亚齐省农业部门对贫困的影响

Ridho Fatwa, Srinita Srinita, M. Abrar
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摘要

本研究旨在分析亚齐省农业部门对贫困的影响。在本研究中,影响亚齐省贫困水平的变量是国内生产总值(GDP)在农业部门的份额、农业部门的劳动力、农业用地、农民教育和人均区域国内生产总值(GRDP)。本研究使用的回归模型是使用面板数据的多元线性回归分析方法(普通最小二乘回归分析)和固定效应方法(固定效应模型)来确定变量之间的影响。本研究的结果基于同时检验(检验F),该检验表明,总体而言,自变量(农业部门的GDP份额、农业部门的劳动力、农业用地、农民教育和人均GRDP)共同显示了它们对贫困水平的影响。基于偏检验(t检验)的研究结果表明,农业部门GRDP和人均GDP占比变量对贫困具有负向显著影响,农业部门劳动力对贫困具有正向显著影响,而农业用地和农民受教育程度变量对贫困具有负向影响,但不显著。本研究调整后的r平方值为0.868629。这表明,因变量即亚齐省贫困的86.86%的变化可以用自变量即农业GRDP份额、农业人力、农业用地、农民教育和人均GRDP来解释。而剩下的13.14%是由模型之外的其他因素解释的。
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The Effect of the Agriculture Sector on Poverty in Aceh Province
This study aims to analyze the influence of the agricultural sector on poverty in Aceh Province. In this study, the variables used in influencing the poverty level in Aceh Province are the share of Gross domestic product (GDP) in the agricultural sector, labor in the agricultural sector, agricultural land, Farmer Education and Gross Regional Domestic Product (GRDP) per capita. The regression model used in this study is the method of multiple linear regression analysis (ordinary least squares regression analysis) using panel data and a fixed effect approach (fixed effect model) to determine the effect between variables. The results of this study are based on a simultaneous test (Test F) which shows that overall, the independent variables (share of GDP in the agricultural sector, labor in the agricultural sector, agricultural land, Farmer Education and GRDP per capita together show their effect on the poverty level. The results of the study based on a partial test (t test) showed that the share of the agricultural sector GRDP and the GDP per capita variable had a negative and significant effect on poverty and agricultural sector labor had a positive and significant effect on poverty, while the variables of agricultural land and farmer education negative effect, but not significant. The value of Adjusted R-squared in this study is 0.868629. This shows that the 86.86 percent change in the dependent variable, namely the Poverty of Aceh Province, can be explained by the independent variable, namely Share of Agricultural GRDP, Agricultural Manpower, Agricultural Land, Farmer Education and Per Capita GRDP. While the remaining 13.14% is explained by other factors outside the model.
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