Association for Public Policy Analysis & Management

Women have made tremendous progress in math-intensive science, technology, engineering and mathematics (STEM) majors and occupations with one glaring exception:  computer science and information technology (Ceci, Ginther, Kahn & Williams 2014).  In computer science and information technology, women as a percentage of majors peaked in the 1980s and data indicates that they are more likely to work outside of computer science/IT fields compared with men if they have majored in those disciplines.  Our work will use the 1993-2013 waves of the Scientists and Engineers Statistical Data System (SESTAT) to examine the factors associated with women’s departure from computer science and information technology occupations.  SESTAT is a panel data set that follows individuals with STEM majors or those working in STEM occupations over time.  SESTAT collects detailed information on demographics, education, employer characteristics, reasons for job changes and job satisfaction.  Our analysis will estimate hazard models of the probability of leaving computer science and information technology careers as a function of job satisfaction and other covariates.