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New Mandatory Survey from US Census Bureau

Blog | august 7, 2018.

In June of 2018, the United States Census Bureau announced a new survey called the Annual Business Survey that will replace three existing surveys, the Survey of Business Owners for employer businesses, the Annual Survey of Entrepreneurs, and the Business Research and Development and Innovation Survey for Microbusinesses.  The Census Bureau is purportedly combining the surveys in an effort to reduce respondent burden, increase data quality and reduce inefficiencies.

If your business is selected, you will receive an initial letter informing your business of the requirement to complete the survey. The letter will contain instructions to access the survey online. The Census Bureau estimates that the electronic survey will take approximately 52 minutes to complete, though conversations that our attorneys have had with clients indicate that the time for completion may take much longer.

Responses to the Annual Business Survey are mandatory per Sections 224 and 225 of Title 13 of the United States Code. Any business who fails to respond will be subject to penalties of up to $5,000.

For a list of FAQs about the new survey visit census.gov . If you have any additional questions about the new survey or your requirements please contact us at 770-536-3381.

Explore a topic, ask a question, or just get to know us. Call us at 770.536.3381

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Current Mandatory Business Surveys

A Notice by the Census Bureau on 03/25/2024

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Supplementary information:, annual integrated economic survey (aies), annual business survey (abs), business and professional classification report, business enterprise research and development survey (berd), paperwork reduction act, enhanced content - submit public comment.

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Census Bureau, Department of Commerce.

Notice of determination.

The Bureau of the Census (Census Bureau) will conduct the following current mandatory business surveys in 2024: Annual Integrated Economic Survey, Annual Business Survey, Business and Professional Classification Report, and the Business Enterprise Research and Development Survey. We have determined that data collected from these surveys are needed to aid the efficient performance of essential governmental functions and have significant application to the needs of the public and industry. The data derived from these surveys, most of which have been conducted for many years, are not publicly available from nongovernmental or other governmental sources.

The Census Bureau will make available the reporting instructions to the organizations included in the surveys. Additional copies are available upon written request to the Director, 4600 Silver Hill Road, U.S. Census Bureau, Washington, DC 20233-0101.

Nick Orsini, Associate Director for Economic Programs, telephone: 301-763-1858; email: [email protected] .

The surveys described herein are authorized by title 13, United States Code (U.S.C.), sections 131 and 182 and are necessary to furnish current data on the subjects covered by the major censuses. These surveys are made mandatory under the provisions of sections 224 and 225 of title 13, U.S.C. These surveys will provide continuing and timely national statistical data for the period between economic censuses. The data collected in the surveys will be within the general scope and nature of those inquiries covered in the economic census. The most recent economic census was conducted in 2023 for the reference year 2022. The next economic census will occur in 2028 for the reference year 2027.

Notice of specific reporting requirements for each survey, including who is to report, the information to be reported, the manner of reporting, and the time and place of filing reports, will be provided by mail or email only to those required to complete these surveys.

The AIES is a new survey designed to combine several existing Census Bureau annual survey collections to reduce respondent burden and simultaneously increase data quality and operational efficiencies. The AIES integrates and replaces the following existing annual collections: the Annual Retail Trade Survey (ARTS) (Office of Management and Budget (OMB) control number 0607-0013), the Annual Wholesale Trade Survey (AWTS) (OMB control number 0607-0195), the Service Annual Survey (SAS) (OMB control number 0607-0422), the Annual Survey of Manufactures (ASM) (OMB control number 0607-0449), the Annual Capital Expenditures Survey (ACES) (OMB control number 0607-0782), the Manufacturer's Unfilled Orders Survey (M3UFO) (OMB control number 0607-0561), and the Report of Organization (OMB control number 0607-0444).

The AIES covers all domestic, private, non-farm employer businesses in the U.S. (50 States and the District of Columbia) as defined by the 2017 North American Industry Classification System (NAICS). Exclusions are most foreign operations of U.S. businesses and most government operations (including the U.S. Postal Service), agricultural production companies, and private households. The AIES sample is selected from a frame of approximately 5.4 million companies constructed from the Business Register (BR), which is the Census Bureau's master business list.

The AIES estimates will include data on employment; revenue including sales; shipments; receipts; taxes, contributions; gifts and grants; products; e-commerce activity; operating expenses including purchased services; payroll; benefits; rental payments; utilities; interest; equipment; materials and supplies; other detailed operating expenses; and assets which includes capital expenditures; inventories; depreciable assets; and robotics.

The AIES will provide continuous and timely national and subnational statistical data on the economy. Government program officials, industry organization leaders, economic and social analysts, business entrepreneurs, and domestic and foreign researchers in academia, business, and government will use statistics from AIES.

More information regarding the AIES can be found in the Information Collection Request approved by the Office of Management and Budget on February 7, 2024 at the following link: https://www.reginfo.gov/​public/​do/​PRAViewICR?​ref_​nbr=​202310-0607-003

The ABS provides information on selected economic and demographic characteristics for businesses and business owners by sex, ethnicity, race, and veteran status. Further, the survey measures research and development for microbusinesses, new business topics such as innovation and technology, as well as other business characteristics. The ABS includes all nonfarm employer businesses filing Internal Revenue Service (IRS) tax forms as individual proprietorships, partnerships, or any other type of corporation, with receipts of $1,000 or more. The ABS is sponsored by the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation (NSF) and conducted by the Census Bureau.

More information regarding the ABS can be found in the Information Collection Request approved by the Office of Management and Budget on April 24, 2023 at the following link: https://www.reginfo.gov/​public/​do/​PRAViewICR?​ref_​nbr=​202301-0607-003 .

The Business and Professional Classification Report collects one-time data on a firm's type of business activity from a sample of businesses that were recently assigned Federal Employer Start Printed Page 20630 Identification Numbers or recently added to the scope of the Census Bureau's current business surveys. The data are used to update the sampling frames for our current business surveys. Additionally, the business classification data will help ensure businesses are directed to complete the correct report in the economic census.

More information regarding the Business and Professional Classification Report can be found in the Information Collection Request approved by the Office of Management and Budget on September 15, 2021 at the following link: https://www.reginfo.gov/​public/​do/​PRAViewICR?​ref_​nbr=​202105-0607-002 .

The BERD collects annual data on spending for research and development activities by businesses. The BERD collects foreign as well as domestic spending information, more detailed information about the R&D workforce, and information regarding intellectual property from U.S. businesses. The Census Bureau collects and compiles this information in accordance with a joint project agreement between the National Science Foundation (NSF) and the Census Bureau. The NSF posts the BERD information results on their website.

More information regarding the BERD can be found in the Information Collection Request approved by the Office of Management and Budget on December 15, 2021 at the following link: https://www.reginfo.gov/​public/​do/​PRAViewICR?​ref_​nbr=​202108-0607-005 .

Notwithstanding any other provision of law, no person is required to respond to, nor shall a person be subject to a penalty for failure to comply with a collection of information subject to the requirements of the Paperwork Reduction Act (PRA) unless that collection of information displays a currently valid Office of Management and Budget (OMB) control number. In accordance with the PRA, 44 U.S.C. chapter 45 , OMB approved the surveys described in this notice under the following OMB control numbers: AIES, 0607-1024; ABS, 0607-1004; Business and Professional Classification Report, 0607-0189; and BERD, 0607-0912.

Based upon the foregoing, I have directed that the current mandatory business surveys be conducted for the purpose of collecting these data.

Robert L. Santos, Director, Census Bureau, approved the publication of this notice in the Federal Register .

Dated: March 19, 2024.

Shannon Wink,

Program Analyst, Policy Coordination Office, U.S. Census Bureau.

