The relationship between education and earnings is a long-analyzed topic of study. Generally, there is a strong belief that achievement of higher levels of education is a well established path to better jobs and better earnings.1 This report provides one view of the economic value of educational attainment by producing an estimate of the amount of money a person might earn over the course of their working life, given their level of education. These estimates are “synthetic,” that is, they are not the actual dollars people earned over the complete working life of the person (which would require us to have retrospective earnings data for the 40 years of their work-life). Instead, they are estimated using data from a one point-in-time cross-sectional survey. Median annual earnings estimates are computed for the point in time of the survey for all ages (5-year age groups are used), education, gender, and race/ethnicity groups. The age group-specific medians are then summed across the category of interest (say, Black females with a Master’s degree) to construct expected lifetime earnings of that group if all earnings patterns observed in the cross section were to remain unchanged.
In this report, the Synthetic Work-life Earnings (SWE) estimates are first used to explore the basic relationship between education and earnings. The report then delves deeper into differences between race and gender groups with regard to this relationship. We also consider other factors that might influence earnings, such as citizenship, English-speaking ability, and geographic location.
The data for this research comes from the Multiyear American Community Survey (ACS) data file for the period 2006 to 2008. The ACS represents a part of the U.S. Census Bureau’s revised approach in how it conducts the federally-mandated decennial census of the population of the United States. The ACS is a large, monthly, national survey of the U.S. population that is sent to about a quarter million households each month in order to provide nationally-representative data on the equivalent of the full long-form content on a yearly basis (instead of once every 10 years). In order to provide estimates for very small pieces of geography and subpopulations, the Census Bureau takes sequential yearly files and combines and weights them to produce multiyear files with much larger samples. This analysis uses the multi-year file for the 2006 to 2008 period in order to provide sufficient characteristic detail for the analysis. We include residents from all 50 states plus the District of Columbia. All estimates are presented in 2008 dollars and represent the amount of money that might be expected to be earned over the course of a work-life from ages 25 to 64 for different gender and race/ethnicity groups.
An earlier Census Bureau report on this topic used data taken from the Current Population Survey (CPS).2 The methodology of that report was similar to that used in this report. However, because the 3-year dataset from the CPS is about one-tenth the size of the 3-year ACS dataset, this report allows detailed analysis of gender cross-classified by race/ethnicity groups. Additionally, this report uses more exact 5-year age intervals for all groups, whereas the CPS report relied on less exact 10-year age cohorts for race and gender estimates. Finally, the ACS data, because of its content scope allows for the investigation of factors such as language ability, which is not a part of the CPS data collection.
1 Card, David. 1998. “The Causal Effect of Education on Earnings” in: O. Ashenfelter & D. Card (Ed.), Handbook of Labor Economics, pp. 67–86.
2 Day, Jennifer Cheeseman and Eric C. Newburger. 2002. “The Big Payoff: Educational Attainment and Synthetic Estimates of Work-Life Earnings.” U.S. Census Bureau, Current Population Reports, P23–210. U.S. Census Bureau, Washington, DC.