In this paper we estimate intergenerational earnings mobility models using quantile regressions. Quantile regression is a less restrictive estimation approach than more commonly used methods such as ordinary least squares and instrumental variables, which only estimate the mean effects of intergenerational earnings correlation. Further, we investigate the role of education as an intergenerational transmission mechanism for earnings. We find that the intergenerational earnings correlation is greater at the bottom of the son's conditional earnings distribution than at the top, and that controlling for son's education reduces the intergenerational earnings correlation. We also find that education is relatively more valuable at the bottom of the conditional earnings distribution and thus tends to compress the distribution.

Eric R. Eide is an assistant professor of economics at Brigham Young University and Mark H. Sho-walter is an associate professor of economics at Brigham Young University. They thank Chris Carroll, Lynn A. Karoly, Clayne Pope, and an anonymous referee for helpful comments. Bengte Evenson and Jane Partridge provided outstanding research assistance. This research was supported by a grant from the American Educational Research Association, which received funds for its AERA Grants Program from the National Science Foundation and the National Center for Education Statistics (U.S. Department of Education) under NSF Grant #RED-9452861. Opinions are those of the authors and not necessarily those of the granting agencies. Support was also received from the College of Family, Home, and Social Sciences at Brigham Young University. The data used in this article can be obtained beginning September 1999 through August 2002 from Eric R. Eide, Department of Economics, Brigham Young University, Provo, Utah 84602.

© 2002 by the Board of Regents of the University of Wisconsin System

US ISSN 0022-166X

Return to JHR Home Page