[ FR Doc. 2024-06226 Filed 3-22-24; 8:45 am]

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National Center for Science and Engineering Statistics

• All previous cycle years

The ABS is the primary source of information on research and development among for-profit businesses operating in the United States with one to nine employees. The ABS also collects data on innovation, technology, intellectual property, and financing from U.S.-based companies of all sizes.

Survey Info

• tag for use when URL is provided --> Methodology
• tag for use when URL is provided --> Data
• tag for use when URL is provided --> Analysis

The ABS collects data on research and development (for businesses with one to nine employees), innovation, technology, intellectual property, and business owner characteristics, with additional rotating content that changes from year to year.

Areas of Interest

• Research and Development
• Innovation and Global Competitiveness

Survey Administration

The ABS is cosponsored by the National Center for Science and Engineering Statistics and the Census Bureau.

Survey Details

• Data Tables (PDF 2.7 MB)

Featured Survey Analysis

Microbusinesses Performed $6.1 Billion of R&D in the United States in 2021

ABS Overview

Data highlights, microbusiness domestic r&d performance increased 35% between 2018 and 2021, whereas domestic r&d costs increased 26% over this same period.

Methodology

Survey description, survey overview (2022 survey cycle: data year 2021).

The Annual Business Survey (ABS) is the primary source of information on research and development (R&D) expenditures for nonfarm, for-profit, businesses operating in the United States with one to nine employees. The ABS also collects data on innovation-related data, globalization, and business owner characteristics from nonfarm, for-profit, businesses operating in the United States with at least one employee.

Data collection authority

The 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 0607-1004, expiring 31 May 2025.

Major changes to recent survey cycle

Modules were added on Goods, Services, and Business Processes and Technology; Design and Intellectual Property; and Domestic and Foreign Transactions (Globalization). Five new questions were added, and one question was removed in the Coronavirus Pandemic Impact on R&D and Business Activities module. Questions on capital expenditures were added to the R&D module. A question was added on owner disability in the owner demographics module.

Key Survey Information

Initial survey year.

Calendar year 2017; for innovation, the reference period was 2015–17.

Reference period

Calendar year 2021; for innovation, the reference period was 2019–21.

Response unit

Nonfarm businesses in the United States.

Sample or census

Sample survey of for-profit companies with a U.S. presence engaged in the mining, utilities, construction, manufacturing, wholesale trade, retail trade, or services industries.

Population size

Approximately 4,900,000 employer businesses.

Sample size

Approximately 300,000 employer businesses.

Key variables

Key variables of interest are listed below.

• R&D performance
• 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, wages, and fringe benefits)
• Coronavirus impact on R&D
• Demographic and entrepreneurial characteristics of the business owner
• Indicators of innovation
• Design and intellectual property
• Globalization

Survey Design

Target population.

The target population consists of all for-profit nonfarm companies that are physically located in the United States, that have at least one establishment classified as being an in-scope sector based on the North American Industry Classification System (NAICS), and that was in business during the survey reference year and data collection period.

Sampling frame

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

Sample design

The ABS has a systematic stratified sampling design that uses simple random sampling within strata. Stratification is based on the NAICS industry code. Companies were selected with certainty if they are known R&D performers with one to nine employees, 500 or more employees, or meet sampling stratum-specific cutoffs for receipts and payroll.

Data Collection and Processing

Data collection.

The ABS collects data electronically.

Data processing

All data submitted by respondent companies are reviewed to ensure that data fields are complete and that data are internally consistent. Survey responses often include errors that require correction or unusual patterns that require validation. Automated edit checks are applied to improve the efficiency of data review and correction. Edit checks are designed to catch arithmetic errors and logically inconsistent responses (balance edits). The remaining automated edit checks are designed to flag outliers for further review (analytical edits). If additional information or data corrections are needed, respondents may be contacted to clarify or correct data. If additional information or corrected data cannot be obtained from respondents, data are imputed.

Estimation techniques

Estimates are produced from sums of weighted data (reported or imputed). Exceptions are described in detail in the tables containing relative standard errors and imputed rates (available upon request from the Survey Manager).

Survey Quality Measures

Sampling error.

Estimates of sampling errors associated with the ABS data tables are available from the Survey Manager upon request.

Coverage error

There can be both undercoverage error , where units are not included in the frame, and overcoverage error , where units included in the frame are actually out of scope for the population of interest. The ABS uses the prior-year Business Register to construct the frame, so any changes in businesses that would change the inclusion or exclusion of the business to the survey scope could be sources of coverage error. Prior to tabulation, survey units’ information is updated with the most recently available Business Register data to mitigate this source of error.

Nonresponse error

Unit nonresponse will be done by adjusting weighted reported and imputed data by multiplying each company's sampling weight by a nonresponse adjustment factor. Detailed descriptions of the adjustments for nonresponse will be available in the ABS data tables ( https://ncses.nsf.gov/surveys/annual-business-survey/ ).

Measurement error

Expected sources of measurement error include differences in respondent interpretations of the definitions of R&D activities 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. Error can also occur when respondents do not report dollar amounts correctly. Although quantitative metrics of measurement error are not available, there are ongoing efforts to minimize measurement error, including 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

Data availability.

Data produced from the ABS will be available at https://ncses.nsf.gov/surveys/annual-business-survey/ .

Data comparability

The ABS is a cross-sectional survey designed to produce annual estimates of R&D performance and related statistics. Some estimates from the ABS may not be directly comparable to prior ABS results due to changes in survey methodology. Sources of possible incomparability include changes to questionnaire wording and instructions, changes to data editing and tabulation, and changes to imputation and nonresponse adjustments.

Data Products

Publications.

ABS data will be published in NCSES InfoBriefs and data table reports in the Business and Industry R&D series ( https://www.nsf.gov/statistics/industry/ ).

Electronic access

Results from this survey are available on the NCSES website at https://ncses.nsf.gov/ . The ABS contains confidential data that are protected under Title 13 and Title 26 of the U.S. Code. Restricted microdata will be available at any of the 15 secure Research Data Centers administered by the Center for Economic Studies (CES) at the Census Bureau. Researchers interested in accessing microdata can apply for a restricted-use license by submitting 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 page on research opportunities 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. Per the Federal Cybersecurity Enhancement Act of 2015, the data are protected from cybersecurity risks through screening of the systems that transmit the data.

Technical Notes

Purpose . The Annual Business Survey (ABS) provides information on selected economic and demographic characteristics for businesses and business owners by sex, ethnicity, race, and veteran status. Further, the survey measures research and development (R&D) for microbusinesses, business topics such as innovation and technology, and other business characteristics. The ABS is conducted jointly by the Census Bureau and the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation (NSF). The ABS replaces the quinquennial Survey of Business Owners for employer businesses, the Annual Survey of Entrepreneurs, the Business R&D and Innovation for Microbusinesses Survey, and the Innovation section of the Business R&D and Innovation Survey.

The ABS is designed to incorporate new content each survey year based on topics of relevance. For the 2022 ABS, content includes company information, owner characteristics, research activities at nonprofit organizations, R&D, technology, innovation, financing, and management practices. R&D data are collected on the ABS for businesses with a W-2 employment range between one and nine employees.

Data collection authority . Title 13, U.S. Code, Sections 8(b), 131, and 182; Title 42, U.S. Code, Sections 1861–76 (NSF Act of 1950, as amended); and Section 505 within the America COMPETES Reauthorization Act of 2010, authorize this collection. Sections 224 and 225 of Title 13 require mandatory response. Office of Management and Budget (OMB) No. 0607-1004.

Survey sponsor. NCSES within NSF.

Survey collection and tabulation agent. The survey is conducted annually by the Census Bureau in accordance with an interagency agreement with NCSES within NSF.

