ABSTRACT

Technology adoption and human capital are crucial determinants of economic growth. Here we use a fixed-effect panel model to measure the link between technology adoption and human capital for a sample of 104 countries since 1870–2010 using (HCCTA) and long-run enrolment ratios and educational attainment datasets. Unobserved heterogeneity factors (institutional, tradition, culture, economy type, educational system, migration, innovation, patents) account for the observed difference across countries/regions. Gender difference plays a role in the technology diffusion–human capital relationship, not a vital one. Advanced economies rode on the first three industrial revolutions, with Eastern Europe catching up on the third and fourth industrial waves. The economies of the East used the fourth industrial revolution to converge and surpass other regions. The results show that technology is necessary but not a sufficient determinant of human capital growth. Selective technology adoption policy, accompanied by supporting educational policy (entrepreneurial and research universities) stimulates technology, diffusion, and knowledge spillover. Our results are robust for including population and growth as significant technology adoption and human capital determinants (conditioning variables). Technology, diffusion, and a human capital link is a two-way street with many constraints.

摘要

技术采用和人力资本是经济增长的关键决定因素。在这里，我们使用固定效应面板模型来衡量自 1870 年至 2010 年以来 104 个国家样本的技术采用与人力资本之间的联系，使用 (HCCTA) 和长期入学率和教育程度数据集。未观察到的异质性因素（制度、传统、文化、经济类型、教育体系、移民、创新、专利）解释了观察到的国家/地区之间的差异。性别差异在技术扩散-人力资本关系中发挥作用，而不是至关重要的关系。发达经济体利用了前三次工业革命，东欧赶上了第三次和第四次工业革命。东方经济利用第四次工业革命向其他地区汇聚和超越。结果表明，技术是必要的，但不是人力资本增长的充分决定因素。选择性技术采用政策以及支持性教育政策（创业型和研究型大学）刺激了技术、传播和知识溢出。我们的结果是稳健的，将人口和增长作为重要的技术采用和人力资本决定因素（条件变量）。技术、传播和人力资本的联系是一条双向的道路，有很多限制。我们的结果是稳健的，将人口和增长作为重要的技术采用和人力资本决定因素（条件变量）。技术、传播和人力资本的联系是一条双向的道路，有很多限制。我们的结果是稳健的，将人口和增长作为重要的技术采用和人力资本决定因素（条件变量）。技术、传播和人力资本的联系是一条双向的道路，有很多限制。