The impact of Economic Growth, Foreign Investment, Wages, and Human Development Index on Educated Unemployment

Reyna Karlina, Aula Ahmad Hafidh Siaful Fikri
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Abstract

This study aims to measure four independent variables and one dependent variable using secondary data in the form of panel data comprising 27 districts/cities in a cross-section and a time series over 5 years. The data analysis method employed is panel data regression with the random effects method. Eviews version 12 was utilized for data processing, including testing classical assumptions, hypothesis testing, and testing the Adjusted coefficient of determination (R2). The research findings indicate significant relationships between specific variables and educated unemployment. Economic Growth negatively and significantly impacts educated unemployment, demonstrating its ability to decrease educated unemployment in the region. Minimum District Wage positively and significantly influences educated unemployment, implying that increasing UMK in an area can elevate the number of educated unemployed individuals. Additionally, the Human Development Index (HDI) exerts a negative and significant effect on educated unemployment, suggesting that higher HDI can reduce educated unemployment. However, foreign investment does not significantly affect educated unemployment. Overall, the study shows that these four independent variables explain 67.8% of educated unemployment, while the remaining 32.2% is influenced by factors beyond the study's scope.
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经济增长、外国投资、工资和人类发展指数对受教育失业的影响
本研究的目的是测量四个自变量和一个因变量,使用二次数据的形式,面板数据包括27个地区/城市的横截面和时间序列超过5年。数据分析采用随机效应面板数据回归方法。使用Eviews version 12进行数据处理,包括经典假设检验、假设检验和调整后的决定系数(R2)检验。研究结果表明,特定变量与受过教育的失业之间存在显著关系。经济增长对受教育失业有显著的负向影响,表明经济增长有能力降低该地区的受教育失业。最低地区工资对受过教育的失业人数有显著的正向影响,这意味着提高一个地区的最低地区工资可以提高受过教育的失业人数。此外,人类发展指数(HDI)对受过教育的失业有显著的负向影响,表明更高的HDI可以减少受过教育的失业。然而,外国投资对受过教育的失业没有显著影响。总体而言,研究表明,这四个自变量解释了67.8%的受过教育的失业,而剩下的32.2%则受到研究范围之外的因素的影响。
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来源期刊
World Journal of Science Technology and Sustainable Development
World Journal of Science Technology and Sustainable Development GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
5.50
自引率
0.00%
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0
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