Proposal

Women and minorities are substantially underrepresented in the information technology workforce. Although the reasons for this under representation in general science and engineering careers have been extensively studied, we do not know if these general patterns hold for IT workers. It is especially important to examine and remedy this problem, since despite the recent slowdown IT work is one of the most rapidly growing sectors of the economy. Moreover, as information technology permeates all aspects of the economy –– all firms are becoming IT firms –– it is essential that women and minorities enter these careers or be left out of the new economy.

The proposed project will identify important decision points in the educational and work experiences of Information Technology (IT) workers that have led them to enter and remain in the IT workforce. The results of this study will document the normal patterns of entry and retention in the IT workforce to provide a baseline to examine the special problems of women and minorities who are greatly underrepresented in this expanding and lucrative sector of the economy.

Through a survey of both current IT and non–IT workers in the greater Kansas City area, the project will gather data on individual personality traits in conjunction with detailed family background, and educational and work histories. These data will in turn be used to identify aspects of attitudes, family background, and educational and work experiences that have influenced individual decisions to enter IT jobs, as well as to remain in (or exit from) them. Among IT workers we will use these same data to explore differences by sex, and race and ethnicity.

Many of the same factors that explain the underrepresentation of women and minorities in science and engineering careers are likely to be important in explaining the underrepresentation of women and minorities in IT careers. Research on how these factors apply to IT careers has been limited to date, however, and there have been few studies that specifically address factors unique to the rapidly growing IT sector.

By documenting the characteristics of current IT workers, the proposed study will illuminate both the similarities between IT and science and engineering career choices, and the differences. This information can contribute to the design of educational and training curricula intended to insure that the future IT workforce is adequate to employers needs and draws fully on the talents of all potential IT workers. At the same time, it will suggest potential policy interventions that can be used to redress obstacles that may prevent women and minorities from entering or remaining in IT jobs.

Women and minorities are substantially underrepresented in the information technology workforce. Although the reasons for this under representation in general science and engineering careers have been extensively studied, we do not know if these general patterns hold for IT workers. It is especially important to examine and remedy this problem, since despite the recent slowdown IT work is one of the most rapidly growing sectors of the economy. Moreover, as information technology permeates all aspects of the economy –– all firms are becoming IT firms –– it is essential that women and minorities enter these careers or be left out of the new economy.

The proposed project will survey approximately 2,000 Information Technology (IT) and non–IT workers employed in the Kansas City area to identify important decision points in the educational and work experiences of IT workers that have led them to enter and remain in the IT workforce. The results of this study will document the normal patterns of entry and retention in the IT workforce to provide a baseline to examine the special problems of women and minorities in this expanding and lucrative sector of the economy.

The survey will gather data on personalities using the Strong Interest Inventory, along with information on family background, education, and work histories of both IT and non–IT workers to identify those abilities, background conditions, and experiences that are important in the choice to enter and remain in IT careers. Among IT workers we will be able to examine differences by sex, race, and ethnicity. Differences in education and work experience between IT and non–IT workers will be used to identify specific educational or human resource development policies that are likely to encourage women and minorities to enter and remain in IT occupations.

The relatively small numbers of women and minorities among IT workers is one manifestation of the broader underrepresentation of women and minorities among scientific and engineering (S&E) occupations generally.[1] Scholars studying the recruitment and retention of S&E workers have identified a variety of plausible explanations for the relative dearth of women and minorities. Many of these same factors are likely to be important in explaining the underrepresentation of women and minorities in IT careers, and the proposed study is designed to shed light on them and clarify their relative importance.

In addition, however, the design of the proposed study will capture unique aspects of the education and training of individuals in IT jobs resulting from the rapid growth and changing nature of the field. The expansion of IT employment and the concomitant rapid pace of technological change in this sector have meant that job–requirements have been fluid, and training and career paths have not yet had time to become entirely standardized. This has two important implications. First, many students are likely to be poorly informed about what educational and work experiences are necessary to qualify them for entry into IT jobs. The proposed survey will explore the role of accurate information about IT careers in encouraging entry into the field. Second, we expect that relatively more IT workers than science and engineering workers in general will have acquired their skills through on–the–job training. The proposed survey will identify what aspects of these workers formal educational background prepared them to acquire the necessary IT skills on the job or through non–degree training classes.

