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The growth of lending from nontraditional lenders may pose challenges for official US Department of Agriculture (USDA) farm sector debt estimates, but it is difficult to find data to assess official estimates. The purpose of this study is to examine whether debt provided by nontraditional lenders is accurately accounted for in official estimates.

We compare traditional and nontraditional lending data from farm equipment lien collateral values and the USDA Agricultural Resource Management Survey (ARMS). After analyzing trends in equipment lending implied by farm equipment lien data and ARMS, we estimate whether changes in farm equipment lien values predict changes in equipment debt reported in ARMS and whether lender type influences that relationship.

We find that credit provided by nontraditional lenders is likely underreported in ARMS. Our econometric model shows that equipment debt volumes for nontraditional lenders are consistently lower than traditional loan volumes in ARMS across a variety of model specifications. We also find that an increase in lien values for nontraditional lenders is less likely to predict an increase in ARMS equipment debt volumes than an increase for traditional lenders.

Official farm sector debt estimates may not fully account for nontraditional lenders.

This study demonstrates how the growth of nontraditional lending poses challenges for estimating US farm sector debt. We evaluate farm sector debt estimates and advance knowledge of the role of nontraditional lenders in farm equipment credit provision. The farm equipment lien dataset provides a rich source of novel data for research on local and national equipment debt and investment.

Using a unique dataset of a commercial microfinance institution (MFI) in Madagascar, the purpose of this paper is to investigate how credit access probabilities and loan volume rationing magnitudes for farmers change if the MFI switches to offer flexible microfinance loans, which can account for agricultural production specifics.

The authors estimate probit models for the probability of receiving a loan and Heckman models to investigate the magnitude of volume rationing for all micro loan applications and disbursements of the MFI, differentiating between farmers with standard microfinance loans and farmers with flexible microfinance loans.

The results reveal that agricultural firms with flexible microfinance loans have significantly higher credit access probabilities than non‐agricultural firms and agricultural firms with standard microfinance loans. Furthermore, it was found that agricultural firms with flexible microfinance loans are stronger volume rationed than non‐agricultural firms and agricultural firms with standard microfinance loans.

Even if the authors can show that access to credit for agricultural firms in Madagascar can be enhanced by the provisioning of flexible microfinance loans, the investigated MFI only introduced flexible microfinance loans in 2011 and currently only offers them through five branch offices. Thus, the product is new to the MFI, and results might change with increasing outreach to other geographic regions in Madagascar. Furthermore, the conditions for agricultural production in Madagascar are unique, and the results might change in different country contexts.

The paper's findings suggest that flexible microfinance loans can contribute to the financial inclusion of farmers with seasonal production types. They also suggest that standard microfinance loans seem to be adequate for farmers with less seasonal production types, e.g. animal husbandry.

To the best of the authors' knowledge, this is the first paper to investigate the effects of flexible microfinance loan provision for credit access of small agricultural firms in developing countries in general, and in Madagascar in particular.

Using bank-level data over the 1994–2015 period, the authors aim to investigate the role of bank-specific factors on credit risk in Italy by considering two different groups of banks, namely, cooperative and non-cooperative (commercial and popular), in different local markets.

Relying on highly territorially disaggregated data at labour market areas’ level, the authors estimate the impact of the role of bank-specific factors on credit risk in Italy from the estimation of a fixed-effect estimator. Non-performing loans to total loans has been used as a proxy of credit risk; the bank-specific factors are as follows: growth of loans, reflecting credit policy; log of total assets, controlling for banks’ size; loans to total assets, reflecting the volume of credit market; equity to total assets, capturing the solvency of banks and reflecting their capital strength; return on assets, reflecting the profitability of banks; deposits to loans, reflecting the intermediation cost; cost of total assets, reflecting the banks’ efficiency or volume of intermediation cost.

The empirical findings suggest that regulatory credit policy, capitalisation, volume of credit and volume of intermediation costs are the main bank-specific factors affecting non-performing loans. Nevertheless, the present analysis suggests that the behaviour of cooperative banks’ behaviour seems to be in line with that of commercial rather than popular banks, casting doubts about the feasibility of their credit policies. It turns out that recent reforms involving popular and cooperative banks represent the first step toward the enhancement of the stability and efficiency of the Italian banking system. While the present study’s benchmark results are not particularly affected by the degree of competition in the banking sector and by banks’ size, it shows that both cooperative and non-cooperative banks have undertaken more prudent credit policies after the advent of the financial crisis and the introduction of the Basel regulation.

The relationship between bank-specific factors and credit risk has been analysed using a rich sample of cooperative, commercial and popular banks in Italy over the 1994–2015 period. The authors rely on labour market areas being sub-regional geographical areas where the bulk of the labour force lives and works. The contribution is motivated by the financial distress experienced after the 2008 financial crisis, which has significantly hit the Italian banking system and cooperative banks in particular.

In order to improve the assessment of current lending policies for a microfinance institution (MFI) in Azerbaijan, the purpose of this paper is to analyse how lending conditions are adjusted based on knowledge gains during the loan relationship, with particular attention to delays in previous loans. Moreover, the paper examines what a lender can pre-determine from its own collected repayment records of clients. In addition, the repayment performances and lending policies between agricultural and non-agricultural clients are differentiated.

The analyses are based on a rich data set of an Azerbaijani MFI. For determining the influence of previous delays on the volume rationing in the following loan, the authors apply a generalized linear model. Subsequently, the probability of recidivism is analysed by means of a logit model.

The results confirm a positive relationship between delays in previous loans and repayment problems in present loans, which is increased by the severity of the previous delay. With respect to consequences, it is shown that the borrower with previous delays faces an increase in loan volume rationing in the subsequent loan. Moreover, the authors find that the consequences of previous delays do not differ significantly between farmers and other clients.

