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Augmenting the Human Capital Earnings Equation with Measures of Where People Work

In: Firms and the Distribution of Income: The Roles of Productivity and Luck

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  • Erling Barth
  • James Davis
  • Richard B. Freeman

Abstract

We augment standard ln earnings equations with variables reflecting unmeasured attributes of workers and measured and unmeasured attributes of their employer. Using panel employee-establishment data for US manufacturing we find that the observable employer characteristics that most impact earnings are: number of workers, education of co-workers, capital equipment per worker, industry in which the establishment produces, and R&D intensity of the firm. Employer fixed effects also contribute to the variance of ln earnings, though substantially less than individual fixed effects. In addition to accounting for some of the variance in earnings, the observed and unobserved measures of employers mediate the estimated effects of individual characteristics on earnings and increasing earnings inequality through the sorting of workers among establishments.
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Suggested Citation

  • Erling Barth & James Davis & Richard B. Freeman, 2015. "Augmenting the Human Capital Earnings Equation with Measures of Where People Work," NBER Chapters, in: Firms and the Distribution of Income: The Roles of Productivity and Luck, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:13716
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Augmenting the Human Capital Earnings Equation with Measures of Where People Work
      by maximorossi in NEP-LTV blog on 2016-09-06 01:17:09

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    Cited by:

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    2. Ata Can Bertay & Jose Gabo Carreno & Harry Huizinga & Burak Uras & Nathanael Vellekoop, 2022. "Technological Change and the Finance Wage Premium," Working Papers tecipa-738, University of Toronto, Department of Economics.
    3. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2023. "Functional Data Inference in a Parametric Quantile Model applied to Lifetime Income Curves," Working papers 2023rwp-211, Yonsei University, Yonsei Economics Research Institute.
    4. Barth, Erling & Davis, James C. & Freeman, Richard B. & McElheran, Kristina, 2023. "Twisting the demand curve: Digitalization and the older workforce," Journal of Econometrics, Elsevier, vol. 233(2), pages 443-467.
    5. Knutsson, Polina, 2018. "Sorting on Unobserved Skills into New Firms," Working Papers 2018:38, Lund University, Department of Economics.
    6. Chiara Criscuolo & Alexander Hijzen & Cyrille Schwellnus & Erling Barth & Wen-Hao Chen & Richard Fabling & Priscilla Fialho & Balazs Stadler & Richard Upward & Wouter Zwysen & Katarzyna Grabska-Romago, 2020. "Workforce composition, productivity and pay: the role of firms in wage inequality," OECD Economics Department Working Papers 1603, OECD Publishing.
    7. Giuseppe Berlingieri & Sara Calligaris & Chiara Criscuolo, 2018. "The Productivity-Wage Premium: Does Size Still Matter in a Service Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 328-333, May.
    8. Nathan Goldschlag & Ron Jarmin & Julia Lane & Nikolas Zolas, 2019. "Research Experience as Human Capital in New Business Outcomes," NBER Chapters, in: Measuring and Accounting for Innovation in the Twenty-First Century, pages 229-254, National Bureau of Economic Research, Inc.
    9. Lachowska, Marta & Mas, Alexandre & Woodbury, Stephen A., 2022. "How reliable are administrative reports of paid work hours?," Labour Economics, Elsevier, vol. 75(C).
    10. John Haltiwanger & Henry Hyatt & Erika McEntarfer, 2018. "Who Moves Up the Job Ladder?," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 301-336.
    11. Freund, L. B., 2022. "Superstar Teams: The Micro Origins and Macro Implications of Coworker Complementarities," Cambridge Working Papers in Economics 2276, Faculty of Economics, University of Cambridge.
    12. Molina-Domene, Maria, 2018. "Specialization matters in the firm size-wage gap," LSE Research Online Documents on Economics 88696, London School of Economics and Political Science, LSE Library.
    13. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    14. Jensen, Bjarne S. & Pedersen, Peder J. & Guest, Ross, 2022. "Demographic Changes, Labor Supplies, Labor Complementarities, Calendar Annual Wages of Age Groups, and Cohort Life Wage Incomes," IZA Discussion Papers 15127, Institute of Labor Economics (IZA).
    15. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2022. "Parametric Conditional Mean Inference With Functional Data Applied To Lifetime Income Curves," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(1), pages 391-456, February.
    16. Maria Molina-Domene, 2018. "Specialization matters in the firm size-wage gap," CEP Discussion Papers dp1545, Centre for Economic Performance, LSE.

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    More about this item

    JEL classification:

    • J0 - Labor and Demographic Economics - - General
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General

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