Purpose Farmers in India continue to be deprived of adequate and timely institutional credit. The Kisan Credit Card (KCC) scheme, introduced in 1998, sought to address this issue by providing credit support under a single window with simplified procedure. The study aims to analyze the factors affecting the adoption of KCC and its impact on farmers' economic welfare in Eastern India. Design/methodology/approach We utilize a panel data of 2,537 farming households from five states in Eastern India, namely, Bihar, Uttar Pradesh, Jharkhand, Odisha and West Bengal for the years 2018 and 2023. We deploy panel probit model and random effects model to examine the determinants of access to KCC and its credit limit, respectively. We also analyze the impact of KCC on farmers' input usage, dependence on moneylenders and farm income using propensity score weighted fixed effects model. Findings We find that farmers' participation in agricultural training, demonstrations and development programs encourage farmers to adopt KCC. Furthermore, KCC access increases farmers' input usage and reduces their dependence on money lenders. Research limitations/implications The findings of the study raise concerns over the limited penetration of the scheme among smaller-scale farmers and provide key insights into the underlying issues hindering the efficacious functioning of the scheme. Originality/value This study provides novel panel-data-based empirical evidence from an economically challenged region in India, whose economy significantly depends on agriculture.
Purpose Financial literacy refers to the awareness, knowledge, skills, attitude, and behaviour necessary to make sound financial decisions. This study aims to investigate the links between digital finance literacy and rural households' digital exclusion, particularly in the Indian context. Design/methodology/approach Using a structured questionnaire, a conceptual model is developed and empirically tested after data collection from 660 rural households in Tamil Nadu, India. Using hierarchical regression, the study finds that rural households' digital finance literacy is significantly associated with their digital exclusion. Specifically, higher levels of digital finance literacy correspond to lower levels of digital exclusion across social, economic, technological, service, and behavioural dimensions. Findings Findings indicate that digital finance infrastructure mediates the relationship between rural households' digital finance literacy and various digital exclusion factors (social, economic, technological, service, and behavioural). Finally, the findings of the mediation analysis suggest a partial mediation of rural households’ digital finance literacy with social, economic, and behavioural exclusions, and full mediation exists with technological and service exclusions. Originality/value Studies on digital financial literacy in disadvantaged groups are scarce; this study demonstrates that enhancing digital infrastructure can mitigate technology and service exclusions. The findings of this study will be helpful to the government, financial institutions, banks, and other non-banking institutions in improving infrastructure platforms, developing niche products, and providing the best services to meet end users' needs.
Purpose The purpose of this study is to evaluate how global agricultural stock markets reacted to African Swine Fever (ASF) outbreaks in China and Germany in 2020, and to identify which agricultural sub-industries were most affected. The study also aims to provide insights into how market responses differ between major importing (China) and exporting (Germany) countries and is hence a comparative case analysis of these two specific ASF outbreaks. Design/methodology/approach An event study methodology is applied using daily data from a global agricultural MSCI Index. Cumulative abnormal returns (CAR) following these two ASF outbreak announcements are estimated for the full global agricultural MSCI Index and for four agricultural sub-industries and compared. Multiple model specifications and placebo events are used to test the robustness of these results. Findings The results show statistically significant negative CAR for the MSCI agricultural index following ASF outbreak announcements in both China and Germany, with stronger effects observed for the Chinese outbreak. The sub-industries “agricultural products and services” and “packaged foods and meats” primarily drive the negative market reactions in response to both outbreaks. These findings remain robust across alternative specifications. Practical implications The study highlights the vulnerability of global agricultural markets to animal disease outbreaks and underscores the need for investors, policymakers and firms to account for sector-specific and country-specific risk exposures. Understanding which sub-industries are most affected can support the development of targeted risk-mitigation and crisis-response strategies. Originality/value This study provides the first comprehensive assessment of ASF’s impact on the global agricultural sector using a broad-based agricultural MSCI Index. By comparing market reactions between a major importer (China) and a major exporter (Germany) and examining heterogeneous effects across sub-industries, it offers novel insights into investor behavior and the economic consequences of animal disease outbreaks.