Frequency . Annual.

Initial survey year . Calendar year 2017; for innovation, the reference period was 2015–17.

Reference period . Calendar year 2021; for innovation, the reference period was 2019–21.

Response unit . Nonfarm businesses in the United States.

Sample or census . Sample.

Population size . A total of 4.9 million employer firms; approximately 505,000 firms with one to nine employees and in North American Industry Classification System (NAICS) industries 31–33 (manufacturing), 42 (wholesale trade), 51 (information), 5413 (architectural, engineering, and related services), 5415 (computer systems design and related services), or 5417 (scientific research and development services) were in scope for the R&D module.

Sample size . 300,000 employer businesses.

Target population . Included are all nonfarm businesses filing Internal Revenue Service (IRS) tax forms as individual proprietorships, partnerships, or any type of corporation and with receipts of $1,000 or more. The target population included only companies that had paid employees according to the IRS Form 941 that covered 12 March 2022, are classified in an in-scope NAICS industry, were physically located in the United States, and were in business at the end of calendar year 2022. The ABS covers firms with paid employees only. The ABS is conducted on a company or firm basis rather than an establishment basis.

Sampling frame . The sampling universe was constructed from the final 2020 Business Register. The Business Register is the Census Bureau’s comprehensive database of U.S. businesses. Business Register data are compiled from a combination of business tax returns, data collected from the economic census, and data from other Census Bureau surveys. The Business Register includes sole proprietorships, partnerships, and corporations reporting business activity to the IRS on any one of the following IRS tax forms: 1040 (Schedule C), “Profit or Loss from Business” (Sole Proprietorship); 1065, “U.S. Return of Partnership Income”; 941, “Employer’s Quarterly Federal Tax Return”; 944, “Employer’s Annual Federal Tax Return”; or any one of the 1120 corporate tax forms.

The Business Register contains establishments that are out of scope for the ABS sample. These establishments are removed from the sampling universe. They include the following:

• Establishments engaged in the following NAICS industries:
• 110000, 111, or 112 - Agriculture production
• 482 - Railroads
• 491 - U.S. Postal Service
• 521 - Monetary authorities—central bank
• 525 - Funds, trusts, and other financial vehicles
• 813 - Religious, grantmaking, civic, professional, and similar organizations
• 814 - Private households
• 92 - Public administration
• Unclassified with legal form of organization as tax exempt or unknown
• Establishments located in American Samoa, Northern Mariana Islands, Guam, Puerto Rico, or the U.S. Virgin Islands
• Establishments belonging to foreign entities
• Government establishments
• Establishments with zero payroll and zero employment
• Establishments identified as out of business during prior year data review
• Single-unit establishments modeled as likely to be out of business using administrative data from the most recent monthly Business Register data sets

Information on industry classification, receipts, payroll, and employment was extracted from the Business Register during the frame construction.

The sample is also designed to estimate demographic characteristics of the business owners. To efficiently sample for demographic characteristics, a variety of sources of information are used to estimate the likelihood that a business is a woman- or minority-owned business. Administrative sources include the Decennial Census, the American Community Survey (ACS), and the Numident file, which is the Social Security Administration’s comprehensive database of information from Social Security applications. Individual business owners are identified through IRS K-1 filings for partnerships and corporations and from the Business Register for sole proprietorships. The owners are matched to the 2000 and 2010 Decennial Censuses to get race, sex, and ethnicity data; to the 2000–20 ACS; and to the Numident file (in that order) through a Protected Identification Key. Country of birth is also identified through the linkages to the ACS or Numident data. Each firm is then placed in one of the following eight strata describing characteristics of business owners for sampling: American Indian or Alaska Native, Asian, Black or African American, Hispanic, non-Hispanic White men, Native Hawaiian and Other Pacific Islander, publicly owned, and women owned. Businesses are assigned to one and only one stratum, with priority given to the less common race or ethnicity groups.

Sample design . The ABS frame is stratified by state, expected owner race or ethnicity, and industry and is systematically sampled within each stratum. A standard type of estimation for stratified systematic sampling is used. Large companies were selected with certainty based on volume of sales, payroll, or number of paid employees. Certainty cases have a selection probability of 1, a sampling weight of 1, and represent only themselves. Specifically for the 2022 ABS, firms were selected with certainty based on the following criteria:

• Firms in NAICS 5415 or 5417 with expected employment of fewer than 10 employees that reported at least $500,000 in R&D expenses in a prior year ABS,
• Firms in NAICS 5413, 31, 32, 33, 42, or 51 with expected employment of fewer than 10 employees that reported at least $50,000 in R&D expenses in a prior year ABS,
• Firms with more than 500 employees, or
• Firms larger than stratum-specific payroll and receipt cutoffs.

The certainty cutoffs vary by sampling stratum, and each stratum is sampled at varying rates, depending on the number and size of firms in a particular stratum.

The remaining frame is subjected to stratified systematic random sampling. Sampling rates vary by strata and are determined by the following calculations. Note that a systematic sample uses take rate to sample, and the sampling rate is 1/take rate.

The ABS sample consisted of 300,000 businesses. There were 46,000 selected with certainty. The certainty portion of the sample consisted of

• 5,000 with sufficient R&D expenses in previous cycles of the ABS,
• 17,000 with 500 or more employees,
• 16,000 with payroll above the stratum cutoff, and
• 8,000 with receipts above the stratum cutoff. (Note that payroll cutoffs are applied first so cases above both cutoffs appear in payroll count.)

The remaining 254,000 noncertainty cases were selected using the systematic stratified random sample selection. The maximum sample weight was 40.

Data Collection and Processing Methods

Data collection . Prior to mailing the survey, certain businesses selected were determined to be out of scope and were not contacted. The survey was mailed to 300,000 employer businesses in July 2022. Businesses were sent a letter informing them of their requirement to report. The letter also provided instructions on how to access the survey and submit online. There were three mail follow-ups conducted to increase response. Additionally, the Census Bureau conducted e-mail follow-ups to respondents who entered the electronic system but did not submit the questionnaire. The collection period closed in January 2023.

Mode . The 2022 ABS was collected using a Web-based survey instrument.

Check-in rate . The check-in rate is defined as the unweighted number of surveys that were submitted online by in-scope companies, divided by the unweighted total number of all in-scope companies in the sample. Response to individual questions did not factor into this metric. At the close of the collection period in January 2023, there were 184,000 responses submitted (62% of the sample).

There were an additional 1,900 businesses that contacted the Census Bureau to indicate that the business was no longer in operation or had been sold for the reference year via the call center.

Businesses selected to report R&D represented 39% of those mailed. Of the businesses mailed and selected to report R&D, 71,000 businesses (or 65%) submitted responses.

Unit response rate (URR). The URR is the unweighted number of responding companies for the survey. For the ABS, response is defined as a company providing the number of owners, number of paid owners, and number of employees or a company responding that it ceased operations prior to 2021.

For the ABS, the URR was 67.0%. The URR for businesses eligible to report the R&D module was 70.3%.

Item r esponse r ates (IRR) . The 2022 ABS collected data on approximately 650 variables, and the distribution of values reported by sample companies is highly skewed. Thus, rather than report unweighted item response rates, total quantity response rates are calculated, which are based on weighted data. The survey skip patterns vary for respondents; therefore, it can be impossible to know an exact denominator for item response calculations.

Total quantity response rate (TQRR). For a given published estimate other than count or ratio estimates, TQRR is the percentage of the weighted estimate based on data that were reported by units in the sample or on data that were obtained from other sources and were determined to be equivalent in quality to reported data and weighted only by sampling but not nonresponse weights. The TQRR for total sales in the United States in 2020 was 72.6%.

