The authors would like to thank Charlie Brown, David Card, Erica Groshen, participants of the labor lunch at the University of California-Berkeley, and two anonymous Industrial Relations referees for their helpful comments. This document reports the results of research and analysis undertaken by the U.S. Census Bureau staff. It has undergone a Census Bureau review more limited in scope than that given to official Census Bureau publications. This research is a part of the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) Program and is funded in part by the Alfred P. Sloan Foundation. The views expressed on statistical, methodological, and technical issues are those of the authors and not necessarily those of the Office of the Comptroller of the Currency or of the U.S. Census Bureau, its program sponsors, or its data providers. Some of the data used in this research are confidential data from the LEHD Program. The U.S. Census Bureau supports external researchers' use of these data through the Research Data Centers (http://www.ces.census.gov). For questions regarding the data, please contact the U.S. Census Bureau, LEHD Program, Room 5K168F, 4600 Silver Hill Road, Suitland, Maryland 20746, USA (http://lehd.did.census.gov).
Decomposing the Sources of Earnings Inequality: Assessing the Role of Reallocation
Version of Record online: 16 SEP 2012
© 2012 Regents of the University of California
Industrial Relations: A Journal of Economy and Society
Volume 51, Issue 4, pages 779–810, October 2012
How to Cite
Andersson, F., Davis, E. E., Freedman, M. L., Lane, J. I., Mccall, B. P. and sandusky, K. (2012), Decomposing the Sources of Earnings Inequality: Assessing the Role of Reallocation. Industrial Relations: A Journal of Economy and Society, 51: 779–810. doi: 10.1111/j.1468-232X.2012.00697.x
- Issue online: 16 SEP 2012
- Version of Record online: 16 SEP 2012
This study exploits longitudinal employer–employee matched data from the U.S. Census Bureau to investigate the contribution of worker and firm reallocation to changes in earnings inequality within and across industries between 1992 and 2003. We find that factors that cannot be measured using standard cross-sectional data, including the entry and exit of firms and the sorting of workers across firms, are important sources of changes in earnings distributions over time. Our results also suggest that the dynamics driving changes in earnings inequality are heterogeneous across industries.