Implications of Automation for Global Migration

Yixiao Zhou, Rodney Tyers

Research output: Working paperDiscussion paper

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Abstract

Relative wages and the share of total value added accruing to low-skill workers have declined during the past three decades, among both OECD countries and large developing countries. The primary beneficiary until recently has been skill, the supply of which has risen as education investment has increased. The rise in artificial intelligence (AI)-driven automation suggests that declines in value added shares accruing to low-skill workers will continue. Indeed, AI-driven automation creates an impulse for diminished labor market performance by low-skill workers throughout the world but most prominently in high-fertility, relatively youthful regions with comparatively strong growth in low-skill labor forces. The implied bias against such regions will therefore enhance emigration pressure. This paper offers a preliminary analysis of these effects. Central to the paper is a model of the global economy that includes general demography and real wage sensitive bilateral migration behavior, which is used to help quantify potential future growth in real wage disparities and the extent, direction and content of associated migration flows. Overall, global wage inequality is increased by expanded skilled migration, primarily because of large increases in skilled wage premia that arise in developing regions of origin. Inter-regional divergences in skilled wages are reduced, however, due to the additional skilled labour market arbitrage opportunities offered by more open migration policies.
Original languageEnglish
PublisherUWA Business School
Publication statusPublished - 2019

Publication series

NameEconomics Discussion Papers
No.19
Volume19

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