Survey Overview (2019 Survey Cycle)

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Purpose.

The Business Enterprise Research and Development Survey and its immediate predecessors BRDIS and BRDS are collectively referred to as BERD in this overview. BERD is the primary source of information on R&D expenditures and R&D employees of for-profit, publicly or privately held, nonfarm businesses with 10 or more employees in the United States that performed or funded R&D either domestically or abroad.

Data collection authority.

National Science Foundation Act of 1950, as amended, and the America COMPETES Reauthorization Act of 2010; collected under Office of Management and Budget control number 0607-0912, expiring 28 February 2022.

Major changes to recent survey cycle.

Data collection was added to determine whether companies filed for a state tax credit for research activities, the amount spent on artificial intelligence R&D, and counts of temporary and leased employees working on R&D.

Key Survey Information

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Frequency.

Annual.

Initial survey year.

BRDS collected data for 2017–18, BRDIS collected data for 2008–16, and the Survey of Industrial R&D (SIRD) collected data for 1953–2007.

Reference period.

CY 2019.

Response unit.

Companies with known positive R&D activity (approximately 20,000), known to have no R&D activity (approximately 2,300), and with unknown R&D activity (approximately 23,500).

Sample or census.

Sample survey representing for-profit, publicly or privately held companies with 10 or more employees in the United States that performed or funded R&D either domestically or abroad in the mining, utilities, construction, manufacturing, wholesale trade, retail trade, or services industries.

Population size.

A total of 1,125,000 companies.

Sample size.

A total of 46,000 companies prior to data collection. The actual number of companies that remained within the scope of the survey between sample selection and tabulation was 42,500.

Key variables.

Key variables of interest are listed below.

  • R&D performance (domestic and foreign R&D for U.S.-based companies)

  • Total and R&D employment

  • Sources of R&D funding

  • Type of R&D work (basic research, applied research, and development)

  • Type of R&D cost (e.g., salaries and fringe benefits)

  • R&D capital expenditures

  • R&D application and technology focus areas

  • Industry codes based on the North American Industry Classification System (NAICS)

  • Business activity codes

  • Geographic location of domestic and foreign R&D performance of U.S.-based companies

  • Sales

Survey Design

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Target population.

The target population consists of all for-profit nonfarm companies that are publicly or privately held, have 10 or more paid employees in the United States, have at least one establishment that is classified in an in-scope sector based on NAICS, is in business during the survey year, and is physically located in the United States.

Sampling frame.

The Business Register, maintained by the Census Bureau, is the source used to create the sample frame for BERD.

Sample design.

BERD has a stratified probability sampling design that uses both simple random sampling and probability proportional to size (PPS) sampling within strata. Stratification is based on R&D activity and an industry code based on the North American Industry Classification System (NAICS). For companies with known R&D activity, PPS sampling is based on R&D performance. For companies with unknown R&D activity, PPS sampling is based on annual payroll. Companies known to perform large amounts of R&D and companies with large amounts of payroll are selected with certainty.

Data Collection and Processing

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Data collection.

BERD uses multimode data collection by paper booklet or Web reporting instruments. Respondents have the option to report on the Web (99%) or by mail (1%).

Data processing.

All data submitted by respondent companies are reviewed to ensure that data fields are complete and that data are internally consistent. Given the size and complexity of BERD, many survey responses contain errors that require correction or unusual patterns that require validation. Several hundred automated edit checks are applied to improve the efficiency of analyst data review and correction. Approximately two-thirds of these edit checks are designed to catch arithmetic errors and logically inconsistent responses (balance edits). The remaining edit checks are designed to flag outliers for further analyst review (analytical edits). During editing, if additional information or data corrections are needed, respondents are contacted. If additional information or corrected data cannot be obtained from respondents, data are imputed.

Estimation techniques.

The general methodology used to produce estimates from BERD involves sums of weighted data (reported or imputed), in which the weights are the product of the sampling weight and the nonresponse adjustment factor. However, there are some exceptions, which are described in the technical notes in the annual reports for BRDIS, BRDS, and BERD (https://www.nsf.gov/statistics/srvyberd/).

Survey Quality Measures

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Sampling error.

Estimates based on the total sample have small relative standard errors (RSEs). An RSE is the standard error of the survey estimate divided by the survey estimate and then multiplied by 100. For 2019, RSEs for domestic R&D performance paid for by the company, paid for by others, and total were 0.43%, 0.67%, and 0.38%, respectively. Estimates of sampling errors associated with each cell in the detailed statistical tables are available by request.

Coverage error.

Coverage error is minimal because the Business Register, the source for BERD, is continually updated and contains comprehensive coverage of all domestic businesses.

Nonresponse error.

