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Workers in the crowd: the labor market impact of the online platform economy
[An evaluation of instrumental variable strategies for estimating the effects of catholic schooling]

Author

Listed:
  • Michele Cantarella
  • Chiara Strozzi

Abstract

We compare individuals engaged in online crowdwork against workers in traditional occupations from the United States and Europe, investigating the determinants of access into crowd employment and the nature of the deterioration of salary conditions and job quality characterizing these markets. We do so by matching responses from comparable working conditions surveys, and controlling for most individual and socio-economic characteristics affecting pay. We find that most differences in earnings are largely unexplained by the ability of individuals, and that labor in crowdwork is vastly under-utilized.

Suggested Citation

  • Michele Cantarella & Chiara Strozzi, 2021. "Workers in the crowd: the labor market impact of the online platform economy [An evaluation of instrumental variable strategies for estimating the effects of catholic schooling]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(6), pages 1429-1458.
    • Handle: RePEc:oup:indcch:v:30:y:2021:i:6:p:1429-1458.
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    1. Joni Hersch & Leslie S. Stratton, 2000. "Household Specialization and the Male Marriage Wage Premium," ILR Review, Cornell University, ILR School, vol. 54(1), pages 78-94, October.
    2. Alexander Bick, 2016. "The Quantitative Role Of Child Care For Female Labor Force Participation And Fertility," Journal of the European Economic Association, European Economic Association, vol. 14(3), pages 639-668, June.
    3. 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.
    4. Joshua Angrist & Victor Lavy, 2009. "The Effects of High Stakes High School Achievement Awards: Evidence from a Randomized Trial," American Economic Review, American Economic Association, vol. 99(4), pages 1384-1414, September.
    5. Schmitz, Hendrik & Westphal, Matthias, 2017. "Informal care and long-term labor market outcomes," Journal of Health Economics, Elsevier, vol. 56(C), pages 1-18.
    6. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 40(4), pages 791-821.
    7. Oecd, 2016. "New Forms of Work in the Digital Economy," OECD Digital Economy Papers 260, OECD Publishing.
    8. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    9. Barry T. Hirsch & David A. MacPherson, 2003. "Union Membership and Coverage Database from the Current Population Survey: Note," ILR Review, Cornell University, ILR School, vol. 56(2), pages 349-354, January.
    10. Sanderson, Eleanor & Windmeijer, Frank, 2016. "A weak instrument F-test in linear IV models with multiple endogenous variables," Journal of Econometrics, Elsevier, vol. 190(2), pages 212-221.
    11. Angrist, Joshua D & Krueger, Alan B, 1995. "Split-Sample Instrumental Variables Estimates of the Return to Schooling," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 225-235, April.
    12. Yongsung Chang & Sun-Bin Kim & Kyooho Kwon & Richard Rogerson, 2011. "Interpreting Labor Supply Regressions in a Model of Full- and Part-Time Work," American Economic Review, American Economic Association, vol. 101(3), pages 476-481, May.
    13. Adams-Prassl, Abigail, 2020. "The Gender Wage Gap on an Online Labour Market: The Cost of Interruptions," CEPR Discussion Papers 14294, C.E.P.R. Discussion Papers.
    14. Martin Kenney & Petri Rouvinen & Timo Seppälä & John Zysman, 2019. "Platforms and industrial change," Industry and Innovation, Taylor & Francis Journals, vol. 26(8), pages 871-879, September.
    15. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    16. Leigh, Andrew, 2010. "Informal care and labor market participation," Labour Economics, Elsevier, vol. 17(1), pages 140-149, January.
    17. Stephen G. Donald & Kevin Lang, 2007. "Inference with Difference-in-Differences and Other Panel Data," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 221-233, May.
    18. Card, David & Krueger, Alan B, 1992. "Does School Quality Matter? Returns to Education and the Characteristics of Public Schools in the United States," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 1-40, February.
    19. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    20. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    21. Hotchkiss, Julie L, 1991. "The Definition of Part-Time Employment: A Switching Regression Model with Unknown Sample Selection," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(4), pages 899-917, November.
    22. John F. Ermisch & Robert E. Wright, 1993. "Wage Offers and Full-Time and Part-Time Employment by British Women," Journal of Human Resources, University of Wisconsin Press, vol. 28(1), pages 111-133.
    23. Joshua D. Angrist & Alan B. Krueger, 1993. "Split Sample Instrumental Variables," Working Papers 699, Princeton University, Department of Economics, Industrial Relations Section..
    24. De Stefano, Valerio., 2016. "The rise of the "just-in-time workforce" : on-demand work, crowdwork and labour protection in the "gig-economy"," ILO Working Papers 994899823402676, International Labour Organization.
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    4. Li, Xue & Tan, Alexander Jun Hao & Wang, Xueqin & Yuen, Kum Fai, 2023. "Investigating gig workers’ commitment to crowdsourced logistics platforms: Fair employment and social exchange perspectives," Technology in Society, Elsevier, vol. 74(C).
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    7. Yunhao He & Marcus V. Goncalves, 2025. "Mapping Gender Pay Disparities in Chinese Finance: A Systematic Literature and Bibliometric Review," Administrative Sciences, MDPI, vol. 15(9), pages 1-40, September.

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