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Reducing Poverty of Cocoa Smallholders in Indonesia: Is Agricultural Economic Activity Still the Pioneer?

机译:减少印度尼西亚可可小农的贫困:农业经济活动仍是先锋吗?

摘要

One of the crucial debates arises when finding a solution for reducing ruraludpoverty, is how the causes of poverty should be classified into the agriculturaludand non-agricultural economic activities. A strong assumption is that,udagricultural and non-agricultural economic activities could be expected to reduceudpoverty, but it is difficult to determine the economic activities that have a strongudpositive impact on rural poverty reduction. This paper identifies the povertyudcauses of two villages (hereafter, ???desa???) in Indonesia by interviewing 152 cocoaudsmallholder households. We employed a (1) Head Count and Poverty Gap Indicesudfor describing the poverty situation, (2) Factor Analysis for constructingudrepresentative factors for the dimension, (3) Path Analysis for identifying theuddirect and indirect impacts of explanatory variables on household income as audpoverty proxy, and (4) Paired-samples T-Test to evaluate the degree of povertyuddifferences. It was found that; (1) statistically, there is no differentiation in theuddegree of poverty between Desa Compong and Desa Maddenra. However, there isuda differentiation in income structure, meaning that the causes of poverty areuddifferent; (2) the orientation of cocoa production is strong and directly associatedudwith the poverty in Compong, while for coffee, cashew-nut and livestockudproduction are associated with poverty in Maddenra. A major implication ofudthese findings is that encouraging cocoa production in Compong, and coffee,udcashew-nut & livestock production in Maddenra can be strongly expected toudreduce poverty directly, meaning that agricultural economic activity is still theudpioneer to reduce rural poverty directly in the country.
机译:寻找减少农村贫困的解决方案时,最关键的辩论之一是如何将贫困原因归为农业非农业经济活动。一个有力的假设是,可以预期农业和非农业经济活动将减少贫困,但是很难确定对农村减贫产生重大综合影响的经济活动。本文通过采访152个可可豆/小农户,确定了印度尼西亚两个村庄的贫困/原因。我们采用(1)人数和贫困差距指数 ud来描述贫困状况,(2)因子分析为维度构建 udrepresentative因子,(3)路径分析用于确定解释变量对贫困人口的 uddirect和间接影响家庭收入作为 uproverty代理,和(4)配对样本T检验来评估贫困 uddifference的程度。发现: (1)从统计学上讲,Desa Compong和Desa Maddenra之间的贫困程度没有区别。但是,收入结构存在差异,这意味着贫困的原因是不同的。 (2)可可生产的方向很强,与康邦的贫困直接相关,而咖啡,腰果和牲畜的生产与马登德拉州的贫困相关。这些发现的主要含义是,可以强烈期望鼓励贡邦的可可生产以及马登德拉的咖啡,腰果和牲畜的生产直接减少贫困,这意味着农业经济活动仍然是减少农村人口的积极因素。贫困直接在该国。

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