The underrepresentation of women and minorities, specifically blacks and Hispanics, in the Information Technology (IT) workforce is part of a broader underrepresentation of these groups in all areas of science and engineering. The small numbers of women and these underrepresented minorities in S&E has been widely noted, and a good deal of research has been devoted both to delineating and tracking the changing scope of the problem and to identifying its causes.[2] Comparatively less research has sought to understand the reasons for the small number of women and minorities in IT careers. However, with the rapid expansion of IT employment during the 1990s, this topic has attracted increased interest in the past few years.

In this section, we first review what is known in general about factors affecting the differential entry rates of women and underrepresented minorities into S&E studies and professions. Then we discuss recent research specific to IT careers.

The Educational Pipeline

The literature addressing production of scientists, engineers, and mathematicians commonly uses the metaphor of a "pipeline" to describe the educational process through which students pass. The idea of a pipeline captures the sequential and cumulative aspect of the educational experiences that contributes to the training of qualified scientific and technical personnel. Careers in science, engineering, and technology generally require at least some college, and generally a bachelor’s degree is the minimum qualification for entry into these fields.[3]

The pool of potential entrants into S&E careers is largest as students begin their high school years. Subsequent leakages in the pipeline progressively reduce the number of potential entrants into technical careers. Starting in high school, students begin to make curricular choices that constrain future career choices and opportunities. During these years students begin to acquire the foundational skills in mathematics and science on which subsequent training is dependent. Those who fail to acquire these skills are at a progressively greater disadvantage at later stages of education, and are likely to choose careers outside of science, engineering, and mathematics.

Why are there so few women and minorities in S&E?

A good deal of the research that has been done to date focuses on the magnitude, timing, and causes of "leakage" from the education pipeline that occurs from the beginning of high school through college and post–graduate education. As this research makes clear the underrepresentation of women and minorities arise through different mechanisms.

Women actually attend and graduate from college in greater numbers than men; but relatively few of them receive degrees in science, engineering, or mathematics. Although rates of degree attainment for women in S&E fields have continually increased over the last four decades, research indicates that the disparity between men’s and women’s degree attainment in these areas is still significant. In 1996, for example, women earned 55 percent of bachelor’s degrees award at US colleges, but accounted for just 34 percent of bachelor’s degrees in math and computer science. These disparities increased at the graduate level, where women only received 18.1 percent of doctorate degrees in these fields (National Science Board 2000, p. 4.28, 4.34; Huang, Nebiyu, and Walter 2000, p. 4–5).

On the other hand, research has shown that the percentage of black and Hispanic students entering college who express interest in science, engineering, and mathematics majors and careers is the same or even higher than that of white students (Commission on the Advancement of Women and Minorities in Science, Engineering and Technology Development–hereafter cited as CAWMSET–2000, p. 28; Astin, Korn, Sax and Mahony 1994). Thus minorities’ underrepresentation among S&E degree recipients arises as a result of the small numbers who enter college and their lower completion rates at intended majors. For example, in 1996, African–Americans accounted for 12 percent of the population, 8 percent of all bachelor’s degrees, and 6 percent of S&E bachelor’s degrees. Like women, minorities’ involvement in S&E disciplines significantly decreases at the graduate level (Huang et al 2000, p. 7–9; CAWMSET 2000, p. 30–36; U.S. Department of Commerce 1999, p. 96–8).

Why do college–bound women opt for non–technical majors? And why do so few African–American and Hispanic students attend college? The majority of researchers argue that cultural and social influences are the cause of differences in women and minorities’ interest and abilities in S&E (Alper and Gibbons 1993). Despite researchers’ focus on social and cultural influences and the relatively large literature exploring these influences (see, e.g., Oakes 1990 and Huang et al 2000), there is little consensus about the relative importance of these different factors. Researchers, for example, still disagree about whether females and minorities exit the S&E pipeline because they are socialized to value social, rather than more theoretical, disciplines or because they are pushed out because of teaching methods or discriminatory practices that make these subjects less attractive to them (Alper and Gibbons 1993; Powell 1990, p. 293).