Purpose This study examines the impact of credit on agricultural growth in Vietnam from 1996 to 2023, focusing on how credit effectiveness differs across prosperity and crop-loss regimes and under varying macroeconomic conditions, particularly business cycles and inflation. Design/methodology/approach A Markov Regime Switching model is employed to capture nonlinear and regime-dependent effects. Annual data from the World Bank and the Food and Agriculture Organization are used to analyze how credit operates under different agricultural and macroeconomic states. Findings Credit significantly supports agricultural growth during crop-loss periods by acting as a financial buffer. However, during prosperity phases, its effect weakens and may even become negative under high inflation, increasing financial risk. These results highlight the importance of macroeconomic stability and cyclical conditions in determining credit effectiveness. Originality/value The study contributes by incorporating business cycles and inflation into the analysis of agricultural credit, applying a nonlinear regime framework, and providing evidence from Vietnam, an emerging economy where agriculture remains crucial for food security and development.
PurposeThis study examines how commodity prices mediate the relationship between soil productivity and farmland values to better understand the dynamic economic value of soil quality.Design/methodology/approachThe authors use a hedonic pricing model to analyze land values derived from about 88,000 Illinois farmland sales transactions from 2000 to 2022, interacting soil productivity measures with spatially-interpolated commodity prices to separate the effects of market conditions from the marginal productivity of soil.FindingsPremiums for farmland with high soil productivity ratings vary significantly with commodity prices. The marginal product of increased soil productivity was twice as large from 2018 to 2022 as in the 2000-2005 base period.Originality/valueThis research introduces a novel approach to assess soil quality premiums by interacting soil quality measures with expected output prices, allowing the data to reveal distinct technology-driven changes in soil value capitalization.
PurposeThis study investigates the impact of ad hoc government payments-specifically the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP)-and Farm Bill safety net payments-Agricultural Risk Coverage (ARC) and Price Loss Coverage (PLC)-on non-real estate agricultural loan delinquencies in the United States. The goal is to evaluate the relative effectiveness of these payments in alleviating financial stress in the agricultural sector.Design/methodology/approachWe use a state-level panel dataset covering the years 2015-2022 and apply linear fixed effects models to estimate the marginal effect of each payment type on total non-real estate farm debt and delinquency rates. Robustness is assessed using dynamic panel models and Lewbel's IV estimator to address potential endogeneity.FindingsARC and CFAP payments are significantly associated with reductions in short-term loan delinquencies (30-89 days past due). ARC payments also increase total operating debt, suggesting improved liquidity. PLC payments reduce longer-term delinquencies (90+ days past due), while MFP payments increase total debt but do not reduce delinquencies, indicating weaker effectiveness.Originality/valueThis is the first study to jointly evaluate the effects of ARC, PLC, MFP, and CFAP payments on non-real estate farm debt outcomes using actual payment timing and amounts. It offers novel empirical insights into the financial efficacy of government support programs in agriculture.
PurposeThis study examines the nexus between green-oriented Islamic agricultural financing and national food security in Indonesia, using agricultural financing provided by Islamic banks as a proxy for Islamic green financing. Design/methodology/approachThis study uses provincial panel data from 34 Indonesian provinces over 2019–2023. Fixed-effects estimation is employed to control for unobserved heterogeneity, while robust least squares are applied to address outliers and violations of classical assumptions. FindingsThe results show that green-oriented Islamic agricultural financing is positively and statistically associated with national food security, without implying causal effects. The fixed-effects estimates indicate stronger associations with food affordability and food utilization, while no significant relationship is found with food availability. Robustness checks confirm that the positive association remains significant for national food security and food availability after controlling for outliers and influential observations. Further, regional analysis reveals marked heterogeneity, with the strongest and most consistent effects observed in Java–Kalimantan, followed by Eastern Indonesia, while the relationship is weaker and only marginally significant in the Sumatra region. Research limitations/implicationsThis study employs Islamic agricultural financing as a proxy for green-oriented Islamic financing, which captures its potential contribution rather than fully reflecting Sharia-compliant green financing activities. Future research should develop more precise indicators incorporating environmental performance, climate resilience, governance quality, and Islamic sustainability principles. Practical implicationsThe findings support the integration of green-oriented Islamic finance into regionally differentiated food security and sustainable agriculture policies. Originality/valueThis study provides recent subnational evidence on the potential contribution of green-oriented Islamic agricultural financing to food security in Indonesia using official indicators from the National Food Agency.