Total quantity nonresponse rate (TQNR). For a given published estimate, TQNR, defined as 100% minus TQRR, is calculated for each tabulation cell from the ABS, except for cells that contain count or ratio estimates. TQNR measures the combined effect of the procedures used to handle unit and item nonresponse on the weighted ABS estimate. Detailed imputation rates are available on request.

Data editing . Prior to tabulating the data, response data were reviewed and edited to correct reporting errors. R&D data were tabulated for records reporting $50,000 or more in R&D expenditures.

Additionally, R&D data were only tabbed for records classified in the following NAICS industries:

• 31–33 - Manufacturing
• 42 - Wholesale trade
• 51 - Information
• 5413 - Architectural, engineering, and related services
• 5415 - Computer systems design and related services
• 5417 - Scientific research and development services

Survey analysts reviewed the R&D reported by the survey respondents. Research was done by evaluating the reported business descriptions, reported R&D-to-sales ratio, and company website information. The majority of corrections involved false-positive reports or data reported using incorrect units (such as whole dollars instead of thousands of dollars). For NAICS industries 5415 and 5417, it is difficult to differentiate R&D from other technical work based solely on company website information. Due to this difficulty and the large number of companies sampled in these industries, it was not feasible to review each case individually; thus, relatively few corrections were made for false-positive reports. All cases were reviewed in these industries that had greater than $50,000 in R&D expenses.

Additional data errors were detected and corrected through mass corrections and an automated data edit system designed to review the data for reasonableness and consistency. The editing process interactively performed corrections by using standard procedures to fix detectable errors. Quality control techniques were used to verify that operating procedures were carried out as specified.

Unit n onresponse. Unit nonresponse is handled by adjusting weighted reported data as follows. Each company’s sampling weight is multiplied by a nonresponse adjustment factor. To calculate the adjustment factors, each company in the sample that is eligible for tabulation is assigned to one (and only one) adjustment cell. The adjustment cells are based on employment size and NAICS sector. For employment size, there are five categories: 1–4 employees, 5–9 employees, 10–49 employees, 50–249 employees, and 250 or more employees. For a given adjustment cell, the nonresponse adjustment factor is the ratio of the sum of the sampling weights for all companies in the cell to the sum of the sampling weights for all companies in the cell with reported data. The nonresponse adjustment factor for adjustment cell h was calculated as follows:

r is the respondents (partial and complete),

nr is the nonrespondents ,

wgt is the original sampling weight value,

h is the nonresponse adjustment cell, and

NAF h is the nonresponse adjust factor for cell h .

For the nonresponse adjustment, a business is considered a respondent if it provided the number of owners, number of paid owners, and number of employees. Businesses that responded they ceased operations prior to 2021 are excluded from nonresponse adjustments as out of scope.

Tabulation. Although as many firms as possible were identified as out of scope during sampling, additional out-of-scope firms were identified with either response or updated administrative data not available at the time of sampling. These 33,000 firms were removed for tabulations and include

• Firms reporting zero employment,
• Firms that responded as having gone out of business before 2021,
• Nonprofit organizations,
• Firms that responded as being owned by a domestic parent company, and
• Firms with unclassified NAICS industry.

Industry c lassification . The industry classifications of firms are based on the 2017 NAICS ( https://www.census.gov/naics/ ). Firms with more than one domestic establishment are assigned a single industry classification using a hierarchal system based on the largest payroll sector, largest payroll 3-digit NAICS (within the largest sector), largest payroll 4-digit NAICS (within the largest 3-digit), and largest payroll 6-digit NAICS (within the largest 4-digit). For tabulation, industry classification was based on administrative data for 2017.

Geography . Firms with establishments operating in more than one state are tabulated as unclassified geography and counted only once in state and national totals.

Variance e stimation . The ABS uses the delete-a-group jackknife variance estimator. Note that certainty cases do not contribute to the sampling variance. The delete-a-group jackknife variance estimator requires that every sampling stratum contains at least two sampled firms. Sampling strata that do not meet this requirement are collapsed as needed to create a new set of variance estimation strata that satisfies this requirement.

Data tables showing relative standard errors are available on request from the Survey Manager.

The estimates produced from the ABS are subject to both sampling and nonsampling errors.

Sampling error . The sampling error is described above in the variance estimation section.

Coverage error . Coverage error occurs when the frame fails to completely enumerate the population of interest. There can be both undercoverage error , where units are not included in the frame, and overcoverage error , where units included in the frame are actually out of scope for the population of interest. The ABS uses the prior-year Business Register to construct the frame, so any changes in businesses that would change the inclusion or exclusion of the business to the survey scope could be sources of coverage error. Prior to tabulation, survey units’ information is updated with the most recently available Business Register data to mitigate this source of error.

Non sampling error . All surveys and censuses have nonsampling errors. Nonsampling errors are attributable to various sources, such as the inability to obtain information for all cases in the universe, imputation for missing data, data errors and biases, mistakes in recording or keying data, errors in collection or processing, and coverage problems.

Although explicit measures of the effects of these nonsampling errors are not available, adjustments are made to the published relative standard errors to account for errors associated with imputation of missing data. It is believed that most of the important operational and data errors were detected and corrected through an automated data edit designed to review the data for reasonableness and consistency. Quality control techniques were used to verify that operating procedures were carried out as specified.

Measurement error . The most common source of measurement error was reporting in different units (e.g., reporting whole dollars rather than thousands of dollars). Variations in respondent interpretations of the definitions of R&D activities are of particular concern, and error can occur when respondents do not report dollar amounts correctly. Little public information exists for most of the small businesses surveyed by the ABS, so it is difficult to determine whether companies are reporting R&D that satisfies the survey's definitions, particularly where the development of software and Internet applications are concerned. Although no metric of measurement error is produced, 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, telephone interviews and consultations with respondents, and post-survey evaluations.

Data Comparability

Some estimates from the 2022 ABS may not be directly comparable to prior ABS results due to changes in survey methodology. Sources of possible incomparability include changes to questionnaire wording and instructions, changes to data editing and tabulation, and changes to imputation and nonresponse adjustments.

Changes in survey coverage and population. There were no changes to survey coverage and population for reference year 2021 (ABS 2022).

Changes to questionnaire wording and instructions . The survey section that collected information on R&D from businesses (section D) had nearly identical question wording and instructions for both the ABS 2021 and the ABS 2020 questionnaires. The 2022 ABS collected additional detail from businesses on the location of R&D performance and explicitly highlighted the concept of “domestic R&D performance.” For the 2022 ABS detailed questions about R&D expenditures (types of costs, funding sources, and R&D categories) were tied to domestic R&D performance (a subset of total R&D costs), whereas previous ABS questionnaires asked similar questions tied to total R&D costs.

The following are survey changes in the questionnaire from ABS 2021 to ABS 2022; question number references are in reference to the ABS 2022:

• New question: B.15 Owner Disability (added for all owners)
• New question: C.11 Research Performance by Type of Cost
• New questions: C.17–C.19 Additional questions on Capital Expenditures for Research Activities at Nonprofit Organizations
• New questions: D.10–D.12 Additional questions on Capital Expenditures for businesses with 1–9 employees
• New question: D.18 State Tax Credit for Research Activities
• New section E: Goods, Services, and Business Processes and Technology
• New section F: Design and Intellectual Property
• New section G: Domestic and Foreign Transactions
• Revised section H: Coronavirus Pandemic Impact on Research and Development and Business Activities
• Removed question: H.5 Outsourcing R&D Expenditures Due to the Coronavirus Pandemic
• New question: H.5 Changing R&D Payment Due to the Coronavirus Pandemic
• New question: H.6 Effect of Coronavirus Pandemic on Business Sales
• New question: H.7 Financial Health of the Business
• New question: H.8 Outstanding Debt for the Business
• New question: H.9 Level of Operations During the Coronavirus Pandemic

Changes in reporting procedures or classification. There were no changes to reporting procedures or classification for data year 2021.