Previous research has identified three broad sets of influences that appear to affect student’s educational and career paths(Huang et al 2000, p. 10–14; Leslie, McClure, and Oaxaca 1998; CAWMSET 2000, p. 15–26; U.S. Department of Commerce 1999, p. 101–102; Powell 1990):

• Family background and support. Parental education and profession, financial resources, emotional support, familial expectations for success, and demands placed on students by family obligations may influence student goals as well as their ability to succeed in science, engineering, and mathematics programs.
• Opportunities and school resources. Exposure to science and mathematics both inside and outside school fosters interests in technical careers and thus influences student attitudes and motivation. School resources, teachers’ skills, and staff attitudes influence the adequacy of course offerings and hence student preparation; they may also influence the quality and quantity of information and encouragement that students receive regarding science and engineering careers and the kinds of preparation necessary to pursue such careers.
• Attitudes, perceptions, and behavior. Perceptions of one’s own ability to master science and math material, differing levels of interest in science and math, and the resulting level of time and effort dedicated to coursework and extracurricular activities appear likely to influence student curricular choices and, consequently, student performance at each stage along the educational pipeline. Because of the cumulative and sequential nature of science, engineering, and math training, early choices may foreclose or constrain subsequent opportunities.

It is apparent that these factors are likely to affect one another and therefore cannot be treated as entirely independent influences. In particular, student attitudes, self–confidence, and behaviors are likely to be shaped directly and indirectly by the outside influences of both family and school. Family background and support are also likely to affect, at least indirectly, opportunities and school resource through parental decisions and resources that affect household location and school choice. The magnitude of these factors’ influences is also different for minorities and women. Some of these factors, such as little self–confidence in one’s mathematical or science abilities, affect both women and minorities. Other factors, such as a deficiency in educational resources and opportunities, tend to affect minorities more severely than they do white females (CAWMSET 2000, p. 2, 36–37; U.S. Department of Commerce 1999, p. 101).

Huang et al (2000) seek to disentangle the effects of different factors in a multivariate statistical analysis of two longitudinal data sets–the National Educational Longitudinal Study (NELS), and the Beginning Postsecondary Students Longitudinal Study (BPS). They use the NELS data set to examine factors that affect the likelihood that high school students will attend college and choose an S&E major. Using a multivariate statistical framework, they find that racial and ethnic differences in the likelihood of attending college and choosing an S&E major are largely explained by family background and support, in combination with student interests. Gender differences, however, remain largely unexplained by these factors (Table 32, p. 61).

Huang et al (2000) use the BPS data set to examine influences on the completion and persistence of S&E majors once they have entered 4–year colleges. These data show that Black and Hispanic students who enroll in S&E majors in their first year are considerably less likely to complete them within 5 years than are Whites and Asians (26.8% vs. 46%), and are more likely to switch to non–S&E majors (30.5% vs. 14.4%). Interestingly, women who choose S&E majors are more likely to complete them than are men. [4] Multivariate analysis of these data show that although the probability of completion is correlated with explanatory variables measuring family background and support, student interest and ability, and institutional characteristics, accounting for these variables does not substantially alter the effects of race, ethnicity or gender on outcomes.

While the pool of women and minorities in S&E fields is greatly reduced by the end of educational pipeline, it is reduced even further during the steps of obtaining a job and maintaining employment. In 1997, women were 46 percent of the U.S. workforce but only 23 percent of the S&E workforce, and they were often found in less prestigious, lower–paying jobs. Underrepresented minorities were 23 percent of the U.S. population and only 6 percent of the S&E workforce (National Science Board 2000, p. 3.10–3.13). Once in S&E occupations, women exit the profession at rates far higher than men (even when controlling for family reasons), a trend that also applies to IT professions (Preston 1994; Council of Economic Advisers 2000, p. 9; CAWMSET 2000, p. 50). Women cite multiple reasons for exiting the field–unfriendly atmospheres towards women, lack of female role models, isolation and lack of mentoring in their jobs, higher performance standards for them, and inadequate mentoring in college to prepare them for corporate jobs; minorities cite many similar difficulties in S&E jobs (Council of Economic Advisers 2000, p. 9; CAWMSET 2000, p. 50–3).

