Racial Differences in Educational Pathway in the Making of Income Inequality: A Case of Washington State, USA

Friday, 20 July 2018: 15:45
Oral Presentation
Vivien CHEN, Education Research and Data Center, USA
Is college a worth investment for all? Does college return to education alleviate income inequality along racial and ethnic line? Recent years, research has found rising income inequality between race/ethnicity in the United States. A mounting scholarship on return to education has demonstrated that income disparity comes from college major- college graduates with degree in Science, Technology, Engineering, and Math (STEM) major earn relatively higher wage than other majors. The determination of college majors comes from not only educational opportunity, progress, and choices at college level, but also from high school preparation in transition to college. However, little is known whether racial/ethnic income inequality is attributable to the racial disparity in educational pathway from high school to college, in the selection into and persistence in college majors in a series of economic contexts. Understanding the trends of racial/ethnic income inequality through educational pathway in past decade impacted by the Great Recession (GR) is an important but unaddressed question.

This study analyzes the case of Washington State, which, in past few years, has experienced a rising demand for STEM human capital to meet the need from fast-growing high-technology industry. Using statewide longitudinal data system (WA SLDS), American Community Survey, as well as a state-sponsored-and-privately-run STEM program, I portray high school graduates’ educational pathway, through course-taking and college major to college degree completion, and their racial income disparity from 2008 through 2017 by three graduation cohorts - before-, during-, and post- GR. To estimate the net effect of racial educational pathways on income, I use fixed-effect and spatial autocorrelation models to control for selectivity from contextual factors from institution over space and time. Policy implications, echoing to the state policies related to educational equity and equality under the development of high-stake accountability, will be addressed. Data quality issues will also be discussed.