IDEAS home Printed from https://ideas.repec.org/a/ags/jloagb/131367.html
   My bibliography  Save this article

Determinants of FSA Direct Loan Borrowers' Financial Improvement and Loan Servicing Actions

Author

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

Abstract

Regression models of Farm Service Agency borrower net worth, debt-to-asset ratio, and loan servicing actions over an average seven-year period following loan origination are estimated to identify determinants of borrower financial progress over time. Results show significantly increasing net worth and debt-to-asset ratio. The change in net worth increases and the change in debt-to-asset ratio decreases as time in loan program increases. Increasing origination net worth tends to decrease loan servicing actions. Socially disadvantaged and beginning farmer loans perform similarly to nonprogram loans. Borrowers originating limited resource loans experience significant net worth impacts relative to borrowers originating regular FSA loans.

Suggested Citation

  • Dixon, Bruce L. & Ahrendsen, Bruce L. & Landerito, Aiko O. & Hamm, Sandra J. & Danforth, Diana M., 2010. "Determinants of FSA Direct Loan Borrowers' Financial Improvement and Loan Servicing Actions," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 28(2), pages 1-19.
    • Handle: RePEc:ags:jloagb:131367
    DOI: 10.22004/ag.econ.131367
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/131367/files/JAB_Fall2010__03.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.131367?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jill M. Phillips & Ani L. Katchova, 2004. "Credit score migration analysis of farm businesses: conditioning on business cycles and migration trends," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 64(1), pages 1-15, May.
    2. Dixon, Bruce L. & Ahrendsen, Bruce L. & Nwoha, O. John & Hamm, Sandra J. & Danforth, Diana M., 2007. "FSA Direct Farm Loan Program Graduation Rates and Reasons for Exiting," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 39(3), pages 471-487, December.
    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. 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.
    5. Ani L. Katchova, 2005. "Factors affecting farm credit use," Agricultural Finance Review, Emerald Group Publishing, vol. 65(2), pages 17-29, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Goeringer, L. Paul & Goodwin, Harold L., Jr. & Dixon, Bruce L. & Popp, Michael P., 2013. "EnVesting in an Agricultural Legacy: Design and Implementation of a Targeted Young and Beginning Farmer Loan Program in Arkansas," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143037, Southern Agricultural Economics Association.
    3. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    4. Laila Touhami Morghem & Khawlah Ali Abdalla Spetan, 2020. "Determinants of International Migration: An Applied Study on Selected Arab Countries (1995-2017)," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 6-19.
    5. Kapeliushnikov, Rostislav & Kuznetsov, Andrei & Demina, Natalia & Kuznetsova, Olga, 2013. "Threats to security of property rights in a transition economy: An empirical perspective," Journal of Comparative Economics, Elsevier, vol. 41(1), pages 245-264.
    6. Bettina Becker & Martin Theuringer, 2000. "Macroeconomic Determinants of Contingent Protection: The Case of the European Union," IWP Discussion Paper Series 02/2000, Institute for Economic Policy, Cologne, Germany.
    7. T.R.L. Fry & R.D. Brooks & Br. Comley & J. Zhang, 1993. "Economic Motivations for Limited Dependent and Qualitative Variable Models," The Economic Record, The Economic Society of Australia, vol. 69(2), pages 193-205, June.
    8. Rui Baptista & Joana Mendonça, 2010. "Proximity to knowledge sources and the location of knowledge-based start-ups," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(1), pages 5-29, August.
    9. Robert J. Barro & Rachel M. McCleary, 2016. "Saints Marching In, 1590–2012," Economica, London School of Economics and Political Science, vol. 83(331), pages 385-415, July.
    10. Metiu, Norbert, 2021. "Anticipation effects of protectionist U.S. trade policies," Journal of International Economics, Elsevier, vol. 133(C).
    11. Bowker, James Michael & Starbuck, C. Meghan & English, Donald B.K. & Bergstrom, John C. & Rosenberger, Randall S. & McCollum, Daniel W., 2009. "Estimating the Net Economic Value of National Forest Recreation: An Application of the National Visitor Use Monitoring Database," Faculty Series 59603, University of Georgia, Department of Agricultural and Applied Economics.
    12. Thomas Bolli & Martin Woerter, 2013. "Technological Diversification and Innovation Performance," KOF Working papers 13-336, KOF Swiss Economic Institute, ETH Zurich.
    13. Becker, Gary S. & Rubinstein, Yona, 2011. "Fear and the response to terrorism: an economic analysis," LSE Research Online Documents on Economics 121740, London School of Economics and Political Science, LSE Library.
    14. Gary King, 1989. "A Seemingly Unrelated Poisson Regression Model," Sociological Methods & Research, , vol. 17(3), pages 235-255, February.
    15. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    16. Christopher J. W. Zorn, 1998. "An Analytic and Empirical Examination of Zero-Inflated and Hurdle Poisson Specifications," Sociological Methods & Research, , vol. 26(3), pages 368-400, February.
    17. Jong-Hyun Kim & Yong-Gil Lee, 2021. "Factors of Collaboration Affecting the Performance of Alternative Energy Patents in South Korea from 2010 to 2017," Sustainability, MDPI, vol. 13(18), pages 1-25, September.
    18. Dionne, Georges & Laberge-Nadeau, Claire & Desjardins, Denise & Messier, Stéphane & Maag, Urs, 1998. "Analysis of the economic impact of medical and optometric driving standards on costs incurred by trucking firms and on the social costs of traffic accidents," Working Papers 98-6, HEC Montreal, Canada Research Chair in Risk Management.
    19. Niklas Elert, 2014. "What determines entry? Evidence from Sweden," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 55-92, August.
    20. Marullo, Cristina & Ahn, Joon Mo, 2024. "Knowledge tensions and decision-making challenges in open innovation: Standardization as a de-biasing mechanism," Technovation, Elsevier, vol. 136(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:jloagb:131367. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aeaggea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.