Implications for the Underrepresentation of Women and Minorities in the IT Workforce

In the last two decades, employment in the IT workforce has increased greatly compared to general employment, and job opportunities in IT are only expected to continue increasing (Council of Economic Advisers 2000; U.S. Department of Commerce 1999). Considering the importance of IT to our economy, there is a national concern that an adequate supply of skilled workers exist to fill these jobs. Women and minorities comprise an increasingly larger portion of the U.S. workforce, yet they make up a relatively small percentage of the IT workforce (CAWMSET 2000, p. 9, 40). In 1999, while women comprised 47 percent of the U.S. workforce in general, they only held 29 percent of IT jobs (Council of Economic Advisers 2000, p. 5). The percentages of blacks and Hispanics are similarly low compared to their portion of the overall workforce, and, as in the S&E workforce, minorities and women’s participation is especially low in more prestigious, higher–paying IT jobs (U.S. Department of Commerce 1999, p. 94; Council of Economic Advisers 2000, p. 2; National Science Board 2000, p. 3.11, 3.13).

Recent discussions of the underrepresentation of women and minorities in the IT workforce have echoed discussions about S&E, including the variety of reasons for these groups’ underrepresentation. Unfortunately, these have done little to help to resolve the relative importance of these reasons in determining the makeup of the IT workforce in particular (see e.g., Freeman and Aspray 1999; National Research Council 2001).

In addition to the triad of influences commonly identified as potential explanations for student exit from the S&E educational pipeline, there is another factor that appears to operate in the IT context. Because of the substantial growth of IT employment, and the rapid pace of technical change in this field it is widely believed that students lack an adequate knowledge of potential career IT opportunities, and are not fully aware of the types of classes they should take to prepare for IT careers. According to Garcia and Giles (n.d., p. 3), for example, "secondary school counseling may be key to minority success in college." Freeman and Aspray (1999, p. 80), similarly urge that "because many parents know less about computing than more established professions, it is incumbent on high school guidance counselors to provide information about computing careers."

Limited support for these conjectures is provided by a recent survey of 8th and 11th grade students in Silicon Valley (Silicon Valley Network 1999). This study found that relatively few students knew about the characteristics of common IT jobs. This lack of knowledge was especially pronounced among black and Hispanic students. The same study also found that few students understood the importance of math and science classes as sources of foundational skills needed to pursue advanced study in IT fields. Although these results are suggestive, the study did not in fact document any causal connections between students’ lack of information and either college attendance or choice of major.

Another issue that appears to be specific to the IT workforce is the fact that IT job categories and the requisite qualifications to fill these jobs are still in a state of flux. Because IT occupations are new, education and career paths leading to these jobs are less clearly defined than for longer established S&E jobs. As a result individuals without S&E degrees, but possessing some minimum of computing or math coursework may be able to make the transition to some areas of IT work. At the same time, the graphic design requirements of web site design and other activities may provide a means through which those with artistic training may be drawn into the IT field.

Prior research on the underrepresentation of women and minorities in science, engineering, and mathematics generally has identified in broad outlines the sequential process of training necessary for individuals to enter careers in these fields. The tendency of women and minorities to exit this pipeline in differentially high numbers has suggested an array of interrelated mechanisms that can help to explain their relative absence from technical fields. While these factors seem likely to apply to IT as well, there appear to be additional factors specific to the IT field that require further investigation. There is as yet, little solid evidence about the factors that are most important in this instance, or about their relative importance.

To improve our understanding of how the factors identified in past research on the S&E pipeline as well as those specific to the IT field have contributed to the underrepresentation of women and minorities in IT occupations we propose to gather data on the experiences of current IT workers to identify the key turning points in their passage through the education and training pipeline, as well as their post education work experience. Data will be gathered through a survey of current IT and non–IT workers employed at a large sample of firms located in the greater Kansas City metropolitan area.

We have chosen to focus on the Kansas City area because prior research has provided us with access to a large pool of employers and these contacts will substantially facilitate the process of identifying and interviewing an appropriate sample of employees. Based on these contacts we have already secured endorsements for our study from the Greater Kansas City Chamber of Commerce, and KC Catalyst.

As we argue below employers in the Kansas City area are representative of the larger universe of IT employers (at least those located outside a few high–tech areas like Silicon Valley and Route 128), and our results should thus have broader relevance.

