- Chapter Overview
- Types of Indicators
- Data Sources and Considerations
- Key Elements for Indicators
In response to increasing interest in both the policy and research communities about the role of science and technology (S&T) in state and regional economic development, a new chapter devoted to the subject was introduced in the 2004 edition of Science and Engineering Indicators. The chapter focuses on the S&T indicators for individual states and the District of Columbia. It has been expanded in the 2008 edition from the original 24 state indicators to 47.
The reader is cautioned that all of the indicators are broad measures, and several rely on sample estimates that have a margin of error that may be substantial for some states; this is called out in appropriate places. In any case, small differences in state values generally carry no useful information.
The indicators are designed to present information about various aspects of state S&T infrastructure and to stimulate discussion about appropriate uses of state-level S&T indicators. The data used to calculate the indicators were gathered from both public and private sources. Whenever possible, data covering a 10-year span are provided to identify meaningful trends. However, because consistent data were not always available for the 10-year period, data for certain indicators are given only for the years in which comparisons are appropriate.
Ready access to accurate and timely information is an important tool for formulating effective S&T policies at the state level. By studying the programs and performance of their peers, state policymakers may be able to better assess and enhance their own programs and performance. The tables are intended to give the user a convenient listing of some of the quantitative data that may be relevant to technology-based economic development. In addition to describing the behavior of an indicator, the "Findings" section frequently presents an interpretation of the behavior's relevance and meaning. The interpretation is sometimes speculative, with the objective of motivating further thought and discussion.
Types of Indicators
Forty-seven indicators are included in this chapter and grouped into the following areas:
- Elementary and Secondary Education
- Higher Education
- Financial Research and Development Inputs
- Research and Development Outputs
- Science and Technology in the Economy
The first two areas address state educational attainment. In this edition of Indicators, emphasis has been increased on the science and mathematics skills students develop at the elementary and middle school levels. Additional information on gender and racial/ethnic performance has been added in appendix tables 8-1 through 8-12 for those indicators reporting mathematics and science results for fourth and eighth graders. Student achievement is expressed in terms of performance, which refers to the average state score on a standardized test, and proficiency, which is expressed as the percentage of students who have achieved at least the expected level of competence on the standardized test.
Comparable state-level performance data are not available for high school students. Instead, mastery of college-level material through performance on Advanced Placement Exams has been included as a measure of the skills being developed by the top-performing high school students. Other indicators in education focus on state spending, teacher salaries, student costs, and undergraduate and graduate degrees in S&E. Three new indicators have been added to measure the level of education in the population of individual states.
Workforce indicators focus on the level of S&E training in the employed labor force. These indicators reflect the higher education level of the labor force and the degree of specialization in S&E disciplines and occupations.
Financial indicators address the sources and level of funding for R&D. They show how much R&D is being performed relative to the size of a state's business base. Comparison of these indicators illustrates the extent to which R&D is conducted by industrial or academic performers.
The Experimental Program to Stimulate Competitive Research (EPSCoR program) is a federal program aimed at building R&D capacity in states that have historically been less competitive in receiving federal R&D funding. Because this program does not cover all states and is basically focused on academic institutions, it is covered in chapter 5, Academic Research and Development, in the sidebar, "EPSCoR—the Experimental Program to Stimulate Competitive Research."
The final two sections provide measures of outputs. The first focuses on the work products of the academic community and includes the production of new doctorate holders, the publication of academic articles, and patent activity both from the academic community and from all sources in the state.
The second section of output indicators examines the robustness of a region's S&T activity. These indicators include venture capital activity, Small Business Innovation Research awards, and high-technology business activity. Although data that adequately address both the quantity and quality of R&D results are difficult to find, these indicators offer a reasonable information base.
Data Sources and Considerations
Raw data for each indicator are presented in the tables. The first entry in each table represents the average value for the states. For most indicators, the state average was calculated by summing the values for the 50 states and the District of Columbia for both the numerator and the denominator and then dividing the two. Any alternate approach is indicated in the notes at the bottom of the table.
The values for most indicators are expressed as ratios or percentages to remove the effect of state size and facilitate comparison between large and small states or heavily and sparsely populated states. For example, an indicator of higher education achievement is not defined as the absolute number of degrees conferred in a state because sparsely populated states are neither likely to have nor need as extensive a higher education system as states with larger populations. Instead, the indicator is defined as the number of degrees per number of residents in the college-age cohort, which measures the intensity of educational services relative to the size of the resident population.
