常规任务偏向型技术变革与内生技能投资
Routine-Biased Technological Change and Endogenous Skill Investments
American Economic Journal: Economic Policy · 2025 · Danyelle Branco、Bladimir Carrillo、Wilman J. Iglesias
中文摘要
我们考察个人如何调整其教育投资以应对常规任务偏向型技术变革。我们发现，在受机器人影响地区成长的个人更有可能完成学士学位，并且其收入experienced相对增长。技能溢价与机会成本的变化似乎是驱动这些效应的原因。为解释这些发现，我们估计了一个内生技能获取模型，其中技能需求与供给的变化共同塑造了收入的演变路径。反事实模拟表明，除非教育补贴足够慷慨，否则内生的技能反应无法完全抵消自动化对收入的不利影响。（JEL I26, J22, J23, J24, J31）
Abstract
We investigate how individuals alter their educational investments in response to routine-biased technology. We find that individuals growing up in robot-impacted areas are more likely to complete a bachelor’s degree and experience a relative increase in earnings. Changes in the skill premium and opportunity cost appear to drive these effects. To interpret these findings, we estimate a model of endogenous skill acquisition where changes in the demand and supply of skills shape the path of earnings. Counterfactual simulations suggest that the endogenous skill response cannot fully undo the adverse earnings effects of automation unless there are sufficiently generous educational subsidies. (JEL I26, J22, J23, J24, J31)
📖 解析
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