We begin by describing the characteristics of the Kansas City IT employers we will survey, and then detail the nature of the survey we plan to conduct.

Characteristics of The IT Labor Market in the Kansas City Metro Area

Kansas City is not typically identified as a center of high–tech industry. But the greater Kansas City area comprises a large, dynamic economy containing a cross–section of employers of IT workers who can be viewed as representative of many of the broader trends taking place in the national economy. With a population of 1.7 million, the Kansas City SMSA ranks 28th in size in the country. The minority population in Kansas City closely mirrors that of the nation (13.3% Black, and 3.7% Hispanic, compared to 12.1% and 3.9%, respectively for the nation). In terms of industrial composition and the broad sectoral distribution of the labor force the area is also quite similar to the nation as a whole.[5]

During December 2000 and January 2001, the Policy Research Institute at the University of Kansas conducted a survey of firms employing IT workers in the greater Kansas City area (defined to include surrounding communities such as St. Joseph, MO, and Lawrence, KS). This survey provides valuable information about the characteristics of IT employers and workers in the Kansas City area, and contacts PRI made while conducting this survey should facilitate the process of gathering additional data.

With cooperation from the Silicon Prairie Technology Association and the Regional Consortium for Technology and Information Exchange an initial sample of over 1300 primarily for–profit firms was identified. From this initial universe of firms survey workers were able to establish contact with a manager with IT supervision or knowledge in 791 firms. These initial contacts identified 334 firms engaged in IT work or employing at least some IT full–time IT workers. Of the contacted firms eligible to participate in the survey, 128 (38.3 percent) were willing to participate.

Table 1 reports some general characteristics of the surveyed firms. In total the 128 surveyed firms employ roughly 180,000 people, and close to 66,000 IT workers. The firms ranged in size from 1 employee to 60,000 employees, and the number of IT workers ranged from 1 to 20,000. The median firm had 50 employees and 8 IT workers. As is true nationally, women are clearly underrepresented among Kansas City area IT workers. Interestingly the number of minority IT workers is relatively high. Possibly this is the result employers including Asians in their estimate of the number minority workers. Since Asians are overrepresented in the IT workforce, this would tend to bias the estimates upward.

Table 1:
Characteristics of Kansas City Area
Firms Surveyed by Policy Research Institute

As Table 2 illustrates the surveyed firms are located across a broad spectrum of industries including technology consulting, communications, software production or programming, design and production and electronic commerce. The largest single category of firms, representing 43.5 percent of valid responses, falls in the "other" category, reflecting one of the key findings of the survey, that IT work is defusing widely into all sectors of economic activity including many more traditional sectors and industries.

Table 2:
Primary Service or Sector of Kansas City Area
Firms Surveyed by Policy Research Institute

Table 3 provides some indication of the range of skills used by the firms in the survey, as well as their relative importance. For each of the skills listed in the table the surveyed firms were asked to rate their importance to the firm’s operations on a 10–point scale with 10 meaning very important and 1 meaning not at all important. Using the median response it is evident that Operating System expertise, knowledge of specific software languages, network/LAN administration, application specialists, and database administration are the most important types of IT skills used by Kansas City area employers.

Table 3:
Importance of Specific IT Skills to Kansas City Area
Firms Surveyed by Policy Research Institute
(Median Response)

The demographic composition of the IT workforce in Kansas City largely parallels national patterns. The PRI survey found that for the average employer in Kansas City women made up about 26 percent of the IT workforce, while minorities made up slightly less than 13 percent. Looking at composition of workers rather than employers, women were estimated to make up 28 percent of the IT workforce employed by surveyed firms, while minorities constituted 23 percent of the IT workforce employed. The discrepancy between minority shares in the total workforce, and the average across employers reflects the fact that minority employment was more concentrated among the larger employers in the survey. It should be possible to design a sampling framework that will provide an adequate basis to compare and contrast education and career histories of women and minorities in IT careers with those of white males.

A survey of IT workers employed in the Kansas City area is not likely to be representative of workers in a few cutting edge centers of high–tech innovation like Silicon Valley and the Route 128 area outside of Boston. But IT workers in the Kansas City area are likely to be representative of the bulk of IT workers who are employed outside these areas, many of whom are beginning to find employment outside of traditional high–tech sectors. Studying the career paths of these workers should provide substantial insight into the factors that influence decisions to enter into and remain in the IT workforce that can be used to shed light on the factors contributing to the underrepresentation of women and minorities in this sector of the economy.