No official list of high-technology industries or sanctioned methodology to identify the most technology-intensive industries exists in the United States. The definition used here was developed by the Bureau of Labor Statistics and is based on the percentage of employment in technology-oriented occupations. See "Technical Note: Defining High-Technology Industries."
Although data for Puerto Rico are reported whenever available, they frequently were collected by a different source, making it unclear whether the methodology used for data collection and analysis is comparable with that used for the states. For this reason, Puerto Rico was neither ranked with the states nor assigned a quartile value that could be displayed on the maps. Including data for U.S. territories and protectorates, such as American Samoa, Guam, Northern Mariana Islands, and Virgin Islands, was considered; however, data for these areas were available only on a sporadic basis and for fewer than one-quarter of the indicators, so they were not included.
Although there is no consensus on the identity of high-technology industries, this chapter utilizes a modification of the approach employed by the Bureau of Labor Statistics (BLS). That approach is based on the intensity of high-technology employment within an industry. High-technology occupations include scientific, engineering, and technician occupations. These occupations employ workers who possess an in-depth knowledge of the theories and principles of science, engineering, and mathematics, which are generally acquired through postsecondary education in some field of technology. An industry is considered a high-technology industry if employment in technology-oriented occupations accounts for a proportion of that industry's total employment that is at least twice the 4.9% average for all industries (i.e., 9.8% or higher). Level I high-technology industries include the 14 industries in which technology-oriented employment is at least 5 times the average for all industries, or 24.7%. Level II high-technology industries include the 12 industries in which the high-technology occupations are 3.0–4.9 times the average or 14.8%–24.7% of total employment. Level III high-technology industries include the 20 industries with a proportion of high-technology employment that is 2.0–2.9 times the industry average or 9.8%–14.7% of total employment.
In each case, the industry is defined by a four-digit code that is based on the listings in the 2002 North American Industry Classification System (NAICS). The 2002 NAICS codes contain a number of new additions and changes from the previous 1997 NAICS codes that were used to classify business establishments in datasets covering the period 1998–2002. Therefore, this listing of high-technology industry codes can be applied only to datasets covering the years after 2002 when the 2002 NAICS codes were used to classify business establishments.
The BLS methodology includes the "Federal Government, excluding Postal Service" in its listing of high-technology industries. However, in this chapter "high-technology industries" is used in indicators that refer to business establishments and employment in those business establishments. These indicators are intended to measure private-sector activity. For this reason, "Federal Government, excluding Postal Service" was deleted from the list of high-technology industries. With this deletion, the list of high-technology industries used in this chapter includes the 46 four-digit codes from the 2002 NAICS listing shown in
Key Elements for Indicators
Six key elements are provided for each indicator. The first element is a map that is color-coded to show in which quartile each state placed on that indicator for the latest year that data were available. This helps the reader quickly grasp geographic patterns. The sample map below shows the outline of each state. On the indicator maps, the darkest color indicates states ranking in the first or highest quartile, and white indicates states ranking in the fourth or lowest quartile. Cross-hatching indicates states for which no data are available.
The second element is a quartiles table. States are listed alphabetically by quartile. The range of indicator values for that quartile is shown at the top of the column. Ties at quartile breaks were resolved by moving the tied states into one quartile. Differences in states at the margins of adjacent quartiles will often not be substantively meaningful.
The third element, at the bottom of the map box, is a short citation for the data source. The full citation appears under the table on the facing page.
The fourth element, in a shaded box on the lower left side of the page, is a summary of findings that includes the national average and comments on trends and patterns for the particular indicator. Although most of the findings are directly related to the data, some represent interpretations that are meant to stimulate further investigation and discussion.
The fifth element, on the lower right side of the page, is a description of the indicator, a brief note about the nature of the data, and other information pertaining to the data.
The final element is the data table that appears on the facing page. Up to 3 years of data and the calculated values of the indicator are presented for each state, the District of Columbia, and Puerto Rico. Puerto Rico is included in the data table only when data are available.
Hecker D. 2005. High-technology employment: A NAICS-based update. Monthly Labor Review 128(7):57–72.