探讨利率、宏观经济环境、农业周期和性别对农业部门贷款需求的影响:马里的证据

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Tim Ölkers, Oliver Mußhoff
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引用次数: 0

摘要

正规信贷对发展中国家农业部门的发展起着重要作用,因为许多农民的流动性受到限制。获得信贷可以提高农民对投入和农业技术的购买力,从而提高整体生产率。马里的农民特别容易受到暴雨等冲击的影响。获得流动资金以提高农业部门的抗灾能力至关重要。因此,需要更高的融资量,这就需要对农业贷款需求进行分析。本文旨在从萨赫勒地区的一个国家出发,实证研究利率、宏观经济环境、农业周期和农民性别对农业部门贷款需求的影响。本分析采用了马里一家商业银行提供的农场层面独特而全面的贷款数据。分析时间跨度为 2010 年至 2020 年。结合了两种不同的估算策略。首先,以发放的贷款额为因变量,采用普通最小二乘法回归。其次,应用机器学习技术、最小绝对收缩和选择算子来选择最相关的特征作为估计中的解释变量。结果显示,利率、总附加值、农民性别以及农业周期对农业贷款需求有显著的统计学影响。这些结果对处理金融包容性和市场失灵问题的政策制定者和农业金融机构很有意义,他们可以将这些信息纳入未来贷款产品的设计中,以刺激农民的贷款需求,尤其是女性农民的贷款需求。[经济学引文:G20、G21、O13、O16、Q14、Q18]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Exploring the role of interest rates, macroeconomic environment, agricultural cycle, and gender on loan demand in the agricultural sector: Evidence from Mali

Exploring the role of interest rates, macroeconomic environment, agricultural cycle, and gender on loan demand in the agricultural sector: Evidence from Mali

Formal credit plays an important role for the development of the agriculture sector in developing countries because many farmers are characterized as liquidity constrained. Access to credit can increase farmers' purchasing power for inputs and agricultural technology, thus raising the overall productivity. Farmers in Mali are particularly vulnerable to shocks, such as heavy precipitation events. Access to liquidity to increase the resilience of the agricultural sector is essential. Therefore, higher financing volumes are required, which make the analysis of loan demand in agriculture of interest. The purpose of this paper is to empirically investigate the role of the interest rate, the macroeconomic environment, the agricultural cycle and the gender of the farmer on the loan demand in the agricultural sector from a country in the Sahel. Unique and comprehensive loan data at the farm level, provided by a commercial Malian bank, is used for this analysis. The analysis covers the period from 2010 to 2020. Two different estimation strategies are combined. First, an ordinary least square regression is applied with the granted loan amount as the dependent variable. Second, the machine learning technique, least absolute shrinkage and selection operator, is applied to select the most relevant features to be used as explanatory variables in the estimation. The results reveal that the interest rate, the gross value added, the farmer's gender as well as the agricultural cycle have statistically significant effects on the granted loan demand in agriculture. These results are of interest to policymakers, who deal with financial inclusion as well as market failures, and agricultural financial institutions who could incorporate such information in the design of future loan products to stimulate farmers' loan demand, especially for female farmers. [EconLit Citations: G20, G21, O13, O16, Q14, Q18].

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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