Survey Design and Methodology

Using contacts described previously in the approximately 335 Kansas City area firms known to employ some IT workers, we intend to seek and gain cooperation from approximately 50 firms (including those with larger numbers of IT workers) in the proposed study. The firms will be asked to provide us access to first, a sample of their IT workers, and later to a comparable sample (roughly matched in terms of age and education level) of non–IT workers.

We plan to draw an initial sample of 3500 IT workers and request their participation in a telephone survey covering life history, education experiences, and work history. Once participants have completed the telephone survey they will be asked to take an established measure of occupational personality, the Strong Interest Inventory (Harmon et al., 1994), via the Internet. We conservatively anticipate a responses rate of approximately 30%, yielding survey data on approximately 1000 IT workers, and occupational personality data on a subset of these. After the initial wave of survey data are collected, we intend to engage in purposive sampling if necessary with the goal of obtaining at least 100 Black and 100 Hispanic respondents.

Next, from these same 50 firms, we intend to draw a comparable sample (roughly matched in terms of age and education level) of 3500 non–IT workers, and request their participation in the same telephone survey, followed by the request to take the same occupational personality measures via the Internet. We conservatively estimate obtaining survey data on approximately 1000 non–IT workers, and occupational personality data on a subset of these. We also intend to engage in additional purposive sampling if necessary with the goal of obtaining at least 100 Black and 100 Hispanic non–IT respondents.

Having comparable data sets for IT and non–IT workers should allow us to systematically identify and evaluate differences and similarities in these two groups with respect to life history events, educational choices, education achievement, work and occupational choices, and basic occupational personality (the extent to which individuals’ interests match up to those for six general occupational types – Realistic, Investigative, Artistic, Social, Enterprising, and Conventional). Engaging in purposive sampling, if necessary, to ensure that survey responses are obtained from at least 100 Black and 100 Hispanic IT and 100 Black and 100 Hispanic non–IT workers will help ensure the statistical conclusion validity of comparison between IT and non–IT worker ethnic subgroups. (Given that approximately 25% of IT workers are female, we anticipate no problem in obtaining adequate numbers of female respondents to ensure the statistical conclusion validity of comparisons made for gender.)

Collecting occupational personality data using the Strong Interest Inventory will allow for the exploration of differences in basic occupational interest patterns between IT – and non–IT workers, and among the ethnic and gender grouping within and across these two groups. It should also allow for determination of the relative impact of basic interests, life history, educational experiences, and work history on pursuit, achievement, and maintenance of IT careers.

The telephone survey approach has been used successfully by our organization in surveys on the training needs of Kansas firms (Krider et al., 1989; Krider et al., 1991; Stella et al., 1997). Our telephone survey approach typically involves the following steps:

1. An initial phone call to the respondent to explain the purpose of the research project and the nature of the survey;
2. Securing the agreement of the participant to participate;
3. Securing the name and address of the participant so that preliminary information on what will be covered in the survey can be mailed to the participant – the participant is cued to have specific information available at the time of the actual survey;
4. An appointment is set with the participant for the telephone survey;
5. The participant is called at the appointed time and responds to the survey questions;
6. The surveyor using a prompting survey template enters survey responses as the respondent gives them.

Work Plan

The initial phase of the project will involve making contact with firms and developing the survey instrument. These two activities will be pursued simultaneously From June to December 2002. During this period Policy Research Institute investigators contact firms to obtain their cooperation and will craft an initial survey. This survey will be pilot tested in three to five focus groups of IT workers. Based on experience in these focus groups, the investigators will revise the survey. The revised survey will be piloted using three to five additional focus groups, and subsequent feedback will be incorporated into the final survey instrument.

After verification of the revised survey instrument survey research laboratory workers will conduct telephone surveys of IT and non–IT workers between January and June 2003. Once the surveys have been administered the research team will begin analysis of the resulting data, and write up the results. This phase of the project will be completed by the end of July 2004.

