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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.

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.

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.

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.

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.

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.

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.

USDA direct and guaranteed farm loan programs exhibit significant geographical variation in lending activity. County‐level estimations made using Tobit procedures indicate that use of Farm Service Agency (FSA) farm loan programs is greater in counties with lower per capita income and regions experiencing greater farm financial stress. Use of direct FSA loan programs was lower in counties with fewer private‐sector lenders. Guarantee loan program usage was found to decline when commercial agricultural lenders are absent from the county. FSA loan programs were more highly utilized in counties with an FSA loan service center and in states receiving greater FSA farm loan funding in past years.

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.

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.

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.

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.

Different loan characteristics and macroeconomic conditions significantly influence the occurrence of possible guarantee outcomes and time to the outcomes.

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.

The purpose of this paper is to examine changes in the structures of US farms and lenders and identify prospective implications for federal credit.

Data from US farm operations for 1996-2014 were adjusted to 2014 values using commodity price indices. Farm size groups were constructed by value of farm production to analyze changes in farm numbers, production, assets, debt, leverage, liquidity, profitability, land tenure, commodity type, contract production, organization type, and use of Farm Service Agency (FSA) direct and guaranteed loans by farm size. Bank, Farm Credit System (FCS), and FSA data from 1996 to 2015 were adjusted to 2014 values. Lender size groups were constructed to analyze changes in bank and association numbers, farm loans, and use of FSA guaranteed loans by lender size.

The greatest consolidation has been by farms with over $2 million in production. More farm debt is held by large, complex organizations, frequently with multiple operators, more variable income, and greater reliance on production contracts and operating and nonreal estate credit. Large farms have greater leverage, are more profitable, and have a larger share of household income from the farm. Banks and FCS institutions are fewer and larger, yet smaller institutions use FSA guarantees to a greater extent. Larger farms tend to be more reliant on both direct and guaranteed FSA loans and are likely to become more dependent on FSA credit.

Changing farm and lender structure together with softening farm income may require FSA farm loan program changes to meet any increase in loan demand. Policy alternatives are provided to meet changing demand for farm credit.

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.

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.

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.

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.

The purpose of this paper is to analyze the repayment records of Farm Service Agency (FSA) borrowers in two distinct US farming regions that have been experienced serious drought conditions even as the US economy was going through a recession. The analysis will identify factors that significantly influence both the probability of FSA borrowers’ survival (capability to remain in good credit standing) and temporal endurance (or length of period of good standing with creditor).

This analysis utilizes a data set of farm borrowers of the Farm Service Agency that regular farm lenders have classified as “marginal” relative to other borrowers. The research goal is addressed by confining this study’s regional focus to the Southeast and Midwest that have both dealt with financial stress arising from abnormal natural and economic conditions prevailing during the same time period. A split population duration model is employed to separately identify determinants of the probability and duration of survival (condition of good credit standing).

This study’s results indicate that larger loan balances, declining commodity prices, and the severity of drought conditions have adversely affected both the borrowing farms’ probability of survival and temporal endurance in terms of maintaining non-delinquent borrower standing. Notably, Midwestern farms have been relatively less affected by drought conditions compared to Southeastern farms. This study’s results validate the contention that the farms’ capability to survive and the duration of their survival can be attributed to differences in regional resource endowments, farming activities, and business structures.

This study’s analytical framework departs from the basic duration model approach by considering temporal endurance, in addition to survival probability analysis. This study’s original contributions are enhanced by its specific focus on the contrasting farm business structures and operating environments in the Midwest and Southeast regions.

The purpose of this paper is to evaluate the determinants of supply chain relationships, the provision of supplier support measures and the role that support measures play in stimulating investment by suppliers in emerging economies.

The paper draws on survey evidence for 300 commercial dairy farms in Armenia. The identification of potential determinants of supply chain relationships and support programmes is based on literature on supply chain management and transaction cost economics.

