Advanced Search
MyIDEAS: Login

Factors affecting the agricultural loan decision-making process

Contents:

Author Info

  • Allen M. Featherstone
  • Christine A. Wilson
  • Terry L. Kastens
  • John D. Jones

Abstract

Agricultural lenders in today’s environment face many challenges when evaluating the creditworthiness of farm borrowers. To address these challenges, a survey was conducted with financial institutions in Kansas and Indiana where agricultural lenders were asked for their responses to hypothetical agricultural loan requests. Each loan request differed by the borrower’s character, financial record keeping, productive standing, Fair Isaac credit bureau score, and credit risk. Lenders provided information about themselves and their financial institutions. The survey data obtained determine the relative importance of financial and nonfinancial information when analyzing agricultural loan applications. Tobit models are estimated to identify the borrower and lender characteristics that are important in determining loan approval, while OLS models are used to investigate the factors that affect interest rates offered to farm borrowers. The results offer a comparison of agricultural lending between two important agricultural states and provide lenders with insight on the factors that influence the decision-making process of other agricultural lenders.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.emeraldinsight.com/Insight/viewContentItem.do;jsessionid=43AE8F21925462C6AD91A4975FB7E4CD?contentType=Article&contentId=1784595
Download Restriction: Cannot be freely downloaded

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Emerald Group Publishing in its journal Agricultural Finance Review.

Volume (Year): 67 (2007)
Issue (Month): 1 (May)
Pages: 13-33

as in new window
Handle: RePEc:eme:afrpps:v:67:y:2007:i:1:p:13-33

Contact details of provider:
Web page: http://www.emeraldinsight.com

Order Information:
Postal: Emerald Group Publishing, Howard House, Wagon Lane, Bingley, BD16 1WA, UK
Email:
Web: http://www.emeraldinsight.com/afr.htm

Related research

Keywords: Agricultural loans; Credit bureau score; Credit evaluation; Interest rates;

Other versions of this item:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Allen M. Featherstone & Laura M. Roessler & Peter J. Barry, 2006. "Determining the Probability of Default and Risk-Rating Class for Loans in the Seventh Farm Credit District Portfolio," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 28(1), pages 4-23.
  2. Barry, Peter J. & Ellinger, Paul N., 1989. "Credit Scoring, Loan Pricing, And Farm Business Performance," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 14(01), July.
  3. Gustafson, Cole R. & Beyer, Ronald J. & Saxowsky, David M., 1991. "Credit Evaluation: Investigating the Decision Process of Agricultural Loan Officers," Proceedings: 1991 Regional Committee NC-161, September 23-24, 1991, St. Louis, Missouri 130940, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. 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.
  2. 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.
  3. Myyrä, Sami, & Pietola, Kyosti & Heikkilä, Anna-Maija, 2011. "Farm Level Capital: Capital positions, structures, the dynamics of farm level investments, capital accumulation and leverage positions," Factor Markets Working Papers 105, Centre for European Policy Studies.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:eme:afrpps:v:67:y:2007:i:1:p:13-33. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Louise Lister).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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