Explore the vast range of titles available.

Transitioning to sustainable agricultural systems is imperative to meet the global Sustainable Development Goals (SDGs). Achieving more sustainable agricultural production systems will require significant additional capital, however this cannot be covered by the current financial market setup, which dissociates public and private funders. Blended finance, where concessionary development-oriented funding is used to mobilize additional private capital, is essential. To ensure that the limited pool of concessionary funding is used efficiently and effectively, a shared understanding of the roles and limitations of public and private funders is necessary. In this paper, we describe the high-level funding gap for sustainable agriculture, the general landscape of agricultural finance, and the concept and potential roles of blended finance in this context. This paper introduces the conditions under which different financing mechanisms can contribute to addressing barriers related to sustainable agriculture investments. It highlights that multiple funding modalities must be utilized in order to achieve agricultural investment at a meaningful level and encourages greater exploration of the range of blended financing structures to increase SDG-related agriculture investments.

PurposeSeveral farm safety net strategies are available to farmers as a source of financial protection against losses due to price instability, government policies, weather fluctuations and global market changes. Producers can employ these strategies combining crop insurance policies with countercyclical policies for several crops and production areas; however, less is known about the efficiency of these strategies in enhancing profit and reducing its variability. In this study, we examine the efficiency of these strategies at minimizing inter crop year farm profit variability.Design/methodology/approachWe utilized relative mean of profit and coefficient of variation, to compare counterfactually calculated farm safety net strategies for a sample of 28,615 observations across 2,486 farms and four dryland crops (corn, soybean, sorghum and wheat) in Kansas spanning nine crop years (2014–2022). A no farm safety net strategy is used as the benchmark for every alternative strategy to ascertain whether a policy customization is statistically different from a no farm safety case.FindingsThe general pattern of the results suggests that program combination strategies that have a high-profit enhancement potential necessarily have low profit risk for dryland wheat and sorghum production. On the contrary, such a connection is absent for dryland corn and soybeans production. Low-cost farm safety net strategies that enhance corn and soybeans profits do not necessarily lower profit risks.Originality/valueThis paper is one of the first to use a large sample of actual farm-level observations to evaluate how combinations of safety net programs offered under the Title I (PLC, ARCCO and ARCIC) and XI (FCIP) of the U.S. Farm Bill rank in terms of profit level enhancement and profit risk reduction.

Purpose: Lack of access to credit is commonly held responsible for slow agricultural and rural development in low- and middle-income countries. This paper aims to investigate the contribution of demand- and supply-side factors, particularly the role of risk rationing, on credit application and uptake in the case example of Kyrgyzstan. Design/methodology/approach: Toward this aim, the study explores the determinants of credit behavior of 1,738 Kyrgyz sample farm households from 2013 to 2016 waves of the nationally representative “Life in Kyrgyzstan” (LIK) dataset along a hierarchical regression model, differentiating between factors influencing individual demand for credit and factors influencing supply for credit. Findings: The results of our analysis indicate the relative importance of demand-side factors for credit applications, reflecting farmers' perceived risk of credit default and loss of collateral. Meanwhile, supply-side factors, such as real credit constraints and collateral requests, have a stronger influence on credit uptake rates and overall loan sums. These findings highlight the role of risk rationing for agricultural investment, suggesting a stronger focus of development policy on improving risk-sharing mechanisms for farmers, e.g. by developing the agricultural insurance sector. Originality/value: The paper contributes novel evidence on the role of risk rationing in shaping the demand for formal credits for increasing agricultural and rural investment in low-income transition economies. Previous research has mostly focused on the role of credit supply, thus underrating the potential contribution of individual risk attitude, risk experience and risk sharing.

Propensity score matching is used to estimate how direct-to-consumer (DTC) marketing influences farm survival and growth over 5-year periods. Results show that beginning farms with DTC sales grow more slowly but are more likely to survive in business compared to similar farms without DTC sales. The study finds that DTC marketing is associated with lower financial performance and a greater likelihood of facing borrowing constraints, which might help explain the slower farm growth. DTC marketing is also associated with lower farm income volatility, which might help explain the higher survival rate.

PurposeThe agricultural sector remains the backbone of several emerging economies, including Kenya, where it contributes 34% to its gross domestic product (GDP). However, access to financing for agricultural activities appears to be very low compared to developed economies. Following this, governments in a number of countries have sought to introduce banking sector regulations to facilitate increased funding to the agricultural sector. Taking motivation of the interest rate capping regulations by the Central Bank of Kenya (CBK) in 2016, this paper examined the effect of these interest rate ceiling regulations on agri-lending in Kenya.Design/methodology/approachThe paper employs random effects technique to estimate a panel data of 26 commercial banks in Kenya from 2014 to 2018 using the ratio of loans to agricultural sector to gross loans and the natural logarithm of loans to agricultural sector as proxies for agri-lending. Bank size, equity, asset quality, liquidity, revenue concentration and bank concentration are employed as control variables.FindingsThe results of the panel regression estimations show that the introduction of the interest cap resulted in increases in the proportion and growth in agri-lending compared with the pre-interest cap period. In addition, large banks and highly capitalised banks were found to be associated with lower agri-lending, with differences in the effects across pre-cap and post-cap periods.Practical implicationsFrom a policy perspective, the findings highlight the effectiveness of interest rate capping in meeting this objective and supports the calls for strengthening cooperation between the government and key stakeholders in the financial sector. This will allow for the effective enforcement of policies by the regulatory powers in a manner that guarantees sound and dynamic financial systems, particularly within the agricultural sector.Originality/valueAs far as the authors are aware, this the first paper to examine the effect of the interest rate cap regulation on agri-lending in Kenya.

