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Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data

Listed author(s):
  • John M. Abowd
  • Kevin L. McKinney
  • Nellie L. Zhao

Using earnings data from the U.S. Census Bureau, this paper analyzes the role of the employer in explaining the rise in earnings inequality in the United States. We first establish a consistent frame of analysis appropriate for administrative data used to study earnings inequality. We show that the trends in earnings inequality in the administrative data from the Longitudinal Employer-Household Dynamics Program are inconsistent with other data sources when we do not correct for the presence of misused SSNs. After this correction to the worker frame, we analyze how the earnings distribution has changed in the last decade. We present a decomposition of the year-to-year changes in the earnings distribution from 2004-2013. Even when simplifying these flows to movements between the bottom 20%, the middle 60%, and the top 20% of the earnings distribution, about 20.5 million workers undergo a transition each year. Another 19.9 million move between employment and non-employment. To understand the role of the firm in these transitions, we estimate a model for log earnings with additive fixed worker and firm effects using all jobs held by eligible workers from 2004-2013. We construct a composite log earnings firm component across all jobs for a worker in a given year and a non-firm component. We also construct a skill-type index. We show that, while the difference between working at a low- or middle-paying firm are relatively small, the gains from working at a top-paying firm are large. Specifically, the benefits of working for a high-paying firm are not only realized today, through higher earnings paid to the worker, but also persist through an increase in the probability of upward mobility. High-paying firms facilitate moving workers to the top of the earnings distribution and keeping them there.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 23224.

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Date of creation: Mar 2017
Handle: RePEc:nbr:nberwo:23224
Note: LS
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  1. Barry T. Hirsch & Muhammad M. Husain & John V. Winters, 2016. "Multiple job holding, local labor markets, and the business cycle," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-29, December.
  2. Michael Baker & Gary Solon, 2003. "Earnings Dynamics and Inequality among Canadian Men, 1976-1992: Evidence from Longitudinal Income Tax Records," Journal of Labor Economics, University of Chicago Press, vol. 21(2), pages 267-288, April.
  3. Abowd, John M. & Vilhuber, Lars, 2011. "National estimates of gross employment and job flows from the Quarterly Workforce Indicators with demographic and industry detail," Journal of Econometrics, Elsevier, vol. 161(1), pages 82-99, March.
  4. John M. Abowd & Bryce E. Stephens & Lars Vilhuber & Fredrik Andersson & Kevin L. McKinney & Marc Roemer & Simon Woodcock, 2009. "The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators," NBER Chapters,in: Producer Dynamics: New Evidence from Micro Data, pages 149-230 National Bureau of Economic Research, Inc.
  5. Levy, Frank & Murnane, Richard J, 1992. "U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations," Journal of Economic Literature, American Economic Association, vol. 30(3), pages 1333-1381, September.
  6. J. David Brown & Julie L. Hotchkiss & Myriam Quispe-Agnoli, 2013. "Does Employing Undocumented Workers Give Firms A Competitive Advantage?," Journal of Regional Science, Wiley Blackwell, vol. 53(1), pages 158-170, 02.
  7. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, February.
  8. Wojciech Kopczuk & Emmanuel Saez & Jae Song, 2010. "Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937," The Quarterly Journal of Economics, Oxford University Press, vol. 125(1), pages 91-128.
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