Changes to data editing and tabulation . For data collected in the R&D section of the ABS, every response with $50,000 or more in R&D costs was reviewed for reasonableness. All positive R&D cases were reviewed in industries with high rates of false-positive reports. Outside of the review for potential false-positive R&D cases, the editing of R&D data was performed similarly in 2020 and 2021. There have been no major changes to the edits from year to year.

Data collected in the innovation section of the ABS were edited similarly in 2018 and 2019, but the estimates for product innovation were tabulated differently. For 2017, a business must have responded positively to both the product innovation question and the subsequent business product innovation question (new to market or new to business) to be considered a product innovator. For 2021 and 2022, only a positive response to the question regarding new or improved goods or services was required to be tabulated as a product innovator.

Changes in imputation methods. In 2019, a change was made in how item nonresponse is treated in the ABS. Item nonresponse occurs when a company responds to the survey but leaves some items blank. In 2018, item nonresponse was treated using a combination of mode and donor imputation. For 2019 and future years (including 2021), no imputation was performed to treat item nonresponse, and missing items were included as no or zero in the estimates. For most of the estimates in 2019 (91%), this change in methods did not yield a change in the estimates. For an additional 9% of estimates, there was a difference in the estimate; the difference, however, was not statistically significant. In 2021, the imputation method was updated to exclude out-of-scope firms as donors and recipients. In previous ABS years, all sampled firms were included in imputation and out-of-scope firms were later removed.

Changes in collection methods . During the 2022 ABS collection period, a single letter was mailed to respondents using U.S. Postal Service Priority Mail. For the 2022 ABS, the third follow-up used First Class Mail.

Definitions

• Affi l iated (company or business). An entity that is owned 10% or more (based on voting interest or an equivalent interest) directly or indirectly by your company.
• Business processes . Business process includes the following: (1) methods for producing goods or providing services, (2) distribution and logistics, (3) marketing and sales, (4) information and communication systems, (5) administration and management activities, and (6) product and business process development (including activities to identify, develop, or adapt products or a firm’s processes).
• Core production activity. This term refers to your primary business activities. For manufacturing companies, core production typically involves production of physical goods. For service companies and other companies, core production refers to the main services or activities provided by your business, such as information and communications technology services, marketing services.
• Domestic or U .S.-located . Refers to a location in any of the U.S. 50 states and the District of Columbia.
• Employment . Paid employment consists of full- and part-time employees, including salaried officers and executives of corporations who were on the payroll in the pay period including March 12. Included are employees on sick leave, holidays, and vacations; not included are proprietors and partners of unincorporated businesses.
• Ethnicity . Based on OMB’s guidance, there are two minimum categories for ethnicity: Hispanic or Latino and Not Hispanic or Latino. OMB considers race and Hispanic origin to be two separate and distinct concepts. Hispanics and Latinos may be of any race.
• Exported goods. Value of goods, including the value of equipment, supplies, materials, etc. This should equal the amounts reported in the Automated Export System’s Electronic Export Information filed with U.S. Customs and Border Protection plus the cost of transporting the goods to customers located in foreign destinations (i.e., outside the United States).
• Exported services. An exported service is a service-related product (i.e., services performed, including digital service, license agreement) that is sold or transferred to, or performed for, customers (individual, government, business establishment, etc.) located in foreign destinations (i.e., outside the United States).
• Firm . A business organization or entity consisting of one or more domestic establishment locations under common ownership or control.
• Foreign affiliate. A foreign affiliate is an entity located outside the United States that is owned at least 10% (based on voting interest or an equivalent interest) directly or indirectly by the U.S. reporter.
• Foreign parent (of a U.S.-located business). The first entity outside the United States in an affiliate’s ownership chain that has a direct or indirect investment interest of more than 50% of the affiliate’s voting securities.
• Goods . Usually a tangible object (such as smartphone, furniture, or packaged software) but also includes digital goods (such as downloadable software, music, and film). Exclude the simple resale of new goods and changes of a solely aesthetic nature.
• Imported goods. The value of goods purchased from customers located in foreign destinations (i.e., outside the United States) as indicated in import declarations filed with the U.S. Customs and Border Protection.
• Imported services. An imported service is a service-related product (i.e., service performed, including digital service, license agreement) that is purchased from customers located in foreign destinations (i.e., outside the United States).
• Innovation. A business innovation is a new or improved product or business process (or combination thereof) that differs significantly from the firm’s previous products or business processes and that has been introduced on the market or brought into use by the firm.
• Intellectual p roperty . Includes patents, processes, and trade secrets; books and music; trademarks; recorded performances and events, such as radio and television programs and motion pictures; broadcast and recorded live performances and events and their content; general use computer software; franchise fees; and other (e.g., digital media).
• Noise i nfusion . A method of disclosure avoidance in which values are perturbed prior to tabulation by applying a random noise multiplier to the magnitude data, such as the sales and receipts for all firms. Disclosure protection is accomplished in a manner that causes the vast majority of cell values to be perturbed by, at most, a few percentage points.
• North American Industry Classification System (NAICS) . NAICS is the standard used by federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. This system is used by the United States, Canada, and Mexico.
• Race . The data on race were derived from answers to the race question. Race data are collected in accordance with the guidelines provided by OMB, and these data are based on self-identification. The racial categories included in the questionnaire generally reflect a social definition of race recognized in this country and are not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race question include race and national origin or sociocultural groups. OMB requires that race data be collected for a minimum of five groups: White, Black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander. Respondents may report more than one race.
• Receipts . Includes the total sales, shipments, receipts, revenue, or grants for domestic operations, excluding foreign subsidiaries.
• Research and d evelopment (R&D) . R&D is planned, creative work aimed at discovering new knowledge or devising new applications of available knowledge. This includes basic research, applied research, and development (see definitions below). R&D includes both direct costs, such as salaries of researchers, and administrative and overhead costs clearly associated with the company’s R&D. However, R&D does not include expenditures for routine product testing, quality control, and technical services unless they are an integral part of an R&D project. R&D also does not include market research; efficiency surveys or management studies; literary, artistic, or historical projects, such as films, music, or books and other publications; and prospecting or exploration for natural resources.
• Basic r esearch . Activities aimed at acquiring new knowledge or understanding without specific immediate commercial applications or uses.
• Applied r esearch . Activities aimed at solving a specific problem or meeting a specific commercial objective .
• Development . Systematic work, drawing on research and practical experience and resulting in additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.
• R&D activity in software includes
• Software development or improvement activities that expand scientific or technological knowledge
• Construction of new theories and algorithms in the field of computer science
• R&D activity in software excludes
• Software development that does not depend on a scientific or technological advance, such as
• Supporting or adapting existing systems,
• Adding functionality to existing application programs,
• Routine debugging of existing systems and software, and
• Creation of new software based on known methods and applications.
• Conversion or translation of existing software and software languages; and
• Adaptation of a product to a specific client, unless knowledge that significantly improved the base program was added in that process.
• Services . Intangible activities, such as retailing, insurance, educational courses, air travel, consulting, etc.; also includes digital services. (Exclude the simple resale of new services.)
• Sex . For the purposes of the ABS, sex refers to a person’s biological sex. The sex question wording very specifically intends to capture a person’s biological sex and not gender.
• Unaffiliated (company or business). Entity that is owned less than 10%, directly or indirectly, by your company (i.e., independent contractors and suppliers).
• Worldwide s ales . Worldwide and domestic sales and operating revenues, including grants.

