Factors Affecting the Transmission of Earnings across Generations: A Quantile Regression Approach

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 intergener...

Full description

Saved in:
Bibliographic Details
Published in:The Journal of human resources 1999-04, Vol.34 (2), p.253-267
Main Authors: Eide, Eric R., Showalter, Mark H.
Format: Article
Language:English
Subjects:
Comparative analysis
Compensation and benefits
Correlations
Datasets
Dependent variables
Earnings
Economic aspects
Education
Educational attainment
Effects
Families & family life
Family Characteristics
Family income
Fathers
Fathers and sons
Human resources
Income distribution
Income estimates
Least Squares Statistics
Mobility
Quantile regression
Regression analysis
Role of Education
Sons
Standard error
Studies
Variable coefficients
Variables
Wages
Wages & salaries
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0022-166X
1548-8004
DOI:10.2307/146345