IT Workforce Composition and Characteristics

Women are under represented in the Information Technology (IT) workforce. In the United States, although women make up about forty five percent of the overall labor force they make up only about thirty five percent of the IT workforce. (Information Technology Association of America 2003, p. 11). Within IT, women’s representation declines as one moves up to higher level occupations. While women are relatively more numerous among data entry keyers and computer operators, they are relatively less likely to be found in high level occupations like systems analysts and computer programmers.

The relatively low representation of women in IT fields parallels a broader pattern of gender differentials in other scientific and technical fields. In all science, technology, engineering and mathematics fields combined, women held 25.9 percent of jobs in 2003. Women’s representation varies widely by sub-fields, however: 65.8 percent of psychologists and 54.6 percent of social scientists are women, but only 10.4 percent of engineers, and 37.4 percent of natural scientists (Commission on Professionals in Science and Technology 2004, p. 2).

Over the course of the past 100 years there has been a dramatic change in women’s economic role. In 1900 only one in five adult women worked outside the home, and most of these were young and unmarried (Goldin 1990, ch. 1). Since then male and female labor force participation rates have tended to converge. Between 1900 and 1950 there was a gradual expansion of women’s labor force participation. After World War II the pace of change accelerated sharply as more married women entered the labor force. During the 1960s and early 1970s a series of legal changes significantly broadened protection of women’s rights ending essentially all forms of overt discrimination (Fuchs 1988, chs. 1-2; Long 2001, pp. 9-10). The removal of these barriers in combination with the availability of cheap and reliable birth control technology greatly facilitated the entry of women into higher education, and technical and professional positions (Goldin and Katz 2002).

Nevertheless, as the figures cited at the outset reveal, women’s participation in IT and other technical fields has not increased as rapidly as it has in less technical fields. And in striking contrast to the general trend toward increasing female participation in most areas of the workforce, women’s share of the IT workforce in the United States has actually declined over the past two decades. Any effort to explain gender differences in IT must begin with an understanding of how the number, characteristics and pay of women in IT have evolved over time, and across different sub-fields within IT. This chapter provides a foundation for this analysis by documenting recent changes in the number of women employed in IT, their demographic characteristics and relative pay.

A discussion of the gender composition and characteristics of the IT workforce must begin by clarifying what is meant by IT. This is difficult because IT encompasses a broad array of products and activities related to computing and communications in the modern economy (Freeman and Aspray 1999, pp. 29-31). Although many workers make use of IT in their jobs most studies agree that only those workers who are responsible for creating IT hardware and software should be included in the IT workforce, while those who are primarily users of these products should be excluded (In addition to Freeman and Aspray, see National Research Council 2001, pp. 44-54; Ellis and Lowell 1999, p. 1).

Whatever conceptual definition one adopts, however, its application is limited by the classification schemes used by agencies engaged in collecting data on different elements of the workforce. In what follows we will focus on those IT occupations that are enumerated in the Bureau of Labor Statistics’ Current Population Survey (CPS). The CPS data cover Computer Systems Analysts, Computer Programmers, Operations and Systems Researchers, Computer Operators, and Computer Operators Supervisors. These occupations constitute more or less what the National Research Council (2001, p. 48) has termed "Category 1" IT occupations: those involved with the creation of new products, services and applications. CPS data do not permit us to measure or describe the characteristics of the National Research Council’s "Category 2" occupations: those involved in the application, adaptation, configuration, support or implementation of IT products or services (National Research Council 2001, p. 49). Because occupational titles do not adequately capture the IT content of the support activities of many of the technicians and other occupations included in this group it is more difficult to adequately measure its size or demographic characteristics.

The rapid and sustained decline in the cost of computers over the past two decades has been a prominent factor in the reorganization of work in the United States. Between 1984, near the beginning of the personal computer era, and 2001 the quality-adjusted price of computers fell at an average annual rate of 16 percent, resulting in an 18-fold drop in price (US Department of Commerce; cited in Weil 2005, p. 263). As personal computers diffused into widespread use, mini-computers vanished from the market, and sales of large corporate mainframes languished. Shifting markets and the changing needs of users resulted in significant shifts in the software industry. Growing consumer markets fostered growth of the packaged software industry, and created whole new categories of software. Since the early 1990s, the spread of the internet and the increasing importance of networked computing have initiated a new round of changes in the IT industry (Mowery and Rosenberg 1998, ch. 151-63). Adding to demand pressures during the late 1990s was global concern about the Y2K problem.