Technical Tables

• All Formats (ZIP 186 KB)
• Excel (ZIP 22 KB)
• PDF (ZIP 163 KB)

Questionnaires

View archived questionnaires, key data tables.

Recommended data tables

Total R&D costs

Domestic r&d performed by the company, domestic r&d employees, domestic employees, data tables.

• All Formats (ZIP 6.4 MB)
• Excel (ZIP 777 KB)
• PDF (ZIP 5.6 MB)

Aggregate R&D estimates

Tax credit for research activities, product innovation, business process innovation, new-to-market product innovation, new-to-business product innovation, product or business process innovation, number of domestic employees for companies with 1–9 employees, aggregate sales estimates, number of companies, sales and revenues, sources of domestic sales and revenue, impact of coronavirus on r&d, companies performing or funding r&d on select technologies, companies using select technologies, source of technology capabilities, design activities, intellectual property protection, activities conducted by domestic or foreign unaffiliated or affliated companies, companies and manufacturing activities, general notes.

This report provides data from the 2022 Annual Business Survey (ABS) (data year 2021). The ABS is the primary source of data on research and development of for-profit, nonfarm businesses with one to nine employees operating in the 50 U.S. states and the District of Columbia. The ABS also collects data on innovation, technology, intellectual property, and business owner characteristics of business of all sizes. The ABS is designed to incorporate new content each survey year based on topics of relevance. The 2022 ABS is the fifth year of the ABS. The survey is conducted annually by the Census Bureau for the National Center for Science and Engineering Statistics within the National Science Foundation.

The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY23-0394).

This report is initially published with a selection of tables containing the core data of the survey. The report will be updated with additional tables as more detailed data become available. In some instances, the initial selection of tables may also be updated from a preliminary version to add further data.

The first set of tables in this report, 1–30, released in October 2023. 

The second set of tables in this report, 31–85, released in June 2024.

Acknowledgements and Suggested Citation

Audrey E. Kindlon of the National Center for Science and Engineering Statistics (NCSES) developed and coordinated this report under the guidance of Amber Levanon Seligson, NCSES Program Director, and under the leadership of Emilda B. Rivers, NCSES Director; Christina Freyman, NCSES Deputy Director; and John Finamore, NCSES Chief Statistician. In partnership with NCSES, the Census Bureau conducted the survey and prepared the tables. NCSES staff members who made significant contributions include Gary Anderson, Jock Black, and Timothy Wojan.

The Census Bureau, under National Science Foundation interagency agreement number NCSE-1748418, collected, processed, evaluated, and tabulated the data for this report. The Annual Business Survey is conducted within the Economic Directorate of the Census Bureau under the direction of Nick Orsini, Associate Director for Economic Programs, and Stephanie Studds, Assistant Director for Economic Programs.  

The data were prepared in the Economic Reimbursable Surveys Division under the direction of Kevin Deardorff, Division Chief, and Aneta Erdie, Assistant Division Chief. This work was performed under the supervision of Patrice Hall, assisted by John Clark, Lakitquana Leal, and Gail White, with staff assistance from Concepcion Arenas Alvarez, Ahmad Bakhshi, Elaine Emanuel, Mary Frauenfelder, Aaron Finkle, Samantha Hernandez, James Jarzabkowski, Jessica Welch, and Tesfay Weldu. Additional support, including table creation and subject matter expertise, was provided by Brandon Shackelford.

Mathematical and statistical techniques were provided by the Economic Statistical Methods Division under the direction of James Hunt, Assistant Division Chief. This work was performed under the supervision of Roberta Kurec, assisted by Sandra Peterson, and Dhanapati Khatiwoda, with staff support from Taylor Beebe, Alexandra Abzún Cadenas, Charles Champion, and Daniel Cordes. 

Data collection procedures and operations were provided by the Economic Management Division under the direction of Lisa Donaldson, Division Chief, and Michelle Karlsson, Assistant Division Chief. The staff of the National Processing Center performed mailout preparation, respondent assistance, and correspondence processing. Project management support was provided by Laura Hardesty and Aja Madison.   

Development and coordination of the computer processing system was provided by the Economic Application Division under the direction of Sumit Khaneja, Division Chief and Olajumoke Oyewole, Assistant Division Chief. This work was performed by Marilyn Balogh, Michael Feldman, David Gonzalez, Chakravarthy Sharad, and Joseph Talbot.   

National Center for Science and Engineering Statistics (NCSES). 2024. Annual Business Survey: 202 2 (Data Year 20 2 1 ) . NSF 24-303. Alexandria, VA: National Science Foundation. Available at https://ncses.nsf.gov/surveys/annual-business-survey/2022 .

Featured Analysis

Definitions of research and development, related content, related collections, survey contact.

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National Center for Science and Engineering Statistics

• All previous cycle years

The BERD Survey is the primary source of information on research and development 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 domestically or abroad.

Survey Info

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The BERD Survey and its predecessors are the primary sources of information on research and development performed or funded by businesses within the United States since 1953. The BERD Survey was developed and is cosponsored by the National Center for Science and Engineering Statistics within the National Science Foundation and by the Census Bureau, which collects and tabulates data for the survey in accordance with an agreement between the two agencies. Results are used to assess trends in the performance and funding of business R&D. The annual survey examines a nationally representative sample of companies in manufacturing and nonmanufacturing industries. Its predecessors were the Survey of Industrial Research and Development (SIRD) (1953–2007), the Business R&D and Innovation Survey (BRDIS) (2008–16), and the Business Research and Development Survey (BRDS) (2017–18). Note that SIRD and BRDIS collected statistics for businesses with five or more employees. BRDS produced (and BERD produces) statistics for businesses with 10 or more employees. 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, although it is estimated that companies that performed or funded less than $50,000 of R&D accounted for a very small percentage of total domestic R&D. SIRD, BRDIS, and BRDS all collected data on the full range of R&D activities, but only BRDIS collected data on business innovation activities. Data on business innovation activities have been collected by the Annual Business Survey (ABS) since 2017. Statistics on the R&D activities of businesses with one to nine employees are also collected by the ABS.

Areas of Interest

• Research and Development
• Innovation and Global Competitiveness

Survey Administration

The BERD Survey is cosponsored by the National Center for Science and Engineering Statistics and the Census Bureau.

Survey Details

• Survey Description (PDF 133 KB)
• Data Tables (PDF 6.8 MB)

Featured Survey Analysis

Businesses Spent Over a Half Trillion Dollars for R&D Performance in the United States During 2020, a 9.1% Increase Over 2019

BERD Survey Overview

Data highlights, data show that labor costs in 2020 account for half or more of the r&d performance in the united states for most industries..

The estimated average annual compensation of business R&D employees in 2020 was $155,000 in salaries, wages, and fringe benefits.

Methodology

Survey description, survey overview (2020 survey cycle).

The Business Enterprise Research and Development Survey (BERD) and its immediate predecessors the Business R&D and Innovation Survey (BRDIS) and the Business Research and Development Survey (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.

Major changes to recent survey cycle

To minimize reporting burden especially for smaller companies, survey items are rotated on and off the survey on an odd- and even-numbered year schedule. Statistics on intellectual property, patents, and technology transfer activities for 2020 are available in the full set of data tables. Rotated off of the survey for 2020 were questions on activities with academia, federal R&D by government agency, R&D by application area, and R&D performed by others by type of performer. Statistics on these items will be available again for 2021.

Key Survey Information

Initial survey year.

BERD data collection began for 2019. 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

Calendar year 2020.

Response unit

Companies with known positive R&D activity (approximately 20,500), known to have no R&D activity (approximately 2,200), and with unknown R&D activity (approximately 24,500).