This study explores how participation in direct and intermediated marketing channels and key operational factors influence agricultural producers’ financial performance. Accordingly, we divide the sample of local and regional food marketers into quartiles segmented by profitability performance as an initial exploration of how strong and weak performance may vary across scale, location, and choice of direct and intermediated channels. Moreover, other financial metrics that vary across types of producers and performance-based quartiles are analyzed. This paper provides initial evidence that participation in direct and intermediated markets may allow farms of any scale of sales volume to be financially viable.

PurposeThe design of effective policies that increase access to agricultural credit should consider understanding credit constraint farmers’ groups and their response to changes in the credit conditions. To contribute to this understanding, this study surveyed farmers from Chile and classified them into five credit constraint categories discussed in credit literature. In addition, these farmers indicated how they would react to a series of hypothetical conditions related to changing interest rates, loan maturity and grace periods. Their responses were employed to measure credit demand scores (i.e. relative elasticities). Regression tests evaluated how different types of farmers reacted to changing credit conditions.Design/methodology/approachFarmers from Chile were surveyed using a mix of random and convenience sampling. Surveyed farmers were classified into five credit constraint categories proposed by previous research. Farmers rated their demand for credit on a five-point Likert-type scale for hypothetical changes in interest rates, loan maturities and grace periods. Their responses were employed to measure credit demand scores or relative credit elasticities. The study evaluated credit elasticity as a function of farmers’ credit constraint and some control variables using several regressions, including OLS, ordered probit and hierarchical regression.FindingsThe study identified 44% unconstrained nonborrowing farmers, 23% unconstrained borrowers, 14% quantity-constrained, 16% risk-constrained and 3% transaction cost-constrained farmers. Unconstrained borrowers and quantity-constrained farmers responded most to changing interest rates and loan maturity conditions. In addition, unconstrained nonborrowers and risk-constrained farmers were statistically less sensitive to changes in credit conditions than unconstrained borrowers. This finding is significant because, as discussed, unconstrained nonborrowers represent 44% of our sample. Furthermore, risk-constrained farmers were the least sensitive to changes in interest rates and loan maturity across all other credit categories.Practical implicationsThis study gives insights that can guide agribusiness policies to enhance access to credit in developing countries such as Chile. Agricultural credit capital institutions can better target their clientele by identifying farmers’ possible reactions before implementing policy changes to increase access to credit. This study’s credit constraint categorization and the results discussed can guide that identification. For instance, policies directed toward unconstrained borrowing farmers may find positive responses. However, implementing policies targeting the other three groups (unconstrained nonborrowing, risk-constrained and transaction cost-constrained farmers) is more challenging because these farmers are less responsive to changing credit conditions.Originality/valueThis article correlates farmers’ propensity to borrow and credit constraints across five categories of farmers. Prior research using this categorization framework has not identified farmers into the five groups. Furthermore, in addition to interest rate and loan maturity credit demand relative elasticity, this study adds the grace period elasticity, which has not been included in previous studies on agricultural credit.

PurposeThis study examines the heterogeneous relationship between ad-hoc support policies, high government payments, low interest rates and farm debt use across farms of different sizes and across farm operators of different races, genders and experiences to inform the 2024 Farm Bill discussions.Design/methodology/approachUtilizing USDA’s Agricultural Resource Management Survey data for 2020 and 2021, this study characterizes the differences in short-term farm debt use and the amount of short-term debt during the COVID-19 pandemic period across several farm and farmer types using double selection LASSO and regression analysis.FindingsResults show positive associations between government payments and debt use for all farm types and farmer demographics except for residence farms and non-white farmers, which may be due to their limited access to credit. Findings also indicate that farms that could already access credit, like commercial farms, increased their short-term debt during the pandemic per the decrease in interest rates. Moreover, the 2018 Farm Bill extended certain commodity support and direct and guaranteed loan program participation provisions that were previously more closely restricted. Beginning farmers seemed more likely to use short-term debt in response to higher pandemic government payments than their more experienced counterparts.Practical implicationsThe insights from this study are timely and useful for policymakers for designing and implementing programs related to the new 2024 Farm Bill.Originality/valueOne of the explanations for the results is that beginning farmers have been more likely to use debt than most other groups of operators, signaling the success of special credit provisions. Our results are relevant to making upcoming policies related to female and nonwhite farm and ranch operators.

PurposeThis study aims to determine the nexus between agricultural production and agricultural loans for the period Q1 2003–Q4 2018 in Turkey.Design/methodology/approachThe authors employ the time-series analyses within the scope of the study. Firstly, they run the Engle–Granger two-step cointegration test and the Toda–Yamamoto causality analysis. They also use the dynamic ordinary least squares (DOLS) model estimator and estimate the vector autoregression model for predicting the dynamic structure of time series.FindingsThe results of time series analyses reveal that the variables are cointegrated and there are causal relationships between agricultural loans and agricultural production. Also, the variance decomposition findings indicate that the effect of agricultural loans provided by development-investment banks and participation banks on agricultural production has increased over the years, and the deposit banks have a high impact on agricultural production. The results of the DOLS model indicate that agricultural loans have a positive effect on agricultural production.Originality/valueThis research is one of the few studies that comprehensively determines the direction of nexus between agricultural production and agricultural loans in Turkey economy. This is the first contribution of the study in the literature. Another contribution of this study is to investigate the nexus between agricultural production and agricultural loans for banking sector groups. Unlike other studies in the literature, this study calculates the variance decomposition by going beyond unit root and cointegration tests. Thus, this study has deep findings.