PurposeThis study examines the relationship between mergers and acquisitions (M&As) among U.S. commercial banks and county-level agricultural lending.Design/methodology/approachWe aggregate bank-level information sourced from the Federal Deposit Insurance Corporation (FDIC) to county-level data and employ the Callaway and Sant'Anna (2021) estimator to explore how bank M&As are related to changes in commercial banks' agricultural loan volume.FindingsThe estimates show that counties experiencing a commercial bank M&A subsequently exhibit statistically and economically significant declines in agricultural loan volumes held by commercial banks, with no evidence of differential pre-trends. These patterns are robust in subsamples focusing on rural counties and on community banks.Originality/valueResearch examining the localized effect of bank M&A activities remains limited. Our study bridges this research gap by incorporating the latest available data to conduct a detailed analysis at the local level.
PurposeThis study explores the innovative bundling of crop insurance and credit and its impacts on economic outcomes. This article first presents a theoretical model for “bundlization” of credit and crop insurance. Propositions of such a model are tested in the light of evidence from a nationally representative survey in India. Specifically, this study identifies the correlates of crop insurance access (or bundling of crop insurance and credit) and its impacts on farm income and outstanding debt. Design/methodology/approachA unit-level dataset of 34,946 observations related to 31,784 cereal-producing households is compiled from the Situation Assessment Survey of Agricultural Households in Rural India (2019). Econometric methods (Logistic regression, Multinomial logit model, Propensity score matching and Sensitivity analysis) are used in this study. FindingsThe survey reveals that only 8% of farmers have access to insurance. Credit-linked insurance has a higher uptake than voluntary insurance. Out of 92% of uninsured farmers, nearly 43% are unaware of the existence of a crop insurance scheme. Most insured farmers who experience crop failure are denied claims without explanation. Logistic regression suggests that higher age, higher yield, greater landholding, formal training, working in an employment guarantee scheme, possession of a Kisan Credit Card and experience of loss increase crop insurance access. Multinomial logit regression findings suggest the positive relationship between yield and crop insurance access is limited to loanee farmers. Finally, propensity score matching results suggest that crop insurance significantly improves farm income and mitigates downward risk during crop failure. Bundling crop insurance and credit provides no additional benefits. Practical implicationsThe results of this study find no economic rationale for bundling crop insurance and credit; therefore, policymakers can delink the compulsory provision of crop insurance in credit contracts. However, considering the positive impact of crop insurance in increasing farm income and safeguarding against crop failure, policymakers should consider strategies to increase crop insurance access by making farmers aware of the crop insurance scheme. Originality/valueThis article made a novel contribution in the extant literature on two counts. First, this study develops atheoretical framework to compare payoffs of different categories of farmers, i.e. insured vis-à-vis noninsured farmers, and loanee vis-à-vis nonloanee farmers. Secondly, following the framework's propositions, the determinants of crop insurance access are identified by considering these categories of farmers. Additionally, this study estimates the impact of crop insurance in the event of crop success and crop failure.
