| Eric Eide
Brigham Young University
The effect of education and family background on earnings inequality among young workers
FINAL REPORT:
Study 1: 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 the more commonly used OLS/IV methodology which only estimates 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.
Study 2: The Effect of School Quality on Student Performance: A Quantile Regression Approach.
We use quantile regressions to estimate whether the relation between school quality and performance on standardized tests differs at different points in the conditional distribution of "test score gains". Previous work has focused only on average school quality effects. This paper finds that there are important differences in how various school inputs affect student performance as measured by standardized test scores. For example, lengthening the school year tends to help the best students while not doing much for lower-performing students. On the other hand, per pupil expenditures tend to help the slower students while not affecting the brightest students. These results contrast with much previous statistical evidence that says such variables have little effect on students. The difference comes because past research has focused on how the average student is affected while our research methodology allows for more in depth analysis.
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