Positive determinants of supplier support programmes are the degree of exclusivity of the buyer-supplier relationship, initial capital of the supplier, co-operation between suppliers, and foreign ownership of the buyer. Support programmes are less likely to be offered in very competitive environments. Support measures such as loans, physical inputs and guaranteed prices facilitate supplier investments.

Research is limited to cross-sectional data for a single country and further testing would help assess the generalizability of the findings.

The findings highlight the gains that can be made from openness to international firms. The negative competition effect suggests that buyers are constrained in their ability to monitor use of the provided services in an environment where a lot of buyers are competing for the same supply. Improving the enforcement capability of companies under these circumstances is an important challenge for the industry and policy makers.

The novelty of the study lies in the investigation of the relationships between the nature of supply chain linkages and suppliers' investments.

A potential farm policy concern is that if nontraditional (vendor/point-of-sale) financing represents increased risk, it may have an aggregate effect on sector-wide farm financial risk. This analysis examines the use of nontraditional lender credit among borrowers in the US Department of Agriculture (USDA)'s Farm Service Agency (FSA)'s direct farm loan programs.

Data source included the USDA FSA direct operating loan program for 2011–2020. A Cox proportional hazards model was used to estimate the occurrence of default over seven-year term direct operating loans.

Results indicated that point-of-sale financing has a significant and positive relationship with risk for FSA direct operating loan borrowers. The presence of intermediate point-of-sale financing (mostly from machinery and equipment vendors) is associated with an increased probability of default of 9%, and the presence of such loan balances in the amount of $50,000 or more had a higher probability of default of 21%. Short-term nontraditional financing (for example from fertilizer vendors) was found to be positively related to borrower risk of default as indicated by a 22–25% increase in the likelihood of loan default.

Through FSA Farm Business Plan data, the authors were able to distinguish specific vendors and their loan purpose, which advances the knowledge beyond what is currently available through survey data. Findings indicate a minor increase in borrower risk for those with intermediate-term nontraditional financing. However, borrowers with short-term nontraditional financing and having large balances or greater number of nontraditional loans had increases in risk of default by substantive amounts.

Federal farm credit programs currently administered by the USDA were initiated in the early 1900s to help the farm sector cope with natural disasters, and these programs have continued to evolve. There has been a rich history of research analyzing USDA farm credit programs and the effects they have had on farmers, ranchers, and credit markets. This paper highlights past research and offers a view of the future direction of research on federal farm credit programs.

The determinants of income of rural and urban farm households, with emphasis on the role of off-farm employment by farm household members and of farm size, are examined using data from the 2016 Agricultural Resource Management Survey (ARMS) and quantile regression procedure. The implemented quantile regression technique is extended to allow for the decomposition of the income gap between the two groups of farm households. Findings indicate, regardless of the location of the farm, a positive and significant impact of a previous year's participation in off-farm work by household members on the distribution of current household income. Having operated a larger-sized farm in the previous year is shown with a similar effect in the upper range of the income distribution for urban households and with a comparable impact but across the whole income distribution for rural farm households.

Data from the 2016 ARMS are used in conjunction with quantile regression in order for decomposition of the income gap between the two groups of farm households.

Findings show that urban farm households who in a previous year have participated in off-farm work and operated larger-sized farms tend to earn higher incomes. Results further indicate higher rates of return to education for “urban” farm households in comparison to “rural” farm households, particularly for those with a college education and beyond who are at the lower portion of the income distribution.

To the extent that the ARMS is an annual cross-sectional data, the temporal impacts of factors that potentially may influence the incomes of farm households in urban and rural areas cannot be measured.

Findings from this research indirectly support previous published research where higher earnings by urban US population were documented in comparison to rural population and where earnings tend to rise as a result of participation in off-farm work and in expanding the size of the farming operation; this is in addition to the procurement of higher education.

The results of a higher rate of return to education for “urban” farm households in comparison to “rural” farm households have important policy implications for policymakers.

This is the first paper in the agricultural economic literature that implements a method of assessing the rural–urban divide across all of the quantiles of income distribution.