Until now, the consequences of repayment delinquencies in microfinance lending relationships have hardly been investigated. This study enhances the understanding of lending policies in microfinance by focussing on relationship aspects and by simultaneously differentiating between farming and non-farming clients.

Following the recent global financial crisis, US regulatory agencies issued laws to implement the Basel III accords to ensure the resiliency of the US banking sector. Theories predict that enhanced regulations may alter credit issuance of the regulated banks due to increased capital requirements, but the direction of changes might not be straightforward especially with respect to the agricultural loans. A decrease in credit availability from banks might pose a serious problem for farmers who rely on bank credit especially during economic recessions. The paper aims to discuss these issues.

In this study, the impact of Basel III regulatory framework implementation on agricultural lending in the USA is examined. Using panel data of FDIC-insured banks from 2008 to 2017, the agricultural loan volume and growth rates are examined for agricultural banks and all US banks.

The results show that agricultural loan growth rates have slowed down, but the amount of agricultural loan volume issuance still remained positive. More detailed examination finds that regulated agricultural banks have decreased both the agricultural loan volume and their loan exposure to the agricultural sector, showing a possible sign of credit crunch.

This study examines whether the implementation of the Basel III regulation has resulted in changes in agricultural loan issuance by US banks as predicted by the lending channel theory.

This study examines agricultural lending by commercial banks and the competition they face from the Farm Credit System (FCS) and non-traditional lenders, including merchants, dealers and other input suppliers.

We construct a measure of commercial banks' perceived competition with FCS or non-traditional lenders using the individual responses to the Federal Reserve Bank of Chicago's Land Values and Credit Conditions Survey between 1999 and 2019. Through regression analysis of an unbalanced panel of survey responses, we present a number of stylized facts on the relationship between perceived competition and farm loan rate spreads, collateral requirements, loan delinquencies and expected lending volumes.

Our analysis shows that the two sources of competition have very different effects on commercial bank lending terms, loan portfolio riskiness and expected loan volumes. With these results in mind, we offer a number of suggestions for future research.

We leverage the unique characteristics of the Land Values and Credit Conditions Survey to examine the competition with non-traditional lenders that cannot be observed using administrative data.

Using a unique dataset of a commercial microfinance institution (MFI) in Tanzania, the purpose of this paper is to investigate first whether agricultural firms have a different probability to get a loan and whether their loans are differently volume rationed than loans to non‐agricultural firms. Second, the paper analyzes whether agricultural firms repay their loans with different delinquencies than non‐agricultural firms.

The authors estimate a Probit‐Model for the probability of receiving a loan, a Heckman‐Model to investigate the magnitude of volume rationing for all loan applications and an OLS‐Model to examine the loan delinquencies of all microloans disbursed by the MFI.

The results reveal that agricultural firms face higher obstacles to get credit but as soon as they have access to credit, their loans are not differently volume rationed than those of non‐agricultural firms. Furthermore, agricultural firms are less often delinquent when paying back their loans than non‐agricultural firms.

Even if the authors can show that access to credit and loan repayment is different for agricultural firms, the current regional focus of the MFI only allows for lending to agricultural firms in the greater Dar es Salaam area. Thus, these results might change in a rural setting. Besides general differences of the rural economic environment, the production type of agricultural firms might also differ in rural areas. Also, these results might change in different country contexts.

The findings suggest that a higher risk exposition typically attributed to agricultural production must not necessarily lead to higher credit risk. They also show that the investigated MFI overestimates the credit risk of agricultural clients and, hence, should reconsider its risk assessment practice to be able to increase lending to the agricultural sector. In addition, the results might indicate that farmers qualify less often for a loan as they do not fit into the standard microcredit product.

To the authors' knowledge, this is the first paper which simultaneously investigates access to credit and the repayment behavior of agricultural firms.

This paper uses novel data from a secondary market to assess how loans from nontraditional agricultural real estate lenders (NARELs) differ from traditional sources. Over $2 billion in loans from these entities were purchased by the secondary market between 2011 and 2020, but a lack of data has prevented a robust understanding of how these institutions operate.

The authors review loans from nontraditional lenders through their lifecycle in the secondary market from application to purchase and performance.

This paper finds no observable differences between nontraditional and traditional volumes with regards to borrower credit characteristics, loan approval rates, interest margins and loan performance. It finds significant differences between loan volumes and variable rate product use.

This is the first paper to use internal lender data to review nontraditional agricultural real estate loans and is the first analysis of nontraditional agricultural volumes in the secondary market.

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 number of US commercial banks has declined by about 50% over the last two decades. This change could lead to a potential decline in competition and a potential increase in market power in the agricultural banking market. The focus of this study is to examine whether the risk of failure and the performance of agricultural banks has been affected by bank consolidations.

The impact of bank competition on performance and financial stability of agricultural banks is studied using a Lerner index as a measure of market power. A Z-score is constructed to measure bank stability. Similarly, the return on assets (net income to total assets ratio), return on equity (net income to the total equity ratio), agricultural loan ratio and agricultural loan volume are used as performance measures for agricultural banks. Two-way fixed effect regression models are estimated to measure the impact of competition on financial stability and performance.

Results indicate that bank competition has a U-shaped effect on the probability of default and an inverted U-shaped effect on volume and proportion of agricultural lending. There also exists evidence of a positive but non-linear effect of bank market power on the profitability of agricultural banks.

There is limited literature on the impact of bank competition on financial stability and performance of US agricultural banks. Agricultural banks hold more than 40% of US farm debt. A decrease in the number of banks or the level of competition in agricultural banking may cause an adverse effect on relationship lending. The key findings imply that bank regulatory strategies should focus on enhancing (reducing) competition in more (less) concentrated banking markets to improve the financial health and performance of agricultural banks.