Rosenbloom had NSF support for a project entitled "Estimation of Gross Domestic Product for Colonial North America: the Lower South as a Pilot Project," (Grant No. 9808516) in collaboration with Thomas Weiss and Peter C. Mancall. The results of that project demonstrate that it is possible to use the available evidence for the colonial period of American history to construct reliable, comprehensive estimates of Gross Domestic Product.

The project was intended to provide better measures of aggregate economic growth before 1800 in the Lower South, a region comprising the colonies (and later states) of Georgia, North Carolina, and South Carolina. The work involved compiling new evidence from the abundant colonial documents, integrating it with existing quantitative and qualitative accounts, and interpreting it within a consistent theoretical framework. Data sources used included the minutes of the colonial and state assemblies, correspondence of the colonial and state governors, correspondence and other records of the Commissioner of Indian Affairs, documents relating to the export trade, figures on shipping tonnage entering and clearing ports, the records of the colonial and state committees of claims, vestry minutes of parish churches, the financial documents of the Trustees of Georgia, and probate inventories for the three colonies and states, as well as data compiled in American State Papers and Historical Statistics of the United States, and statistics collected by previous researchers.

These various pieces of data were used primarily to estimate Gross Domestic Product and GDP per capita at benchmark dates in the eighteenth century relying on methods developed by Simon Kuznets and Paul David to generate the GDP figures and identify the major sources of economic growth. In the process of that estimation it proved useful to construct time series on the labor force, the agricultural labor force, the age and sex composition of the free and slave populations, the value of the diet, a volume index of international trade, and key export items such as rice and deerskins, and estimates of trade with other colonies. Beyond the construction of GDP figures, the evidence was used to analyze the behavior of slave prices and the market for slaves, to gauge the likely course of agricultural productivity, and to delineate the nature and extent of economic interaction between the colonists and Native American Indians.

The results of this project’s analysis revealed how important it is to take account of the large amount of economic activity directed toward the domestic market, especially the production and consumption of food. Even in a region like the Lower South, where the export sector was large and successful, the domestic sector largely determined the pace and pattern of the region's economic growth. Mancall, Rosenbloom and Weiss’ estimates of GDP and GDP per capita revealed that growth of GDP per capita, even in this highly export–oriented region, was very slow–almost certainly less than 0.1 percent per year in the colonial period (1720 to 1770) or the longer period of 1720 to1800. These findings have forced a reconsideration of the power of export–based models of economic growth to explain the performance of the economy during the colonial and early national periods of American history, and perhaps more generally as well. To the extent that export models can explain growth during those periods, further questions arise as to the mechanism by which export growth is transmitted to the rest of the economy.

The results of the project have been disseminated widely and in various ways, including 10 presentations at conferences and seminars, 8 working papers. To date the results have resulted in 3 published or forthcoming articles and book chapters. Mancall, Rosenbloom, and Weiss will continue to disseminate the results in additional papers and presentations, and are working on several more articles to be submitted to journals in the coming months. Their work has also produced the most comprehensive series of slave prices, an annual series on exports of deerskins from 1700–1800, and a compilation of public expenditures by the colonial governments of Ga., NC, and SC from 1700–1776.

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[1] Some of this work also includes mathematics. For purposes of brevity, however, we will refer to science and engineering.

[2] We will use the term "minorities" to refer to blacks and Hispanics, which are the racial groups underrepresented in science and engineering fields.

[3] The majority of IT workers also require at least some post–high school training. See, e.g., Freeman and Aspray (1999, ch. 5).

[4] The finding that women are more likely to complete S&E majors is somewhat at odds with the results of other recent research. CAWMSET (2000, p. 31) and National Science Board (2000, p. 4.27) report that women are more likely to switch out of S&E majors.

[5] Industry percentages of SMSA earnings in 1996 (and country 1997) were: manufacturing, 14.9 (17.7); Retail, 9.1 (9.1); Finance, Insurance and Real Estate, 8.7 (8.5); Services. 27.3 (28.5); Government, 13.7 (14.8). Employment shares for the SMSA (and country) were: Manufacturing, 14.5 (18.0); Retail, 20.1 (21.3); Finance, Insurance and Real Estate, 8.1 (6.9); Services, 34.2 (34.9). These figures and those in the text are from Gaquin and Littman, (1999).