Purpose Traditional crop insurance has low adoption in developing countries due to operational inefficiencies and poor systemic risk information, limiting insurers' diversification and farmer utility. In Brazil, less than 15% of cropland is insured. This study investigates whether integrating actuarial modeling with remote sensing can support an alternative area-yield insurance framework that improves risk management, farmer value, and scalability in data-scarce agricultural systems. Design/methodology/approach Remote sensing, yield modeling, and actuarial simulation were integrated to compare spatial aggregation strategies for area-yield insurance. A 10-year soybean yield time series was reconstructed for one million hectares using satellite vegetation indices and an empirical model. Farms were grouped through spatiotemporal clustering and compared with county aggregation. Insurance contracts were optimized using a constant relative risk aversion framework, simulating willingness to pay, premiums, indemnities, and income outcomes. Findings Clustering farms based on spatiotemporal yield patterns reduced systemic risk and outperformed county aggregation. Utility-based simulations showed cluster-structured insurance increased producer utility by 39% relative to administrative boundaries and substantially improved outcomes compared to no insurance. Clustering also enhanced indemnity distribution and risk correlation while maintaining similar premium loads, demonstrating a viable pathway to expand agricultural insurance adoption in developing countries such as Brazil. Originality/value This study introduces a data-driven spatial aggregation approach replacing administrative units with clusters derived from remote sensing yield correlations. By reconstructing long-term field-scale productivity in a data-scarce environment, it demonstrates how Earth observation can operationalize actuarial insurance design. Integrating spatiotemporal clustering with expected utility optimization provides new evidence on aggregation effects on basis risk, indemnities, and insurer margins, informing scalable insurance solutions.
PurposeUnited States (US) cattle producers have tools to manage price risk, such as options contracts, futures contracts and livestock risk protection (LRP) insurance. However, there has been limited use of price risk management tools among beef cattle producers. The purpose of this research is to determine factors associated with the use of options contracts, futures contracts and LRP insurance.Design/methodology/approachWe conducted a survey of US cattle producers about their use of LRP insurance, futures contracts and options to manage price risk. A multivariate probit model was estimated to understand what drives the likelihood of these price risk management tools.FindingsWe find most producers have never used any price risk management tools, but LRP was the most used (12.5%), followed by futures contracts (6%) and option contracts (5.5%). Producer age, herd size, risk preferences, perceived effectiveness at managing price risk and other factors affected the use of these tools. Interestingly, high risk tolerance results in an increased likelihood of using futures contracts, which is opposite to what was anticipated.Originality/valueFindings inform industry stakeholders, educators and policymakers in developing effective educational programs for producers regarding price risk management. This article also broadens the body of knowledge on the acceptance of various price risk management among cattle producers.
PurposeThis paper assessed the impact of access to credit and associated productivity variations on rice farmers' welfare in Ghana.Design/methodology/approachThe authors employed a quasi-experimental research design and the conditional mixed process (CMP) approach with micro-level secondary data from the Ghana Statistical Service (GSS) to jointly estimate the determinants of rice farmers' access to credit, the impact of access to credit on rice productivity and the welfare effect of rice productivity. The joint estimation of these equations and the use of a recursive CMP approach rule out simultaneous feedback within the production cycle and correct for endogeneity while accounting for the mixed (binary and continuous) nature of the dependent variables.FindingsThe model estimates show that access to credit increases rice productivity, which in turn improves rice farmers' welfare. Specifically, access to credit positively impacted rice productivity, with an extra 958.270 kg/ha for credit users. In turn, a unit increase in productivity increased rice producers' welfare by GHC 2.98. Factors influencing access to credit include age, education, marital status, rice output and ownership of mobile phones and bank accounts. While male farmers demonstrated higher productivity, female farmers were associated with superior welfare impacts.Research limitations/implicationsA study is required to understand how changes in productivity arising from access to credit influence farmers' assets and wealth.Practical implicationsPursuit of policies for improving farmers' access to agricultural credit can improve farm productivity and rice farmers' welfare.Originality/valueThis study incorporates farmer welfare as a function of productivity in the access to credit-productivity model, creating a tri-variate model to understand the farmer welfare effect of rice productivity dynamics in Ghana.
