Women and Minorities in the IT Workforce

Women and Minorities in the IT Workforce Sharon G. Levin Department of Economics University of Missouri-St. Louis and Paula E. Stephan Department of Economics, Andrew Young School of Policy Studies Georgia State University

Why this study? • Low incidence in IT was initially motivated by concerns regarding “equity” • The interest heightened during the 1990s as the IT sector boomed and shortages of workers were perceived to exist • The increased participation of women and underrepresented minorities [WURM] was seen as one way by which the IT workforce could be grown

Why this study? • Much of the policy discussion focused on how the pipeline leading to careers in IT could be expanded making IT careers more attractive and accessible to WURM • Often focused on why WURM leave STEM fields while students • Studies related to recruitment, almost without exception, focused on pipeline issues related to recruiting WURM into degree programs in STEM; few examined retention after the career had begun

Why this study? • The present work is one of the few to examine the recruitment of college educated individuals without formal IT training into the IT workforce and how both recruitment and retention vary by gender and minority status • As we will see shortly, the importance of recruitment and retention in determining the size and diversity of the IT workforce is substantial

Data • The SESTAT Database is used: • College educated individuals living in the US in 1990 who had a degree in Science and Engineering, or • Individuals working in Science and Engineering occupations in 1993 who did not possess Science and Engineering degrees

SESTAT Shortcomings • The SESTAT definition of IT occupations fails to capture all jobs where IT work is occurring • SESTAT under-represents 4 groups of scientists and engineers in the US in 1995 and subsequent years • New immigrants with science and engineering (S&E) jobs who entered the US after 1990 and did not subsequently receive a degree in the US • College grads without S&E degrees who were not working in S&E occupations in 1993, but were in S&E occupations at a later date • Associate degree holders working in S&E • Individuals who lack a formal degree but are working in S&E

SESTAT Shortcomings • SESTAT excludes individuals without S&E training who began working in IT occupations after 1993 • Programming, both as a field of education and occupation, is not defined by SESTAT as being in S&E • Degrees awarded from business school are excluded from the definition of S&E fields regardless of their content

Defining IT training • Individuals are formally trained in IT if they received one or more degrees in • Computer/information sciences, computer science, computer system analysis • Information service and systems, other computer and information sciences • Computer and system engineering, electrical, electronics and communications engineering • Individuals were also considered formally trained in IT if they had minored or did a second major in computer/information sciences

Defining IT occupations • Individuals are in the IT workforce if they are employed as • Computer analysts or computer scientists (excluding system analysts) • Information system scientists and analysts, or other computer and information scientist • Computer engineers, software engineers, and post-secondary teachers in computer or mathematical sciences • Computer engineers, including both hardware and computer programmers

Descriptive Analysis

Multivariate Analysis

Conclusions • WURM have different recruitment and retention patterns in the IT workforce than do men and whites • These differences persist after controlling for family structure, age, citizenship status and field of training • URM are more likely than whites to work in non-IT occupations relative to IT occupations • This is not evident for women • There are substantial differences in the odds of working for men compared to women

Conclusions • In terms of recruitment, marriage and family play different roles for men and women • For men, marriage decreases the odds those without formal IT training work in IT rather than in other occupations • For men, marriage increases the odds they remain in the workforce

Conclusions • For women, marriage increases the odds that they will leave the workforce rather than work in IT or other occupations • Women with young children are less likely to work in IT than in other occupations, but more likely to leave the workforce. • Men with young children are also less likely to work in IT than in other occupations, but they are more likely to work in a non-IT occupation than to not work

Conclusions • In terms of retention, Women and African Americans have lower odds of retention than do white males. • For women, this holds for women with and without formal IT training. • For African Americans, this holds only for the IT-trained. Those who were not IT-trained who gained permanent status had lower odds of retention than those who still held temporary status.

Conclusions • Overall these results suggest that policies directed towards recruitment and retention will have different outcomes depending on the group in question • With regards to recruitment, underrepresented women, but not men, would more likely be in the IT workforce if initiatives such as on-site child care and flex-time were provided

Conclusions • With regards to retention, women and African-Americans would be more likely to respond to selected initiatives than would Hispanics and others. • One must also question the extent to which temporary residents chose IT occupations as a means (H1-B visas) by which to enter the US workforce

Women and Minorities in the IT Workforce