工资
工资增长
劳动经济学
新兴技术
经济
面板数据
差异(会计)
计算机科学
计量经济学
人口经济学
人工智能
会计
作者
Frank M. Fossen,Alina Sorgner
标识
DOI:10.1016/j.techfore.2021.121381
摘要
We analyze heterogeneous effects of new digital technologies on individual-level wage and employment dynamics in the United States from 2011-2018. To this end, we employ four digital technology measures from recent literature: computerization probabilities of occupations, occupational impacts of artificial intelligence, and the suitability of tasks for machine learning and their within-occupation variance. Based on CPS and ASEC panel data, the results indicate that labor-displacing digital technologies are associated with slower wage growth and higher probabilities of switching one's occupation and becoming non-employed. In contrast, labor-reinstating digital technologies improve individual labor market outcomes. Workers with high levels of formal education are most affected by the new generation of digital technologies.
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