Abstract:Resumo: O presente trabalho objetiva avaliar o efeito do microcrédito rural sobre o valor da produção agropecuária dos municípios nordestinos atendidos pelo Programa Agroamigo, levando em consideração o volume concedido de empréstimos e o tempo de exposição aos beneficiários. Para tanto, utilizou-se do modelo de diferenças em diferenças (DD) com controle para efeito fixo para um painel anual de 1.791 municípios da região entre 2003 e 2015, usando dados administrativos do programa, indicadores sociais da Relaçã… Show more
“…To solve the financial constraint problem of farmers to promote the process of agricultural modernization, Soeters et al (2017) and Larionov (2020) found that injecting large amounts of financial resources into rural areas with weak funds can help increase crop planting areas. Guedes et al (2021) assessed the impact of rural microfinance on agricultural production value by considering both the amount of the loan issued and the time when the benefit was obtained. Miranda et al (2019) proposed that agricultural product supply chain members subject to capital constraints can conduct warehouse receipt financing with their partners.…”
This study attempts to determine the optimal production and pricing decisions of E-Agri-SCF (agricultural product supply chain financed by e-commerce) and analyzes the influence of financing parameters on the optimal decision. Research indicates that the optimal purchase price decision increases with the expansion of the financing interest rate and declines with the expansion of the capital opportunity cost. The expected output factor of agricultural products has no influence on the optimal purchase price decision. The optimal production decision of the farmer declines with the expansion of the financing interest rate and the opportunity cost of capital and increases with the increase in the expected output factor of agricultural products. In particular, we show that due to the uncertainty in the output of agricultural products, the losses caused by decentralized decision-making in the E-Agri-SCF will increase. Therefore, this article proposes using a cost-sharing contract to promote the coordination of E-Agri-SCF. We prove that when farmers share more costs, they obtain higher benefits, while the e-commerce platform does the opposite. This is because the participation of e-commerce platforms in financing has changed the revenue structure of the supply chain. The findings of this article are very meaningful, as they provide management opinions on the financing terms of E-Agri-SCF.
“…To solve the financial constraint problem of farmers to promote the process of agricultural modernization, Soeters et al (2017) and Larionov (2020) found that injecting large amounts of financial resources into rural areas with weak funds can help increase crop planting areas. Guedes et al (2021) assessed the impact of rural microfinance on agricultural production value by considering both the amount of the loan issued and the time when the benefit was obtained. Miranda et al (2019) proposed that agricultural product supply chain members subject to capital constraints can conduct warehouse receipt financing with their partners.…”
This study attempts to determine the optimal production and pricing decisions of E-Agri-SCF (agricultural product supply chain financed by e-commerce) and analyzes the influence of financing parameters on the optimal decision. Research indicates that the optimal purchase price decision increases with the expansion of the financing interest rate and declines with the expansion of the capital opportunity cost. The expected output factor of agricultural products has no influence on the optimal purchase price decision. The optimal production decision of the farmer declines with the expansion of the financing interest rate and the opportunity cost of capital and increases with the increase in the expected output factor of agricultural products. In particular, we show that due to the uncertainty in the output of agricultural products, the losses caused by decentralized decision-making in the E-Agri-SCF will increase. Therefore, this article proposes using a cost-sharing contract to promote the coordination of E-Agri-SCF. We prove that when farmers share more costs, they obtain higher benefits, while the e-commerce platform does the opposite. This is because the participation of e-commerce platforms in financing has changed the revenue structure of the supply chain. The findings of this article are very meaningful, as they provide management opinions on the financing terms of E-Agri-SCF.
“…Manrique et al (2017), desarrollo un modelo de impacto donde destaca que los receptores de los servicios microcrediticos aumentan sus activos en 17.89% con el objetivo de acrecentar los sistemas productivos rurales. Assis et al (2021), resalta el efecto de los programas microcrediticos rurales en las actividades agrícolas, pues, el indicador costo beneficio repercute en el incremento moderado del retorno con respecto a la inversión, ligado a ello, los efectos del programa en los beneficiarios representan el 3.5% de la producción agrícola rural, por cual el 22% de la producción es ganadera. La imagen del microcrédito a una tasa factible con periodos de pago asequibles y montos provechosos dinamiza la economía, generando así en las familias un incremento significativo de activos y potencializar las microempresas familiares (Maguiña et al, 2021).…”
El artículo determina el efecto del microcrédito en el bienestar socioeconómico del sector transporte urbano de la ciudad de Chachapoyas, Amazonas. Para ello, se empleó los métodos inductivo - deductivo y analítico – sintético, de tipo descriptivo, además, se combinan técnicas de investigación cuantitativa, donde el instrumento de recolección de datos empleados fue el cuestionario. En tal sentido, el tipo de muestreo fue por conveniencia recopilando información de 94 transportistas. Los resultados evidencian que los ingresos familiares se incrementaron en un rango de S/ 2000 a S/ 4000, por lo tanto, las familias presentaron mejoras en las condiciones de vivienda, adquisición de activos, demanda por tecnologías digitales y formación educativa básica. En conclusión, el microcrédito tiene un efecto positivo en el bienestar socioeconómico, donde se destaca el crecimiento del ingreso familiar y la mejora de la calidad educativa de los niños y adolescentes.
“…Londoño et al (2021) plantean que el microcrédito está basado en el pensamiento de mejorar su calidad de vida y la capacidad de generación de riqueza por parte del individuo, reduciendo la pobreza en términos generales, por lo tanto, el acceso a este tipo de recursos es fundamental en la vida económica del individuo o empresa. Guedes et al (2021) sostienen que la desigualdad que se presenta en los países emergentes se da en razón, a que la totalidad de la población no tiene acceso de forma equitativa al beneficio que genera la evolución y desarrollo del sistema financiero. No obstante, Yunus (2004) demostró que otorgando pequeñas sumas de dinero a individuos marginados del sistema financiero, estos fueron pagados a través de los ingresos que generaban sus actividades principales.…”
RESUMEN: Las instituciones financieras buscan cada día reducir los costos operativos relacionados con el otorgamiento del crédito, para tal fin se desarrolla un modelo score que permita lograr dicho objetivo. Este trabajo utiliza las metodologías de la regresión logística y el análisis discriminante tomando como referencia una base de datos conformada por 469.996 clientes pertenecientes a la modalidad del microcrédito, de los cuales se tienen variables cualitativas y cuantitativas. El objetivo es encontrar el mejor modelo que permita tener la mejor estimación y que evidencie beneficios a la hora de tener un modelo score. Se concluye que la regresión logística es el modelo que mejor diferencia y pronostica los clientes buenos de los malos, logrando conseguir reducir el nivel de pérdidas esperadas.Palabras Clave: microcrédito, riesgo de crédito, probabilidad de incumplimiento y modelo score.ABSTRACT: Financial institutions seek every day to reduce operating costs related to the granting of credit, for this purpose a score model is developed to achieve this objective. This work uses the methodologies of logistic regression and discriminant analysis, taking as a reference a database made up of 469,996 clients belonging to the microcredit modality, of which there are qualitative and quantitative variables. The objective is to find the best model that allows to have the best estimate and that shows benefits when having a score model. It is concluded that logistic regression is the model that best differentiates and predicts good customers from bad ones, managing to reduce the level of expected losses.
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