PurposeThis study investigates how agribusinesses' investment rates in physical and intangible capital respond to changes in investment opportunities and examines how their financial health affects these investment decisions. Despite the growing importance of intangible assets in agriculture, research on agribusinesses' investment behavior in these assets remains limited.Design/methodology/approachUsing financial data from U.S. publicly listed agribusinesses from 1975-2024, we employ higher-order cumulant estimators to address measurement error problems in proxies for investment opportunities, such as Tobin's q and Total q. We conduct regression analyses to evaluate investment rate sensitivities across physical and intangible capital along with financial condition, using the Altman Z-score to classify firms as financially distressed or healthy.FindingsInvestment rates in intangible capital are less responsive to changes in investment opportunities than those for physical capital. Second, when financial condition is considered, financially distressed firms' investment rates in physical capital exhibit lesser sensitivity to changes in investment opportunities compared to investments in intangible capital. We also find that financially healthy firms' investment rates in physical capital show greater sensitivity to changes in investment opportunities compared to financially distressed firms, while the opposite is true for investments in intangible capital. Lastly, we find that including the cash flow variable does not signal the presence of financial constraints under the investment-q framework.Research limitations/implicationsA limitation of this study is that the investment-q theory posits that q explains investment behavior. The omission of additional determinants of investment may bias our results. Second, our study revealed a significant role for firm financial condition on the sensitivity of investment rates to investment opportunities. Firms that are financially distressed are more likely to have lower market values relative to the book value of their capital stock and consequently a lower total q-value. However, a lower total q does not always map directly to a lower investment rate.Practical implicationsFor financially distressed agribusinesses, our findings suggest they should focus on improving their financial position before pursuing new investment opportunities. Specifically, these firms should prioritize paying down debt to reduce leverage and improving profitability to better position themselves to take advantage of investment opportunities. Additionally, given their growing importance in maintaining a competitive advantage, agribusinesses may benefit from frameworks that better evaluate intangible investments.Originality/valueWe extend the investment-q framework by examining how financial health affects investment behavior across capital types in agribusinesses. Unlike previous studies that use cash flow to signal the presence of financial constraints, we employ the Altman Z-score as a comprehensive measure of firm financial condition, providing clearer differentiation between financially distressed and healthy firms.
PurposeAgriculture is the backbone of the Indian economy. Over 50% of the workforce is engaged in the agricultural sector, and at least 14% of India's GDP emanates from the farm sector. The present study aims to assess the technical efficiency of paddy farmers in the two districts of West Bengal (Purba Bardhaman and Purulia) and to examine the effect of financial literacy (FL) on their technical efficiency.Design/methodology/approachData on 503 farmers (260 from Purba Bardhaman and 243 from Purulia) were collected through a primary survey. S&P Global Fin_Lit questions were used to measure the FL amongst the sample farmers. The stochastic frontier model was employed to examine the effect of FL on farmers' technical efficiency.FindingsThe study's results showed that the average efficiency level of Paddy farmers was high (94.04%). The study's outcome showed that different dimensions of FL played an instrumental role in reducing the inefficiency levels of the paddy farmers. In addition, age, location of the farmers, land-holding size, agricultural income, farming experience, and the distance of the farmland from the farmer's house significantly affected the efficiency of the paddy farmers.Originality/valueVery few studies have assessed the effect of FL on farmers' technical efficiency. To the best of our knowledge, this is the first attempt, especially in the Indian context, to examine the effect of FL on farmers' efficiency.
PurposeAgricultural insurance is an important risk management tool, essential for maintaining agricultural activities and reducing losses caused by adverse situations. Innovation, in turn, is crucial for the maintenance and development of various sectors. This research aimed to analyze the innovation and use of new technologies applied to the agricultural insurance sector. Design/methodology/approachThe systematic literature review was carried out in the Scopus and Web of Science databases, which yielded 28 articles that met the selection criteria. A co-citation network was developed using the VOSviewer Software, allowing the formation of clusters grouping studies whose implications of innovation or use of new technology converged to the same theme. FindingsClusters referred to pricing and risk analysis, resilience and risk transfer, adverse selection and climate change, cost reduction and transparency in contracts and introduction and/or distribution of agricultural insurance. The results show that Asian countries stand out in the number of studies related to innovation in agricultural insurance. We also verified that the research analyzed contemplates that innovations and new technologies benefit those involved in the agricultural insurance system, including improvements in pricing, risk analysis and distribution. Thus, costs are minimized, and farmers have greater access to this risk management tool. Originality/valueThe analysis of technological Innovations in the context of agricultural insurance emerges as a fundamental principle for decision-making by rural managers, agricultural insurance companies and federal government bodies intending to develop public policies ensuring the maintenance of agricultural activities. Therefore, it is an emerging topic for investigation and practical adoption.