The unit response rate was 69.0% for 2019. Except for estimates of company counts, unit nonresponse is handled by adjusting weighted reported and imputed data by multiplying each company's sampling weight by a nonresponse adjustment factor. For estimates of company counts, other adjustments for nonresponse are made. Detailed descriptions of the adjustments for nonresponse are available in the annual reports containing detailed statistical tables.

Measurement error.

Known sources of measurement error include differences in respondent interpretations of the definitions of R&D activities; differences in accounting procedures, specifically, the characterization and reporting of R&D activities by large defense contractors funded by the U.S. federal government; the reporting of R&D activities by companies classified in the scientific research and development services industry, NAICS 5417; and differences in how companies count and report numbers of employees in various categories, including whether they work on R&D full time or part time. No quantitative metrics of measurement error are produced, but ongoing efforts to minimize measurement error include questionnaire pretesting, improvement of questionnaire wording and format, inclusion of more cues and examples in the questionnaire instructions, in-person and telephone interviews and consultations with respondents, and post-survey evaluations.

Data Availability and Comparability

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Data availability.

Statistics from BERD for 2019 are available at https://www.nsf.gov/statistics/srvyberd/. Statistics produced from BRDS for 2017 and 2018, BRDIS for 2008–16, and SIRD for 1991–2007 are available at https://www.nsf.gov/statistics/industry/. Statistics from SIRD dating to 1953 are available at https://www.nsf.gov/statistics/iris/.

Data comparability.

BERD is a cross-sectional survey designed to produce annual estimates of R&D performance and related statistics, as was its predecessors, BRDS, BRDIS, and SIRD. However, many of the companies that perform large amounts of R&D are included in the survey each year. Thus, there is a longitudinal aspect to the survey. Because of this and the generally low sampling variability of the annual-level estimates, estimates of year-to-year changes are generally precise. Estimates for changes covering a longer time span generally will be less precise.

Beginning in survey year 2018, companies that performed or funded less than $50,000 of R&D were excluded from tabulation. In prior years, companies that performed or funded any amount of R&D were tabulated. This change has affected the comparability of these estimates to those published in prior years. These companies in aggregate represented a very small share of total R&D expenditures in prior years, but they accounted for a larger share of count estimates. Had the companies under this threshold been included in the 2018 estimates they would have contributed approximately $90 million to overall R&D expenditures and would have added around 6,000 to the estimated count of U.S. companies with R&D expenditures.

Except for the discontinuance of the collection of business innovation data by BRDIS and the transfer of the production of business innovation statistics to the Annual Business Survey beginning with the 2017 cycles of both, the transition from BRDIS to BRDS to BERD produced no breaks in the series for the items common to all surveys.

There is no conclusive evidence that the redesign of SIRD to create BRDIS caused breaks in the series for the items common to both surveys, because no substantial changes in scope and methodology were introduced. Significant efforts were made to preserve the comparability of the data series and to minimize the effects of (1) changes in the assignment of companies to industry strata, (2) the inclusion of data on worldwide activities, (3) changes in the measurement of employment, and (4) changes because of the use of a modular survey questionnaire. Nonetheless, possibly because of improved reporting instructions, an unanticipated drop in the number of full-time equivalent scientists and engineers was reported between the last cycle of SIRD (2007) and the first cycle of BRDIS (2008).

Data Products

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Publications.

BERD data are published in NCSES InfoBriefs and reports containing detailed statistical tables in the Business Enterprise Research and Development, Business Research and Development, Business R&D and Innovation, and Industrial R&D series. Data from BERD are also used in the National Science Board's congressionally mandated report Science and Engineering Indicators.

Electronic access.

Results from SIRD are available at NCSES' Industrial Research and Development Information System historical data website, https://www.nsf.gov/statistics/iris/.

BERD contains confidential data that are protected under Title 13 and Title 26 of the U.S. Code. Restricted microdata can be accessed at the secure Research Data Centers administered by the Census Bureau's Center for Economic Studies (CES). Researchers interested in analyzing microdata can submit a proposal to the CES, which evaluates proposals based on their benefit to the Census Bureau, scientific merit, feasibility, and risk of disclosure. To learn more about the Research Data Centers and how to apply, please visit the CES website at https://www.census.gov/programs-surveys/ces.html. For additional information about the application process, including how to initiate a project, please contact the administrator at the primary site where the research will be conducted.

Contact Information

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For additional information about this survey, please contact the Survey Manager.

Raymond M. Wolfe
Survey Manager
Research and Development Statistics Program, NCSES
Tel: (703) 292-7789
E-mail: rwolfe@nsf.gov

National Center for Science and Engineering Statistics
Directorate for Social, Behavioral and Economic Sciences
National Science Foundation
2415 Eisenhower Avenue, Suite W14200
Alexandria, VA 22314
Tel: (703) 292-8780
FIRS: (800) 877-8339
TDD: (800) 281-8749
E-mail: ncsesweb@nsf.gov