失业
匹配(统计)
背景(考古学)
自动化
坠落(事故)
劳动经济学
机器人
经济
德雷福斯技能获得模型
德国的
计算机科学
工程类
人工智能
经济增长
统计
环境卫生
古生物学
历史
生物
机械工程
考古
医学
数学
作者
Dario Cords,Klaus Prettner
出处
期刊:Oxford Economic Papers-new Series
[Oxford University Press]
日期:2021-06-17
卷期号:74 (1): 115-135
被引量:12
摘要
Abstract Will automation raise unemployment and what is the role of education in this context? To answer these questions, we propose a search and matching model of the labour market with two skill types and with industrial robots. In line with evidence to date, robots are better substitutes for low-skilled workers than for high-skilled workers. We show that robot adoption leads to rising unemployment and falling wages of low-skilled workers and falling unemployment and rising wages of high-skilled workers. In a calibration to Austrian and German data, we find that robot adoption destroys fewer low-skilled jobs than the number of high-skilled jobs it creates. For Australia and the USA, the reverse holds true. Allowing for endogenous skill acquisition of workers implies positive employment effects of automation in all four countries. Thus, the firm creation mechanism in the search and matching model and skill acquisition are alleviating the adverse effects of automation.
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