High Technology Agglomeration and Gender Inequalities

The high-tech boom of the last two decades overlapped with increasing wage inequalities between men and women in the United States. The extraordinary growth of high-tech industries increased the demand for college-educated workers, thus pushing up their wages. However, these industries tended to employ mainly skilled men, so similarly qualified women may have been left out of the employment and wage benefits associated with that extraordinary growth. This paper illuminates the degree to which gender inequalities in the United States emanate from the spatial concentration and labor demand characteristics of high-tech firms. The predominant model in the literature analyzing gender wage inequalities is the human capital model which argues that differences in wages (in the context of perfect competition) are explained by differences in human capital variables (e.g., education and experience) and the relative treatment of women by employers (e.g., discrimination usually measured by the error term). Not only are gender-specific factors a main culprit for the wage gap, but, as noted (1993), so is the wage structure—the array of prices set for various labor market skills (both observed and unobserved) determined by the interaction of supply and demand and the rents received for employment in particular sectors of the economy. Increases in wage inequalities among men in the 1980s were mainly explained by the increase in the returns to skills resulting from an increase in the demand for but abrupt slowdown in the supply of skilled men (Juhn et al. 1993). To the extent that this trend 2 reflects rising returns to skills and employment in high-wage sectors, it could be expected to disadvantage women as a group relative to men. (1997) found that improvements in women's human capital compensated for factors that affected women in a negative way during this period. A slowing convergence in the gender wage gap characterized the 1990s compared to the 1980s (Blau and Kahn 2004). Why? Using Juhn et al.'s (1993) decomposition technique, Blau and Khan (2004) find that the " unexplained " portion of the regression analysis fully accounts for the slowdown in wage convergence in the 1990s. The unexplained portion could be a proxy for several factors, including a large reduction in demand for female labor, which may help explain why the difference between women's and men's wages was greater in the 1990s than the 1980s. (2005) compare wage inequalities within the upper-tail wage group (90 th to 50 th percentiles) …