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英文文献：Industrial Growth in Sub-Saharan Africa: Evidence from Machine Learning with Insights from Nightlight Satellite Images-撒哈拉以南非洲的工业增长:机器学习的证据与夜光卫星图像的洞察力
英文文献作者：Christian S. Otchia,Simplice A. Asongu
英文文献摘要：
This study uses nightlight time data and machine learning techniques to predict industrial development in Africa. The results provide the first evidence on how machine learning techniques and nightlight data can be used to predict economic development in places where subnational data are missing or not precise. Taken together, the research confirms four groups of important determinants of industrial growth: natural resources, agriculture growth, institutions, and manufacturing imports. Our findings indicate that Africa should follow a more multisector approach for development, putting natural resources and agriculture productivity growth at the forefront.
这项研究使用夜光时间数据和机器学习技术来预测非洲的工业发展。这些结果为机器学习技术和夜光数据如何被用于预测缺少或不精确的地方经济发展提供了第一个证据。综合来看，研究证实了工业增长的四个重要决定因素:自然资源、农业增长、制度和制造业进口。我们的研究结果表明，非洲应该采取更加多部门的发展方式，把自然资源和农业生产率增长放在首位。
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