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Labor Market Power Across Cities

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Abstract

Workers in larger cities are paid higher wages. The city-size wage premium may reflect the productivity gains from agglomeration or sorting of more productive workers in densely populated areas. However, local labor markets in large cities have more firms and are expected to be more competitive, which could also generate part of the urban earnings premium. I quantify the importance of this channel with rich administrative data for Spain using a spatial equilibrium model to guide the empirical strategy. To address the identification challenge posed by labor market power and wages moving endogenously with unobserved local productivity shocks, I first control for firms’ revenues per worker and for time trends that are heterogeneous across local labor markets. I then develop a new instrumental variable that leverages quasi-experimental variation in monopsony power stemming from changes over time in the size of local public firms. I conclude that 20–30% of the city-size wage premium and 6–15% of the employment gap between small and large cities can be attributed to differences in labor market power across locations.

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  • Claudio Luccioletti, 2022. "Labor Market Power Across Cities," Working Papers wp2022_2214, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2022_2214
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    1. Bernard, Andrew B. & Bradford Jensen, J., 1999. "Exceptional exporter performance: cause, effect, or both?," Journal of International Economics, Elsevier, vol. 47(1), pages 1-25, February.
    2. Steven Berry & Martin Gaynor & Fiona Scott Morton, 2019. "Do Increasing Markups Matter? Lessons from Empirical Industrial Organization," Journal of Economic Perspectives, American Economic Association, vol. 33(3), pages 44-68, Summer.
    3. Kneip, Alois & Sickles, Robin C. & Song, Wonho, 2012. "A New Panel Data Treatment For Heterogeneity In Time Trends," Econometric Theory, Cambridge University Press, vol. 28(3), pages 590-628, June.
    4. Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2011. "The identification of agglomeration economies," Journal of Economic Geography, Oxford University Press, vol. 11(2), pages 253-266, March.
    5. Ben Lipsius, 2018. "Labor Market Concentration does not Explain the Falling Labor Share," 2018 Papers pli1202, Job Market Papers.
    6. Bada, Oualid & Liebl, Dominik, 2014. "phtt: Panel Data Analysis with Heterogeneous Time Trends in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i06).
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    More about this item

    Keywords

    Labor market power; city sizes; wage premium.;
    All these keywords.

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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