自动化在流行病中的作用

IF 1.9 3区 经济学 Q2 ECONOMICS
Shaofeng Xu, Tao Liu, Fengliang Liu
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引用次数: 0

摘要

本文探讨了自动化在流行病中的总体影响和分配影响。利用中国制造业的行业和企业数据,我们发现 COVID-19 大流行导致工业机器人的安装量大幅增加,而在健康危机期间,那些更积极采用机器人的企业经历的收入损失更少,高技能工人和低技能工人之间的工资差距扩大得更明显。随后,我们建立了一个基于 SIS 的宏观经济模型来解释这些观察结果。模型经济有两种稳定状态,疫情爆发会引发从无疾病稳定状态到流行病稳定状态的制度转换。在过渡过程中,由于劳动力短缺和工资上涨,机器人的采用速度加快,缓解了产出损失,但对低技能劳动力的影响更大。在工人可以选择远程工作的扩展环境中,这些结果是稳健的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the role of automation in an epidemic

This paper examines aggregate and distributional implications of automation in an epidemic. Using industry-level and firm-level data from the Chinese manufacturing sector, we document that the COVID-19 pandemic has led to a significant surge in the installation of industrial robots, and during the health crisis firms with more aggressive robot adoption experienced less severe revenue losses and a more pronounced increase in the wage gap between high-skilled and low-skilled workers. We then develop a tractable SIS-based macroeconomic model to explain these observations. The model economy has two steady states, and an outbreak can trigger a regime-switching transition from a disease-free steady state to an epidemic steady state. Accelerated robot adoption in the transition, stemming from labor shortfall and wage inflation, alleviates the loss in output but affects low-skilled labor disproportionately. These results are robust in an extended setting, where workers have an option to work remotely.

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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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