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 manufacturing, mining, utilities, wholesale trade, transportation, information, or services industries.

Population size

A total of 1,140,000 companies.

Sample size

A total of 47,500 companies prior to data collection. The actual number of companies that remained within the scope of the survey between sample selection and tabulation was 44,500.

Key variables

Key variables of interest are listed below.

• Business activity codes based on the North American Industry Classification System (NAICS)
• Geographic location of domestic and foreign R&D performance of U.S.-based companies
• Industry coding based on NAICS
• R&D capital expenditures
• R&D performance (domestic and foreign R&D for U.S.-based companies)
• Sources of R&D funding
• Technology focus areas
• Total and R&D employment
• Type of R&D cost (e.g., salaries and fringe benefits)
• Type of R&D work (basic research, applied research, and development)
• Activities with academia (data collected for odd-numbered years)
• Federal R&D by funding government agency (odd years)
• R&D by application area (odd years)
• R&D performed by others by type of performer (odd years)
• Intellectual property (even years)
• Patents (even years)
• Technology transfer activities (even years)

Survey Design

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 (BR) serves as the primary input to the sampling frame. The BR is the Census Bureau’s comprehensive database of U.S. businesses. BR data are compiled from a combination of business tax returns, data collected from the economic census, and data from other Census Bureau surveys.

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 a NAICS-based industry code. 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

Data collection.

BERD uses Web reporting via the Census Bureau’s Centurion system with embedded electronic worksheets designed to ease respondent burden. Respondents have the option of downloading a PDF version of the questionnaire, but the overwhelming majority report via the online system (≥ 99%) and not 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

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 2020, RSEs for domestic R&D performance paid for by the company, paid for by others, and total were 0.76%, 0.30%, and 0.66%, 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 67% for 2020. 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

Data availability.

Statistics from BERD for 2019 and 2020 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 were 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 for years prior to 2018. 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 2019 estimates, they would have contributed approximately $90 million to overall R&D expenditures and would have added around 7,500 to the estimated number of U.S. companies with R&D expenditures. It is assumed that this group of companies would have contributed similar levels of R&D and number of companies to the 2020 estimates.

In survey year 2017, the employment threshold for inclusion in the target population, described above, was increased from 5 employees to the current threshold of 10 employees for international comparability.

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

Publications.

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

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 Federal Statistical Research Data Centers (FSRDC) administered by the Census Bureau. FSRDCs are partnerships between federal statistical agencies and leading research institutions. FSRDCs provide secure environments supporting qualified researchers using restricted-access data while protecting respondent confidentiality. Researchers interested in using the microdata can submit a proposal to the Census Bureau, which evaluates proposals based on their benefit to Census, scientific merit, feasibility, and risk of disclosure. To learn more about the FSRDCs and how to apply, please visit https://www.census.gov/about/adrm/fsrdc.html .

Technical Notes

Survey overview.

Purpose . The Business Enterprise Research and Development (BERD) Survey, successor to the Business Research and Development Survey (BRDS) (2017–18), the Business R&D and Innovation Survey (BRDIS) (2008–16), and the Survey of Industrial Research and Development (SIRD) (1953–2007), 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 (in the 50 states and the District of Columbia) or abroad.

Data collection authority . The information collected by the BERD Survey is solicited under the authority of the National Science Foundation (NSF) Act of 1950, as amended, and the America COMPETES Reauthorization Act of 2010. Response to this annual survey is mandatory and confidential; the Census Bureau collects the data under the authority of Title 13, Section 8, of the United States Code. The Office of Management and Budget (OMB) control number is 0607-0912.

Survey sponsors . The BERD Survey is cosponsored by the National Center for Science and Engineering Statistics (NCSES) within NSF and the Census Bureau.

Survey collection and tabulation agent . The survey is conducted annually by the Census Bureau in accordance with an interagency agreement with NCSES.

Frequency . Annual.

Initial survey year . BERD Survey data collection began for 2019. BRDS collected data for 2017–18, BRDIS collected data for 2008–16, and SIRD collected data for 1953–2007.

Most recent r eference period . Calendar year 2020.

Response unit. Company.

Sample or census. Sample.

Population size . 1,139,000 companies .

Sample size . 47,500 companies; the actual number of companies that remained within the scope of the survey between sample selection and tabulation was 44,500.

The survey is administered both to companies known to have performed R&D and to companies with no known history of R&D activity. The BERD Survey has been designed to provide detailed statistics on global and domestic R&D expenditures of companies located in the United States and on these companies’ R&D employees.

The survey is sent to a single coordinator within each company, but it is organized into sections that help the coordinator collect specific types of information from different experts (human resources, accounting, R&D managers, etc.) in the company. Foreign-owned companies are instructed to report only for company operations owned by the U.S. subsidiary and, for purposes of the survey, to treat the U.S. subsidiary’s foreign owners as if they were unrelated third parties.

Target Population

The target population for the BERD Survey consists of all for-profit companies that have 10 or more paid employees in the United States, that have at least one establishment located in the United States that is in business during the survey year, and that are classified in certain industries based on the 2017 North American Industry Classification System (NAICS), with a particular focus on those companies that perform R&D in the United States.

The Business Register, a Census Bureau compilation that contains information on more than 7.3 million establishments with paid employees, serves as the primary input to the sampling frame from which the BERD Survey sample is selected. For a given company with more than one establishment, the prior year’s annual payroll and employment data for its active establishments are summed to the company level.

Sampling Frame

The scope of the 2020 BERD Survey is limited to companies that (1) are in business primarily to make a profit; (2) are classified within a specific set of NAICS industries; (3) have 10 or more paid employees in the United States, based on employment on 12 March 2019; (4) have at least one establishment that is physically located in the United States and is in business at the end of calendar year 2020 (the time at which the Census Bureau finished the 2019 Business Register Processing); and (5) are not federally funded R&D centers.

Single-unit company records were extracted from the 2019 Business Register if the company had at least 10 paid employees in 2019 or, when employment information was unavailable, if the company’s 2019 payroll was greater than or equal to $500,000. Companies were removed from the sampling frame if their NAICS codes were designated as Agriculture, forestry, fishing, and hunting (NAICS 11), Postal service (NAICS 491), Educational services (NAICS 61), Private households (NAICS 814), or Public administration (NAICS 92) or if they were no longer in business or were nonprofits. Companies were also removed from the sampling frame if they were not located in the 50 U.S. states or the District of Columbia.

Records for active establishments from multiunit companies were extracted from the 2019 Business Register if the given establishment’s 2019 payroll was greater than zero or if the establishment employed at least one person in 2019. Prior to creating records for multiunit companies from these establishments, establishments classified as Postal service (NAICS 491), Private households (NAICS 814), or Public administration (NAICS 92) were removed, as were those that were not physically located in the 50 U.S. states or the District of Columbia. Unlike single-unit companies, establishments classified as Agriculture, forestry, fishing, and hunting (NAICS 11) or Educational services (NAICS 61) were not initially removed during the construction of multiunit company records. Establishments classified in NAICS 11 or NAICS 61 contributed to the classification of the multiunit companies, and their payroll could have been included in determining the company’s measure of size. From the resulting set of multiunit companies, companies were removed from the sampling frame if they had fewer than 10 paid employees or if the payroll associated with their nonprofit establishments was greater than the payroll of their for-profit establishments.

For each company on the sampling frame, a measure of size was assigned. The measure of size for a given company was based on R&D, if R&D data from the last 5 years were available from (1) BERD, (2) online financial databases, (3) the Report of Organization conducted as part of the Company Organization Survey (in years not ending in “2” or “7”) or as a supplement to the Economic Census (in years ending in “2” or “7”), or (4) qualified R&D expenses from the Internal Revenue Service (IRS). For all other companies, the measure of size was based on total annual payroll for 2019 from the Business Register.