PurposeAgricultural index-based insurance helps farmers to mitigate the adverse effects of climate change. However, adoption rates remain low in developing countries. A number of reasons such as basis risk, high insurance premium and lack of trust in insurance providers, have been cited for the low adoption among farmers. Additional influencing factors could be the characteristics of the insurance agent who sells insurance policies to farmers. In this study, we examine whether the gender of the insurance agent influences male farmers' adoption of index-based insurance, disaggregated by the educational level of farmers.Design/methodology/approachWe run probit regressions on a sample of 783 male farmers producing maize in Mali, which was collected in fall of 2021.FindingsOur results show that male farmers are less likely to adopt index-based insurance if the insurance agent is a female rather than a male. Disaggregated by education level, we find that the higher the education level of the farmer, the more irrelevant the gender of the agent becomes for the purchase decision.Originality/valueOur study highlights the need to take local gender norms into account and shows that formal education is an important facilitator of balanced gender perceptions. We contribute to the discussion about farmers' low adoption of index-based insurance, particularly in Mali.
PurposeThis study examines the impact of microfinance credit on household food security in drought-prone North Wollo, Ethiopia, while addressing selection bias and gender disparities in credit access.Design/methodology/approachUsing primary data from 369 households, we employ an endogenous switching regression (ESR) model to estimate the effects of microfinance participation on caloric intake, dietary diversity and food consumption scores. Instrumental variables distance to microfinance institutions[(MFI) offices and perceived interest rates] control for endogeneity.FindingsResults indicate that microfinance participants consume 17% more calories (2,496 vs. 2,129 kcal/AE/day) and achieve significantly higher dietary diversity (6.29 vs. 5.72 food groups) than non-participants. Counterfactual analysis confirms non-participants could attain similar gains with credit access. However, male-headed households are 15.5% more likely to access credit, highlighting persistent gender inequities. High perceived interest rates and joint liability risks further deter participation.Practical implicationsMFIs should adopt gender-sensitive lending practices, align repayment schedules with agricultural cycles and improve transparency on interest rates to enhance food security impacts. Policymakers must strengthen rural financial infrastructure to mitigate geographic and institutional barriers.Originality/valueThis study contributes to the agricultural finance literature by rigorously quantifying microfinance's role in food security using ESR, while identifying context-specific barriers in vulnerable agro-ecological zones.
PurposeThis study investigates the factors behind the rapid increase in household debt to financial institutions in Cambodia during the 2010s, focusing on the roles of agricultural land prices, land registration and financial institutions' lending behavior.Design/methodology/approachEconometric analyses are conducted using household-level data from the Cambodia Socio-Economic Survey to examine how changes in land prices and land registration influenced household borrowing, while also considering shifts in financial institutions' lending stance.FindingsThe results suggest that rising agricultural land prices significantly contributed to the increase in household debt in the late 2010s by enhancing the collateral value of land. In contrast, the impact of land registration was relatively small. Additionally, financial institutions appear to have adopted a more aggressive lending stance during this period, further driving the growth in outstanding debt.Originality/valueThis study is the first to examine the effect of land prices on household debt to financial institutions in a developing country like Cambodia. In the Cambodian context, its originality lies in the analysis of the mechanism of increasing households' debt to financial institutions and the role of land registration.
PurposeThis study aims to measure the performance of agribusiness cooperatives and investigate the determinants of their performance differentials.Design/methodology/approachMicrodata obtained from a sample of 230 Brazilian agribusiness cooperatives in the year 2022 were analyzed. We combined cluster analysis, data envelopment analysis (DEA) and Tobit regression models.FindingsCooperatives in the sample presented low technical efficiency (TE) scores, with average efficiency levels of 21.85%, 35.96 and 63.93% for clusters 2, 3 and 4, respectively. Thus, these firms could considerably increase the production value with the same endowment of inputs (labor and capital) and production technology. It was also observed that larger cooperatives tend to be more technically efficient than small ones. Board members' education level and the proportion of women in the workforce have positive and statistically significant effects on TE of cooperatives.Originality/valueStudies on TE in agricultural cooperatives in the context of Brazil considering microdata are scarce. Relevant managerial propositions are presented.
