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Implications of Automation for Global Migration

Author

Listed:
  • Yixiao ZHOU

    (Crawford School of Public Policy, Australian National University)

  • Rod TYERS

    (Business School, University of Western Australia; Research School of Economics and Centre for Applied Macroeconomic Analysis (CAMA), Australian National University)

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.

Suggested Citation

  • Yixiao ZHOU & Rod TYERS, 2019. "Implications of Automation for Global Migration," Economics Discussion / Working Papers 19-19, The University of Western Australia, Department of Economics.
    • Handle: RePEc:uwa:wpaper:19-19
    Note: MD5 = 1594688c93cffb4e8cd09f9dc4b93e88
    as

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    File URL: https://ecompapers.biz.uwa.edu.au/paper/PDF%20of%20Discussion%20Papers/2019/DP%2019.19_Zhou%20and%20Tyers.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Automation; demographic change; migration incentives; labor markets and economic growth;

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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