David N. Beede

Women in STEM: A Gender Gap to Innovation

Our science, technology, engineering and math (STEM) workforce is crucial to America’s innovative capacity and global competitiveness. Yet women are vastly underrepresented in STEM jobs and among STEM degree holders despite making up nearly half of the U.S. workforce and half of the college-educated workforce. That leaves an untapped opportunity to expand STEM employment in the United States, even as there is wide agreement that the nation must do more to improve its competitiveness.Although women fill close to half of all jobs in the U.S. economy, they hold less than 25 percent of STEM jobs. This has been the case throughout the past decade, even as college-educated women have increased their share of the overall workforce.Women with STEM jobs earned 33 percent more than comparable women in non-STEM jobs – considerably higher than the STEM premium for men. As a result, the gender wage gap is smaller in STEM jobs than in non-STEM jobs.Women hold a disproportionately low share of STEM undergraduate degrees, particularly in engineering.Women with a STEM degree are less likely than their male counterparts to work in a STEM occupation; they are more likely to work in education or healthcare.There are many possible factors contributing to the discrepancy of women and men in STEM jobs, including: a lack of female role models, gender stereotyping, and less family-friendly flexibility in the STEM fields. Regardless of the causes, the findings of this report provide evidence of a need to encourage and support women in STEM.

Education Supports Racial and Ethnic Equality in STEM

Science, technology, engineering, and math (STEM) workers are essential to American innovation and competitiveness in an increasingly dynamic and global marketplace. In this report, we examine demographic disparities in STEM education and find that educational attainment may affect equality of opportunity in these critical, high-quality jobs of the future.We find that regardless of race and Hispanic origin, higher college graduation rates are associated with higher shares of workers with STEM jobs. But non-Hispanic Whites and Asians are much more likely than other minority groups to have a bachelor’s degree. Other key findings of this report include: Non-Hispanic Whites comprise the largest group of STEM workers, accounting for about seven out of ten STEM worker, which aligns closely with their share of the overall workforce; Non-Hispanic Asians are most likely (42 percent) to graduate college with a STEM degree, while the propensities of other groups are fairly similar (17-22 percent); half of all non-Hispanic Asian workers with STEM degrees have STEM jobs, compared to 30% of Hispanics and non-Hispanic Black and American Indian and Alaska Native workers; one in five STEM workers is foreign-born, of which 63 percent come from Asia; STEM workers in all demographic groups, including the foreign-born, earn more than their non-STEM counterparts. Hispanics and non-Hispanic Blacks receive a significantly larger STEM premium than do non-Hispanic Whites.

Information Technology's Impact on Firm Structure: A Cross-Industry Analysis

Since the 1970s, economists have speculated on the effects of the proliferation of new computer and communications capabilities on business structure and performance. The present analysis explores information technologys (IT)relationship to employment and firm structure by examining how IT affects the relative size of employment at auxiliary units. The analysis treats auxiliary units--establishments where employees provide support services (mainly administrative) to production establishments--as a proxy for the highest administrative levels of the organizational hierarchy. Changes in the relative size of auxiliary employment give a broad indication of IT-related changes in firm structure. Statistical analyses of 46 industries show large variations across industries in the size, sign, and statistical significance of the elasticities of auxiliary unit employment shares with respect to IT capital stock shares. We find no economy-wide trends associated with IT. There is too much variation among industries to rely on estimates obtained from pooling industry data. For the most part, sectorial trends are scarce. Only in the transportation sector do the sign and statistical significance suggest that IT related changes are similar. Ultimately, the enormous variation revealed by our results suggests that one cannot make economy-wide generalizations about the effects of IT. Nevertheless, our results, combined with other evidence,suggest that economies of scale--gained from using IT to reduce coordination and monitoring costs--influence firm size and structure. One reason why the effects of IT are so different across industries is variation in the firm size distribution across industries prior to the IT revolution: 1) For industries with a predominance of small firms, IT-related economies of scale may encourage growth in firm size and lead to an increase in the relative size of centralized back office establishments across the industry. This appears to have occurred in the retail trade industry. 2) In some industries where large firms predominate, IT may induce greater efficiency in back-office jobs, enabling firms to reduce back office employment relative to total employment. This appears to have occurred in some of the transportation industries. 3) In industries where IT primarily substitutes for production workers, auxiliary unit employment share is likely to rise because central administration office employment tends to change less than proportionately in response to changes in overall employment. This appears to have occurred in the primary metals industry.

Regulatory Rules and Estimating Economic Growth: Two Perspectives on Expensing Employee Stock Options1

Government economic statistics generally diverge from statistics based on private sector or regulatory agency data, and they are subject to being updated over time as more tax and administrative data become available. A deeper knowledge of the sources of statistical agency data and the adjustments made to those can help data users avoid confusion.