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Skill-Based Labor Market Polarization in the Age of AI: A Comparative Analysis of India and the United States

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  • Venkat Ram Reddy Ganuthula
  • Krishna Kumar Balaraman

Abstract

This paper examines labor market polarization through a comparative analysis of skill-based employment and wage distributions in India and the United States during 2018-2023, with particular attention to differential automation risks and AI preparedness. Using detailed occupation-level data, automation risk metrics, and a series of statistical tests including wage premium analysis, employment share tests, and wage-employment regressions, we document significant structural differences in labor markets between developing and developed economies. Our analysis yields four key findings. First, we find statistically significant differences in employment distribution patterns, with India showing disproportionate concentration in low-skill employment compared to the US, particularly in occupations with high automation risk. Second, regression analysis reveals that wage premiums differ systematically between the two countries, with significantly larger skill-based wage gaps in India. Third, we find robust evidence of a negative relationship between employment size and wages, suggesting stronger labor supply effects in developing economies. Fourth, analysis of occupation-specific automation risk reveals that developing economies face a "double vulnerability" - concentration of employment in both low-skill occupations and jobs with higher automation potential, complicated by lower AI preparedness scores. These findings provide novel empirical evidence on how development stages influence labor market polarization patterns and carry important implications for skill development and technology adoption policies in developing economies. Our results suggest that traditional approaches to labor market development may need significant modification to account for the differential impacts of AI across development stages.

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  • Venkat Ram Reddy Ganuthula & Krishna Kumar Balaraman, 2025. "Skill-Based Labor Market Polarization in the Age of AI: A Comparative Analysis of India and the United States," Papers 2501.15809, arXiv.org, revised Feb 2025.
    • Handle: RePEc:arx:papers:2501.15809
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    1. David Autor & David Dorn & Gordon Hanson & Kaveh Majlesi, 2020. "Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure," American Economic Review, American Economic Association, vol. 110(10), pages 3139-3183, October.
    2. Korinek, Anton & Stiglitz, Joseph, 2021. "Artificial Intelligence, Globalization, and Strategies for Economic Development," CEPR Discussion Papers 15772, C.E.P.R. Discussion Papers.
    3. Jorge Alvarez & Felipe Benguria & Niklas Engbom & Christian Moser, 2018. "Firms and the Decline in Earnings Inequality in Brazil," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(1), pages 149-189, January.
    4. Daron Acemoglu & Pascual Restrepo, 2022. "Tasks, Automation, and the Rise in U.S. Wage Inequality," Econometrica, Econometric Society, vol. 90(5), pages 1973-2016, September.
    5. George Psacharopoulos & Harry Anthony Patrinos, 2018. "Returns to investment in education: a decennial review of the global literature," Education Economics, Taylor & Francis Journals, vol. 26(5), pages 445-458, September.
    6. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    7. Juan C. Botero & Simeon Djankov & Rafael La Porta & Florencio Lopez-de-Silanes & Andrei Shleifer, 2004. "The Regulation of Labor," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(4), pages 1339-1382.
    8. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    9. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    10. David Card & Francis Kramarz & Thomas Lemieux, 1999. "Changes in the Relative Structure of Wages and Employment: A Comparison of the United States, Canada, and France," Canadian Journal of Economics, Canadian Economics Association, vol. 32(4), pages 843-877, August.
    11. Diego Comin & Martí Mestieri, 2018. "If Technology Has Arrived Everywhere, Why Has Income Diverged?," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(3), pages 137-178, July.
    12. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    13. Pinelopi Koujianou Goldberg & Nina Pavcnik, 2007. "Distributional Effects of Globalization in Developing Countries," Journal of Economic Literature, American Economic Association, vol. 45(1), pages 39-82, March.
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