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Monopsony in Online Labor Markets

Author

Listed:
  • Arindrajit Dube
  • Jeff Jacobs
  • Suresh Naidu
  • Siddharth Suri

Abstract

On-demand labor platforms make up a large part of the “gig economy.” We quantify the extent of monopsony power in one of the largest on-demand labor platforms, Amazon Mechanical Turk (MTurk), by measuring the elasticity of labor supply facing the requester (employer) using both observational and experimental variation in wages. We isolate plausibly exogenous variation in rewards using a double-machine-learning estimator applied to a large dataset of scraped MTurk tasks. We also re-analyze data from 5 MTurk experiments that randomized payments to obtain corresponding experimental estimates. Both approaches yield uniformly low labor supply elasticities, around 0.1, with little heterogeneity.

Suggested Citation

  • Arindrajit Dube & Jeff Jacobs & Suresh Naidu & Siddharth Suri, 2018. "Monopsony in Online Labor Markets," NBER Working Papers 24416, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24416
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    References listed on IDEAS

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    1. David Card & Ana Rute Cardoso & Joerg Heining & Patrick Kline, 2018. "Firms and Labor Market Inequality: Evidence and Some Theory," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 13-70.
    2. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    3. Doerrenberg, Philipp & Duncan, Denvil & Löffler, Max, 2023. "Asymmetric labor-supply responses to wage changes: Experimental evidence from an online labor market," Labour Economics, Elsevier, vol. 81(C).
    4. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    5. Douglas O. Staiger & Joanne Spetz & Ciaran S. Phibbs, 2010. "Is There Monopsony in the Labor Market? Evidence from a Natural Experiment," Journal of Labor Economics, University of Chicago Press, vol. 28(2), pages 211-236, April.
    6. Fosgerau, Mogens & Melo, Emerson & Shum, Matt, 2017. "Discrete Choice and Rational Inattention: a General Equivalence Result�," MPRA Paper 76605, University Library of Munich, Germany.
    7. 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.
    8. Lawrence F. Katz & Alan B. Krueger, 2016. "The Rise and Nature of Alternative Work Arrangements in the United States, 1995-2015," Working Papers 603, Princeton University, Department of Economics, Industrial Relations Section..
    9. Peter Kuhn, 2004. "Is monopsony the right way to model labor markets? a review of Alan Manning's monopsony in motion," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 11(3), pages 369-378.
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    More about this item

    JEL classification:

    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets

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