Strong demand for IT professionals contributed to a rapid expansion of the IT workforce and rising relative pay. From 1983 to the peak of the technology boom in 2000, the IT workforce more than doubled in size, increasing from 1.47 million to 3.13 million persons. To put this in perspective, during this same period the total U.S. labor force increased by just 34 percent, from 99.5 million persons to 132.2 million persons (these figures and all the subsequent statistics are derived from the authors’ computations based on data from the Current Population Survey’s merged outgoing rotation groups). Despite the loss of more than 200 thousand IT jobs in the next two years, the IT labor force in 2002 was still 96 percent larger than it had been in 1983.

To draw more workers into IT jobs relative pay had to rise substantially. In 1983 the median hourly wage of full-time IT professionals was about 20 percent above that for all non-IT occupations. By the late 1990s the wage gap had more than tripled, so that IT professionals earned more than 60 percent more than did workers outside of IT.

The growth of IT employment coincided with important changes in the type of jobs performed by IT professionals. Most obviously, as the importance of mainframe computers diminished, the number of computer operators fell substantially. From a peak of 962 thousand computer operators in 1986, the number of computer operators had fallen to just over 300 thousand by 2002. From being close to half of all IT professionals in the mid-1980s this category of workers fell to under 11 percent of the IT workforce by 2002. Offsetting this decline was the extremely rapid growth in the number of computer systems analysts and scientists. This segment of the IT labor force grew from 273 thousand in 1983 to more than 1.7 million in 2002. By the latter year, this category of workers constituted over 60 percent of all IT professionals, up from less than 20 percent in the early 1980s.

Contrary to the trends in most of the US labor force, the share of women in the IT workforce has declined substantially over the past two decades. In 1983 women made up slightly more of the full-time IT workforce, 43 percent, than they did of all full-time non-IT workers, 40 percent. By 2002, however, the share of women in IT had fallen sharply, dropping to 30 percent, while the share in the non-IT workforce had risen to over 49 percent.

The decline of female representation in IT is troubling, but much of this decline can be accounted for by the declining number of computer operators. Removing this group the share of women in other IT occupations has remained quite stable at around 28 to 29 percent of the workforce. Thus the falling share of women reflects the growing importance within IT of occupations that have traditionally been dominated by men (and, implicitly, the failure of more women to enter these traditionally male-dominated fields).

As is true more generally, women in IT earn less than men do. Indeed the gender wage gap in IT is quite similar to that in the rest of the labor force. In 2002 women in IT earned 82.5 percent as much per hour as men, while in the rest of the labor force they earned 82.8 percent of what men did. Average pay for computer operators is considerably lower than for other IT occupations, so the concentration of women in this field tends to magnify the gender pay gap. Excluding computer operators, women earned about 86 percent of what men did in the remaining IT occupations. This pay ratio has been approximately constant over the past two decades, increasing only from 83 percent in the early 1980s.

IT occupations are often characterized as involving long hours and requiring a significant time commitment. One reflection of this is the higher proportion of both men and women in IT who work full time. In 2002, 95 percent of men and 91 percent of women in IT worked full-time. In non-IT jobs 87 percent of men and just 73 percent of women worked full-time. As a result the average women in IT worked more than 3 additional hours per week than did the average woman in a non-IT job (39.5 hours compared to 36.2 hours). The longer hours in IT may be one factor that discourages women–especially those with young children–from going into or staying in the field.

Table 1 summarizes a variety of demographic characteristics for IT and non-IT occupations broken down by gender. As the table reveals, IT workers tend to be somewhat younger than the rest of the labor force. This is especially true for male IT workers, who are on average more than three years younger than their non-IT counterparts, but female IT workers are also younger than women in non-IT occupations. Reflecting the high levels of training needed to enter IT professions, many more workers in IT jobs have bachelors degrees or higher. Fully two-thirds of men and more than half of women in IT occupations have at least a Bachelors degree, compared to 30 percent of men and 31 percent of women in non-IT occupations.

Table 1:

Selected Demographic Characteristics of Information Technology and Non-Information Technology Workers, 2002

Source: Authors' calculations from Current Population Survey merged outgoing rotation group data.

In contrast to the differences in age and education levels, the percent of workers who are married with spouse present is relatively similar between IT and non-IT occupations. It is true, however, that IT workers are somewhat more likely to have never been married than is true for those in non-IT occupations, but it seems likely that this is due to the fact that IT professionals are younger than the non-IT workforce. Reflecting the fact that married women are still more likely to exit the labor force than are married men, within both groups working women are less likely to be married with their spouse present than is true for men. On the other hand, the proportions of workers with one or more of their own children present in the household is quite similar between IT and non-IT occupations, suggesting that this pattern is similar for both IT and non-IT workers.

