Explaining county‐level variability in farm service agency farm loan programs

Dodson, Charles B.; Koenig, Steven R.

doi:10.1108/00215080380001149

Cited by 8 publications

(6 citation statements)

References 6 publications

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“…Meanwhile, small community banks, defined as those having less than $250 million in total assets, comprised over half of all new FSA bank guaranteed loan volume. While overall market share for FSA guarantees in recent years has ranged between 4 and 5 percent, FSA guarantees tend to be much more important in certain regions and among certain groups (Dodson and Koenig, 2003). Specifically, usage of FSA-guaranteed programs has tended to be greater among young and beginning farmers and in more economically depressed regions.…”

Section: Commercial Banks and Fsa-guaranteed Loan Programsmentioning

confidence: 98%

“…In a subsequent analysis, Settlage et al (2006) found banks with greater experience originating FSA-guaranteed loans had higher probabilities of originating guaranteed loans in the future. Dodson and Koenig (2003) used county-level data to model the use of FSA farm loan programs between 1995 and 1999. Escalante et al (2006) found that the debt-repayment margin ratio and current ratio influenced loan approval for FSA direct and guaranteed loans.…”

Section: Commercial Banks and Fsa-guaranteed Loan Programsmentioning

confidence: 99%

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Bank size, lending paradigms, and usage of Farm Service Agency's guaranteed loan programs

Dodson

2014

Agricultural Finance Review

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Purpose -An established paradigm in small business lending is segmented by bank size with large banks more likely to lend to large informationally transparent firms while small banks are more likely to lend to small informationally opaque firms. In light of banking consolidation, this market segmentation can have implications for credit availability. Federal loan guarantees, such as those provided by USDA's Farm Service Agency (FSA) may reduce the risks of lending to informationally opaque firms thereby mitigating the impacts of the bank size lending paradigm. This paper aims to discuss these issues. Design/methodology/approach -This analysis utilized a binomial logit procedure to determine if there was any empirical evidence that smaller community banks served a unique clientele of farmers when making FSA-guaranteed loans. The analysis relied on a unique data set which incorporated detailed data on farm businesses receiving FSA-guaranteed loans, loan characteristics, as well as information about the originating bank and characteristics of the local credit markets. Findings -Results were consistent with the bank size lending paradigm with smaller banks being less likely to engage in fixed-asset lending, and more likely to serve a riskier and less established clientele when making guaranteed loans. Research limitations/implications -Data limitations did not permit detailed analysis of banks larger than $250 million in total assets nor for consideration of non-bank lenders. An expansion by these lender groups into serving more informationally opaque borrowers could mitigate any adverse impacts arising from fewer small community banks. Practical implications -The results suggested that Federal guarantees do not completely eliminate the relative informational advantages of large and small size banks. And, continued bank consolidation, such that there are fewer small community banks, could result in less credit availability among smaller, less creditworthy farm businesses. Social implications -While FSA guarantees may not enhance a large banks propensity to serve informationally opaque farm borrowers, they may enhance the ability of smaller community banks to serve groups specifically targeted through FSA lending programs; the provision of credit to family farmers who, despite being creditworthy, are unable to obtain credit at reasonable rates and terms. Originality/value -The analysis examines relationship between bank size and the use of FSA guarantees using a unique data set which incorporated information on FSA-guaranteed loans, farm financial characteristics, along with characteristics of commercial banks which participated in the FSA-guarantee program.

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Section: Commercial Banks and Fsa-guaranteed Loan Programsmentioning

confidence: 98%

Section: Commercial Banks and Fsa-guaranteed Loan Programsmentioning

confidence: 99%

Bank size, lending paradigms, and usage of Farm Service Agency's guaranteed loan programs

Dodson

2014

Agricultural Finance Review

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“…The borrower region was defined as the ten USDA Farm Production regions (US Department of Agriculture, Economic Research Service, 2010). Distinct regional differences in FSA loan programs, as shown in previous studies, would suggest regional differences in loan duration (Dodson and Koenig, 2003;Ahrendsen et al, 2011).…”

