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Modeling Poverty Indices Among Crop Farmers Using Beta and Dirichlet Regression Models; A Case of Uasin Gishu County, Kenya

机译:使用Beta和Dirichlet回归模型在农作物农民中建模贫困指数;肯尼亚的Uasin Gishu County的案例

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Poverty and its alleviation schemes remain to be of much concern to many countries in the world. In the Sub-Saharan Africa, 41% of the population live below the extreme poverty line and in Kenya, almost 80% of the population are deemed poor. The Kenyan rural sector has a contribution of 40% to this poverty levels despite agriculture being the backbone and the main source of livelihood in the rural areas. It is in this regard that the study evaluates the household characteristics effect on Poverty indices among Crop Farmer Households. The Beta and Dirichlet regression models were used in the analysis in which the Beta regression model gave a better fit to the poverty indices data. The standardized residuals, probability plots, Chi-square test of association and the Breusch Pagan test for heteroscedasticity were used as goodness of fit evaluation tests in which levels of deprivation had a significant effect on the poverty indices among the crop farmers. Data used in the study was secondary data obtained from the Kenya National Bureau of Statistics Survey Consumption Index in Uasin Gishu County for the period March 2018 to May 2018 in which a total of 489 households were employed in the survey.
机译:贫困及其减轻方案仍然是世界上许多国家的关注。在撒哈拉以南非洲,41%的人口生活在极端的贫困线和肯尼亚之下,近80%的人口被视为贫困。肯尼亚农村部门仍有40%的贫困水平贡献,尽管农业是骨干和农村生计的主要来源。在这方面,该研究评估了对农作物家庭中贫困指数的家庭特征影响。测试版和Dirichlet回归模型用于分析,其中β回归模型对贫困指数进行了更好的拟合。结合的标准化残留,概率图,Chi-Square试验和异源性的Breusch Pagan试验用作拟合评价试验的良好,其中剥夺水平对作物农民中的贫困指数产生了重大影响。该研究中使用的数据是从肯尼亚国家统计调查消费指数获得的二级数据,于2018年3月至2018年5月至2018年5月,在该调查中雇用了489户家庭。

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