After nearly two decades of explosive growth and transformation the expansion of the IT workforce came to an abrupt halt with the collapse of the technology bubble in 2001. For the past several years the number of IT workers has been declining. This decline is generally expected to be temporary, and most forecasts anticipate that employment in IT occupations will continue to grow more quickly than in the labor force generally, though the differential is unlikely to be as large as it was in the past (U.S. Bureau of Labor Statistics 2004).

In the past few years there has been increasing concern about the role of off-shoring in IT job losses. There have been numerous reports of companies exporting technical support and programming jobs to suppliers in India, China, and other low-wage countries with well-educated labor forces. Given the large international differences in wages, shifting some tasks to Asian countries is an attractive option for U.S. companies seeking to cut labor costs. But it is important not to overstate the potential impact of this trend. Off-shoring is most effective when the tasks to be performed have been routinized. These, in turn are the sorts of jobs that are most in-danger of being automated in any event. Jobs requiring specialized knowledge of business practices and discretionary decisions are likely to continue to be performed in proximity to customers, thus ensuring that the vast majority of higher level IT jobs, such as those performed by systems analysts, will remain in the United States (Edwards 2004).

While this suggests that IT job losses in the United States due to off-shoring may be small, it also suggests that the composition of IT jobs will remain biased towards those high skilled jobs that contain relatively few women. Thus prospects for increasing the representation of women in IT appear relatively bleak. If relatively few women have been drawn into the rapidly growing field of computer systems analysts and scientists during the period of rapid expansion in employment, opportunities for women are likely to remain limited in the future as aggregate growth slows. More research is needed to understand why women have tended to avoid these higher-level IT jobs, and to identify those dimensions of education, hiring, and retention that have produced such large gender gaps in representation.

During the past half-century gender differences in the labor market have closed substantially. Overall, women’s labor force participation behavior has come increasingly to resemble that of men, so that today women constitute approximately half of the US labor force. Although a gender earnings gap remains today, the size of this gap has been reduced considerably, and after accounting for differences in education, experience and other characteristics it is smaller than indicated by unadjusted comparisons.

Set against the background of these broad labor market changes, gender differences in Information Technology are striking. While total employment in IT has grown rapidly, women’s share of employment across all IT occupations has fallen substantially over the past two decades. The absence of women does not reflect an absence of financial incentives. Gender pay gaps in IT have paralleled those in the workforce generally. Since pay in IT occupations has grown quite quickly women could realize significant financial rewards from moving into IT occupations.

Although the growing gender gap in IT employment is largely due to changes in the mix of IT occupations that has increased the numbers of computer systems analysts and scientists, the fact remains that women hold less than one-third of such jobs today, about the same proportion as they held 20 years earlier. The persistent under representation of women in these higher level IT occupations is an as yet unexplained phenomenon that requires further study.

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Weil, D. N. Economic Growth (2005). Boston: Pearson-Addison Wesley.

Current Population Survey: A monthly survey of approximately 60,000 households administered jointly by the U.S. Census Bureau and Bureau of Labor Statistics to gather information about employment status and demographic characteristics of individuals.

Full-Time Worker: An individual who works an average of 35 or more hours per week.

Labor Force Participation: In the United States labor force participation is assessed based on the response to questions asked as part of the Current Population Survey. An individual is said to participate in the labor force if he or she is over 16 and either performed paid work, or engaged in a variety of job-seeking activities in the week prior to the survey.

Labor Force Participation Ratio: The ratio of the number of workers participating in the labor force to the total population, aged 16 or over.

Off-Shoring: The practice of relocating jobs previously performed in the United States to other, countries; typically low-wage Asian countries like China and India.

Technology Bubble: The period of time during the mid- to late-1990s when investment in internet based companies boomed. The precise dating of the beginning of the bubble is difficult, but it is generally agreed that the bubble came to an end when US stock markets reached a peak in early 2001.

Wage Gap: The difference in pay between two groups of workers, such as Blacks and Whites, or Men and Women. The wage gap can be measured either in absolute terms or as a ratio or percentage difference.

About the authors

Joshua L. Rosenbloom is a Professor, University of Kansas Department of Economics and Research Association National Bureau of Economic Research.

Ronald A. Ash is a Professor, University of Kansas School of Business.

LeAnne Coder is a Graduate Student, University of Kansas, School of Business.

Brandon Dupont is a Graduate Student, University of Kansas Department of Economics.