "Are scale economies in banking elusive or illusive?: Evidence obtained by incorporating capital structure and risk-taking into models of bank production," Journal of Banking & Finance, Elsevier, vol. 25(12), pages 2169-2208, December.
    3. Trang Dang & David Leatham & Bruce A. McCarl & Ximing Wu, 2014. "Measuring the efficiency of the Farm Credit System," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 74(1), pages 38-54, April.
    4. Brian C. Briggeman & Philip Kenkel, 2008. "Customer segmentation perceptions of farm credit associations," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 68(2), pages 227-236, November.
    5. Atkinson, Scott E. & Primont, Daniel, 2002. "Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions," Journal of Econometrics, Elsevier, vol. 108(2), pages 203-225, June.
    6. Christopher Metli & Kevin J. Stiroh, 2003. "Now and then: the evolution of loan quality for U.S. banks," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 9(Apr).
    7. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    8. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    Keywords

    Farm Credit System; allocative efficiency; input allocation; technical efficiency; financial inputs; deposits;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • E39 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Other
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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