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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.

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 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.

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 focus on public guarantees granted to micro-, small- and medium-sized enterprises (SMEs) by the Italian national credit guarantee programme (Fondo Centrale di Garanzia – Central Guarantee Fund – (CGF)). The CGF provides a direct guarantee to banks granting loans or a counter-guarantee to mutual guarantee institutions (MGIs) acting as first-level guarantors. Because the behaviour of MGIs could affect the default risk of counter-guaranteed loans, it is vital to investigate their operating and structural characteristics in order to identify an optimal design for public credit guarantee schemes (PCGSs).

Using regression models, the paper analyses the determinants of default for 33,229 SME loans guaranteed by an MGI and counter-guaranteed by the Italian CGF. The dependent variable is the ex-post default risk of SMEs’ counter-guaranteed loans in the 2010-2011 period. The explanatory variables are certain characteristics of the MGI.

The authors demonstrate that increases in an MGI’s leverage and the size of the counter-guaranteed portfolios increase the default risk. When the counter-guaranteed portfolio increases, MGIs are more risk taking but take less risk than when local and specialized MGIs are at play. Finally, direct public aid is relevant.

An appropriate design of the PCGS becomes crucial to controlling moral hazard in financial institutions and ensuring the financial sustainability of public intervention in favour of SMEs.

The paper evaluates an original and confidential firm-level data set that is not available in public documents or supervisory board statistics but is collected directly from the MGIs that participated in this study.

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 investigate the drivers influencing the risk of default on mutual guaranteed loans. The authors aim to verify whether default is influenced by the specific business policies of mutual guarantee institutions (MGIs) and to recommend guidelines for directing their operating management.

The authors analyse the guaranteed portfolios of 19 Italian MGIs and investigate the determinants of the defaulted positions at the end of June 2011. The sample consists of 167,777 guaranteed loans, of which 11,349 are in default. Using regression models, we identify the variables related to the business model of MGIs that are significantly associated with default on their positions.

The defaulted positions of MGIs are significantly correlated with the type of issued guarantees. This condition should be considered in defining product and price policies.

The authors identify some critical issues in the risk-taking processes of MGIs. The tested hypothesis highlights the opportunities for the optimisation of guaranteed loan portfolios, which is necessary for reducing the profitability/liquidity pressures of these financial institutions and enhancing their efficiency as instruments for mitigating the effects of credit rationing and promoting the revitalisation of small-and medium-sized enterprises.

The results are based on an original and reserved dataset, which is not available in public financial statements or public statistics, but is collected directly from the MGIs that are part of the study.

Presents a case study of a financial services company socializing in student loans. Positions the study in terms of ′sustainable competitive advantage′, ′strategic necessity′ and ′edge toward the market′ hypotheses. Concludes that information systems played ′an essential but essentially derivative role′ in the success of the enterprise.

Studies of Depression-era financial remediation have generally focused on federal deposit insurance and the provision of equity to banks by the Reconstruction Finance Corporation (RFC). This paper broadens the concept of financial remediation to include other programs – RFC lending, federal guarantees of farm and home mortgages, and the elimination of interest on demand deposits – and other intermediaries – savings and loans, mutual savings banks, and life insurance companies. The benefits of remediation or the amounts potentially at risk to the government in these programs are calculated annually and allocated to the various intermediaries. The slow remediation of real estate loans (two-thirds of these intermediaries' loans) needs further study with respect to the slow economic recovery. The paper compares Depression-era remediation with efforts during the 2008–2009 crisis. Today's remediation contrasts with the 1930s in its speed, magnitude relative to GDP or private sector nonfinancial debt, the share of remediation going to nonbanks, and emphasis on securities markets.

The United States has been at the forefront of a global shift away from direct state funding of higher education and toward student loans, and student debt has become an issue of growing social concern. Why did student loans expand so much in the United States in the 1990s and 2000s? And how does organization theory suggest their expansion, and the growth of federal student aid more generally, might affect higher education as a field? In the 1960s and 1970s, policy actors worked to solve what was then a central problem around student loans: banks’ disinterest in lending to students. They did this so well that by 1990, a new field of financial aid policy emerged, in which all major actors had an interest in expanding loans. This, along with a favorable environment outside the field, set the stage for two decades of rapid growth. Organization theory suggests two likely consequences of this expansion of federal student loans and financial aid more generally. First, while (public) colleges have become less dependent on state governments and more dependent on tuition, the expansion of aid means colleges are simultaneously becoming more dependent on the federal government, which should make them more susceptible to federal demands for accountability. Second, the expansion of federal student aid should encourage the spread of forms and practices grounded in a logic focused on students’ financial value to the organization, such as publicly traded for-profit colleges and enrollment management practices.