爪哇岛农业部门绩效劳动力的面板数据2007-2014

Joko Pranoto, A. Utomo, Muhamad Fathul Muin
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摘要

粮食作物工人人数减少最多的是爪哇,2007-2014年减少了28700万人。爪哇粮食作物农业工人的年龄以45岁以上的工人为主(64.95%)。如果不增加新的工人,那么粮食作物劳动力将越来越多地由老年人群体主导,这将使农业部门难以履行其改善和维持可持续粮食安全的任务。本研究的目的是从爪哇2007-2014年的劳动力吸收方面描述粮食作物农业分部门的状况,并分析粮食作物分部门的区域GDP、实际工资、教育、土地面积对农业粮食作物分部门对劳动力的吸收能力的影响。与爪哇岛上其他四个省份相比,中爪哇省是农业粮食分部门工人人数减少最多的省份。从估计结果来看,选择具有截面SUR的固定效应模型作为最佳模型。研究结果表明,地区GDP、实际工资、土地面积对农业粮食作物细分行业劳动力吸收具有显著的正向影响,而教育对农业粮食作物细分行业劳动力吸收具有显著的负向影响。总的来说,这个模型能够解释这种现象的89,32%的变化。与此同时,另有10.68%是由模型中未包含的其他变量解释的。
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Performance Labor in Agriculture Sector in Java Island Using Panel Data 2007-2014
The highest decrease in the number of food crop workers occurred in Java, as many as 2,87 million people in 2007-2014. The age of food crop agriculture workers in Java is dominated by workers aged over 45 years (64,95%). If there is no addition of new workers, then the food crop labor will be increasingly dominated by old age groups which will make it difficult for the agricultural sector to carry out its mandate to improve and maintain sustainable food security. The purpose of this study is to describe the condition of the food crop agriculture subsector from the aspect of labor absorption in Java for the period 2007-2014 and analyze the effect of the regional GDP of food crops subsector, real wages, education, and land area to the absorption power of agricultural food crops subsector on labor in Java. Central Java Province is a province with the largest decrease in the number of agricultural food crop subsector workers compared to the other four provinces on Java island. From the results of the estimation, the fixed-effect model with cross-section SUR is chosen as the best model. The results show that the variable of regional GDP, real wage, and size of land area has a significant and positive effect on the labor absorption of agricultural food crops subsector, while education has a significant and negative effect. Overall this model able to explain variations of this phenomenon by 89,32%. Meanwhile, another 10,68% is explained by other variables not included in the model.
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