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The Roots of Global Wage Gaps: Evidence from Randomized Processing of U.S. Visas

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  • Michael Clemens

Abstract

This study uses a unique natural experiment to test a simple model of international differences in workers’ wages and productivity. Large differences in wages across countries could arise from several sources. These include barriers to trade in outputs, differences in technology, differences in workers, or differences in the other factors of production accessible in different countries. To measure the relative importance of these sources in one setting, this study exploits the randomized processing of U.S. visas for a group of Indian workers who produce software within a single multinational firm. In this setting, international barriers to trade in outputs, barriers to technology transfer, and all observable or unobservable differences between workers are extremely low. The results indicate that location outside of India causes a sixfold increase in the wages of the same worker using the same technology to produce a highly tradable good. Under plausible assumptions about competition in the industry, this suggests that country-of-work by itself is responsible—in this industry—for roughly three-quarters of the gap in productivity between workers in India and workers in the richest countries. These findings have implications for open questions in labor, growth, international, and development economics.

Suggested Citation

  • Michael Clemens, 2010. "The Roots of Global Wage Gaps: Evidence from Randomized Processing of U.S. Visas," Working Papers 212, Center for Global Development.
  • Handle: RePEc:cgd:wpaper:212
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    File URL: http://www.cgdev.org/content/publications/detail/1424188/
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    Cited by:

    1. Sari Pekkala Kerr & William R. Kerr & William F. Lincoln, 2015. "Skilled Immigration and the Employment Structures of US Firms," Journal of Labor Economics, University of Chicago Press, vol. 33(S1), pages 147-186.
    2. de Brauw, Alan & Mueller, Valerie & Woldehanna, Tassew, 2011. "Insurance motives to remit: Evidence from a matched sample of Ethiopian internal migrants," ESSP working papers 25, International Food Policy Research Institute (IFPRI).
    3. Gordon H. Hanson & Matthew J. Slaughter, 2017. "High-Skilled Immigration and the Rise of STEM Occupations in US Employment," NBER Chapters, in: Education, Skills, and Technical Change: Implications for Future US GDP Growth, pages 465-494, National Bureau of Economic Research, Inc.
    4. Mobarak, Ahmed Mushfiq & Sharif, Iffath & Shrestha, Maheshwor, 2021. "Returns to International Migration: Evidence from a Bangladesh-Malaysia Visa Lottery," IZA Discussion Papers 14232, Institute of Labor Economics (IZA).
    5. Cynthia Kinnan & Shing-Yi Wang & Yongxiang Wang, 2015. "Relaxing Migration Constraints for Rural Households," Working Papers id:7047, eSocialSciences.
    6. Ariel BenYishay, 2012. "Informational Barriers to Credit for Migrants: Evidence from Guatemala," Economic Development and Cultural Change, University of Chicago Press, vol. 60(3), pages 535-570.
    7. Andrew Leigh, 2022. "Engaged Egalitarianism: Why the Australian Recovery Must Prioritise Openness," Economic Papers, The Economic Society of Australia, vol. 41(2), pages 99-109, June.
    8. John Gibson & David McKenzie & Halahingano Rohorua, 2014. "Development Impacts of Seasonal and Temporary Migration: A Review of Evidence from the Pacific and Southeast Asia," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 1(1), pages 18-32, January.
    9. Gharad Bryan & Shyamal Chowdhury & A. Mushfiq Mobarak, 2011. "Seasonal Migration and Risk Aversion," Working Papers id:4650, eSocialSciences.
    10. John Gibson & David McKenzie, 2012. "The Economic Consequences of ‘Brain Drain’ of the Best and Brightest: Microeconomic Evidence from Five Countries," Economic Journal, Royal Economic Society, vol. 122(560), pages 339-375, May.
    11. John Gibson & David McKenzie & Halahingano Rohorua & Steven Stillman, 2018. "The Long-term Impacts of International Migration: Evidence from a Lottery," The World Bank Economic Review, World Bank, vol. 32(1), pages 127-147.
    12. Gibson, John & McKenzie, David, 2014. "Scientific mobility and knowledge networks in high emigration countries: Evidence from the Pacific," Research Policy, Elsevier, vol. 43(9), pages 1486-1495.
    13. Giovanni Peri & Kevin Shih & Chad Sparber, 2015. "Foreign and Native Skilled Workers: What Can We Learn from H-1B Lotteries?," NBER Working Papers 21175, National Bureau of Economic Research, Inc.
    14. Gordon H. Hanson & Chen Liu, 2017. "High-Skilled Immigration and the Comparative Advantage of Foreign-Born Workers across US Occupations," NBER Chapters, in: High-Skilled Migration to the United States and Its Economic Consequences, pages 7-40, National Bureau of Economic Research, Inc.
    15. Michael A. Clemens, 2011. "Economics and Emigration: Trillion-Dollar Bills on the Sidewalk?," Journal of Economic Perspectives, American Economic Association, vol. 25(3), pages 83-106, Summer.
    16. Michael A. Clemens, 2013. "Why Do Programmers Earn More in Houston Than Hyderabad? Evidence from Randomized Processing of US Visas," American Economic Review, American Economic Association, vol. 103(3), pages 198-202, May.
    17. David McKenzie, 2012. "Learning about migration through experiments," RF Berlin - CReAM Discussion Paper Series 1207, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    18. de Brauw, Alan & Mueller, Valerie & Woldehanna, Tassew, 2013. "Motives to Remit: Evidence from Tracked Internal Migrants in Ethiopia," World Development, Elsevier, vol. 50(C), pages 13-23.

    More about this item

    Keywords

    growth; economic development; wealth of nations; productivity; migration; lottery; information technology; wage differences; poverty; income distribution; human capital; spatial differences; agglomeration; price equivalent; tariff equivalent; labor mobility; location; high tech; software; technology;
    All these keywords.

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers

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