Authors: Sijiao Xie*, Arizona State University
Topics: Migration, Population Geography, Gender
Keywords: highly skilled migration, migration, gender, STEM, employment
Session Type: Virtual Paper
Presentation File: No File Uploaded
While there has been much discussion of the broader impacts of skilled migration and the behaviors of skilled migrants, gender rarely enters into these discussions. This is notable as 24% of STEM workers are women and women in STEM earn 14% less on average than men. Since STEM occupations are highly-selective in terms of gender, skill level and nativity, my research examines the relationship between occupational selection in STEM fields and the wage of STEM workers in different ethnic and gender groups across US regions. Using ACS PUMS datasets and Oaxaca-Blinder decomposition methods, I analyze the wage of STEM workers across different gender and ethnic background and identifies factors affecting their wage; this study contributes to the understanding on how the gender wage gap, often found in other non-STEM fields, is mediated or persisted in the highly selective STEM fields, and examine if there is a regional pattern to such mitigating/persisting effects.