Section: Model Specificationmentioning

confidence: 52%

Modeling duration of FSA operating and farm ownership loan guarantees

Long

Ahrendsen

Dixon

et al. 2016

AFR

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to identify determinants of feasible outcome events (expired with no loss, settled for loss, still performing) and time to event of Farm Service Agency (FSA) operating and farm ownership (FO) loan guarantees. Design/methodology/approach -Data on 19,126 FSA guaranteed loans, which were made by various lenders to farmers who have limited ability to obtain loans from normal sources without the Federal guarantee, were collected. Cox proportional hazards models for operating loans (OLs) and FO loans are estimated to identify borrower characteristics, loan characteristics, lender types, and farm and macroeconomic environment factors that influence guarantee outcomes. Findings -Loans with different characteristics (loan amount, loan term, lender type, region originated) and assistance programs (Beginning Farmer, Interest Assistance) have differing guarantee outcomes. Contemporaneous variables, in particular delinquency status, have a significant impact on guarantee outcomes. Research limitations/implications -All loans were originated in calendar years 2004 and 2005. Since FO loans may have as long as 40 year terms, results are not as robust for FO loans as for OLs. Practical implications -Different loan characteristics and macroeconomic conditions significantly influence the occurrence of possible guarantee outcomes and time to the outcomes. Originality/value -Guaranteed loans are the primary method of government credit assistance to US farm operators. Data on individual borrowers have been difficult to obtain for much of the life of the guaranteed program because loan applications are held privately. This study provides insight on how various factors drive guarantee performance which is useful to policy makers trying to increase guaranteed loan program efficiency.

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“…The difference in cost makes clear the high per loan subsidy of the IA program and why IA loans are so attractive to borrowers and their lenders. Dodson and Koenig (2003) seek to explain the disparity across US counties in utilizing FSA farm loan programs. They use a Tobit regression model to test for the relationship between observed use-patterns of FSA loan programs and related factors.…”

Section: Related Studiesmentioning

confidence: 99%

“…The variable equals one if at least one IA loan was made in the county over the five years. Dodson and Koenig (2003) hypothesize that the use of the IA program within a county would increase guaranteed loan use. The IA binary variable has a positive and significant effect on the share of farmers obtaining FSA loan guarantees, as expected.…”

Section: Related Studiesmentioning

confidence: 99%

A triple hurdle model of US commercial bank use of guaranteed operating loans and interest assistance

Ahrendsen

Dixon

Settlage

et al. 2011

Agricultural Finance Review

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Purpose -The purpose of this paper is to estimate a three-equation model of US commercial bank usage of the Farm Service Agency's (FSA) guaranteed operating loan and interest assistance programs. Also, to identify the key farm and banking variables that affect the decision to use loan guarantees and the volume of loans with interest assistance. Design/methodology/approach -A triple hurdle, three-equation system is estimated to model three decisions: to participate in the FSA operating loan program; whether to use interest assistance given the decision to participate in the operating loan program; and then the degree of participation in the interest assistance program. Statistical selection is modeled. Data on almost all commercial banks in the USA from 1995 to 2003 are used in the estimation sample. Findings -Statistical selection is statistically significant so selection must be included in the models. Variables reflecting state-level characteristics such as farm debt servicing ratio, individual bank loan-to-asset ratio, bank size and the general guaranteed loan and interest assistance environment are significant in all three equations. Intensity of interest assistance use varies markedly across states. Originality/value -The interest assistance program has high subsidy costs and is an important source of support for financially marginal farmers. Scant prior research has investigated this program. The present study also shows that modeling interest assistance usage must be embedded in a larger model to give a complete specification.

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Explaining county‐level variability in farm service agency farm loan programs

Cited by 8 publications

References 6 publications

Bank size, lending paradigms, and usage of Farm Service Agency's guaranteed loan programs

Bank size, lending paradigms, and usage of Farm Service Agency's guaranteed loan programs

Modeling duration of FSA operating and farm ownership loan guarantees

A triple hurdle model of US commercial bank use of guaranteed operating loans and interest assistance

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