Industry Classification for Sampling

Each company was assigned to 1 of 60 industry sampling strata based on the reported business segment in which the company performed the largest amount of total domestic R&D, as reported within the previous 5 years (2015–16 BRDIS, 2017–18 BRDS, and 2019 BERD), if available. If these business segment data were not reported for a given company, assignment was based on the NAICS codes of its establishments in the Business Register using the following method, with some adjustments made to account for vertical integration of related business activities within the company. The company was first assigned to the economic sector, defined by a two-digit NAICS code that accounted for the highest percentage of its aggregated annual payroll. Then the company was assigned to a subsector, defined by a three-digit NAICS code that accounted for the highest percentage of its annual payroll within the economic sector. Next, the company was assigned a four-digit NAICS code within the subsector, again based on the highest percentage of its aggregated annual payroll within the subsector. Finally, the company was assigned a six-digit NAICS code within the four-digit NAICS code, based on the highest percentage of its aggregated annual payroll within the four-digit NAICS code. Companies with an assigned six-digit NAICS code beginning with “11” or “61” were removed from the sampling frame at this point, and their R&D and associated data are not included in the tabulations. The industry used for sampling purposes was not necessarily the same code used for publication; see section “ Postsampling Industry Classification .”

Stratification of the Sampling Frame

Each company in an industry sampling stratum was further assigned to one of three R&D groups based on information about its prior domestic R&D activity: (1) companies with a positive value for the measure of size based on R&D ( known positive R&D group ), (2) companies with a zero value for the measure of size based on R&D ( known zero R&D group ), and (3) companies with unknown R&D activity ( unknown R&D group ). For the 2020 BERD Survey, there were 31,500 companies in the first group, 36,500 companies in the second group, and 1,071,000 companies in the third group, for a total of 1,139,000 companies ( table A-1 ).

Sample Selection

In the known positive R&D group, Pareto probability-proportional-to-size (PPS) sampling was used within each noncertainty industry stratum, where the probability of selection was proportional to the company’s measure of size. In the unknown R&D group, Pareto PPS sampling was used within most industry strata; simple random sampling (SRS) was used instead of Pareto PPS for industries in which the number of companies in the sampling frame was high and the likelihood of R&D was low. For both the known positive and unknown groups, a separate stratum was created for companies with fewer than 25 employees, regardless of industry. Pareto PPS sampling was used within these strata. In the known zero R&D group, a single Pareto PPS sample was selected across all industry strata. Each sampling stratum had a certainty and noncertainty portion ( table A-2 ). Across all three groups (known positive, known zero, and unknown), companies in select industries and companies that exhibited characteristics of having large R&D amounts, including those with the largest annual payroll, were selected for the sample with certainty (i.e., the probability of selection was equal to 1). The probability of selection for other companies in the known positive R&D and unknown R&D groups depended on their size, the number of companies selected, and the total size or number of companies in their strata. The number of companies selected was based on a coefficient of variation constraint on the estimated sample total for the stratum and was increased, if necessary, to ensure that the minimum probability of selection is 0.05 for the known positive R&D group and one of six values for the unknown R&D group: 0.004, 0.01, or 0.02 for Nonmanufacturing industries (NAICS other than 31–33) and Incomplete manufacturers (incomplete NAICS beginning with 3), depending on the population size and likelihood of R&D; 0.04 for Printing and related support activities manufacturing (NAICS 323), Furniture and related product manufacturing (NAICS 337), and Computer systems design and related services (NAICS 5415); 0.02 for the remaining Manufacturing (NAICS 31–33) industries; and 0.05 for the companies with fewer than 25 employees. For companies in the known zero R&D group, the probability of selection depended on their size and the number of companies selected. The number of companies selected was based on a coefficient of variation constraint and was increased, if necessary, to ensure that the minimum probability of selection is 0.02.

Once selected, each company was assigned a sampling weight equal to the reciprocal of its probability of selection for the sample. Companies that were selected for the sample with certainty were assigned sampling weights equal to 1, and companies that were selected using SRS or Pareto PPS sampling were assigned weights ranging from 1 to 250. A complete and detailed description of the sample design and estimation methodology is given in the annual BERD Survey methodology report available from the NCSES project officer.

Sample Size

Using the sample design parameters detailed above, a total of 47,500 companies were selected, of which 20,500 companies were in the known positive R&D group, 2,200 companies were in the known zero R&D group, and 24,500 companies were in the unknown R&D group ( table A-3 and table A-4 ). A complete and detailed description of the selection of additional sampling units is given in the annual BERD Survey methodology report available from the NCSES project officer.

During the survey’s annual contact update procedures, 150 large R&D performers from the 2019 sample were found that were not included on the 2020 sampling frame. The primary reasons for this are mergers, acquisitions, or other company structure changes that cause a difference between a company’s current Business Register ID and its prior year survey ID—in this case, its ID in the 2019 BERD file. To follow up with these companies, they were added to the 2020 sample with certainty, and 150 companies were mailed a survey letter. Because it was expected that many of these records would not contribute to 2020 BERD Survey tabulations due to changes in company structure, these companies are not included in sampling frame counts or sample sizes ( table A-5 ).

Data Collection and Processing Methods

Starting in the 2017 cycle, an initial letter was mailed to all companies instructing them to report via the Census Bureau’s Centurion data collection instrument. Paper questionnaires were mailed by respondent request only and during a later nonresponse follow-up for delinquent companies. For paper versus electronic response rates, see section “ Response by Mode .”

Questionnaires

Beginning in the 2017 cycle, all companies completed the same questionnaire, BRD-1, which combined the standard form BRDI-1 and the abbreviated form BRDI-1(S) used in prior cycles ( table A-6 ). Companies that reported less than $1 million in R&D paid for by the company or less than $1 million in R&D funded by others completed abbreviated worksheet(s) in lieu of more detailed questions asked of companies with $1 million or more in R&D. As was the case in previous cycles, some companies with decentralized records requested a special reporting arrangement with the Census Bureau. Under this arrangement, the survey form was mailed to multiple operating units within the same company, and each Alternate Reporting Unit (ARU) completed the survey individually. The data for these ARUs were also tabulated separately in published estimates and were not consolidated at the company level ( table A-7 ).

Because of the potential compartmentalization of organizational knowledge within companies (particularly in larger companies), the BERD Survey questionnaire was organized into sections based on the subject matter of the questions. These sections included the following:

Section 1. Company information. Includes basic questions about company ownership, lines of business, sales, and employee data.

Section 2. R&D paid for by your company. Includes geographic location and accounting questions about the company’s R&D expenses.

Section 3. Costs paid for by others. Includes accounting questions about R&D paid for by others, such as the company’s customers or grant-giving organizations.

Section 4. Capital expenditures. Includes questions on capital expenditures for R&D.

Section 5. Management and strategy of R&D. Includes questions related to the characteristics and focus of the company’s R&D. This section was targeted toward company employees responsible for managing R&D departments or programs.

Section 6. Human resources. Includes questions related to the human resources involved in the company’s R&D activities.

Section 7. Intellectual property and technology transfer. Includes questions on the company’s production, use, acquisition, and disposition of intellectual property related to science and technology (S&T) , with a focus on patents.

Section 8 . Tax t opics . Includes questions on filing federal and state tax credits for research activities.

For specific differences among the BERD Survey questionnaires, see section “ Data Comparability (Changes) .”

Response Rates

Unit response rates.

Of the companies surveyed for the 2020 survey, 31% did not submit any response, and an additional 2% did not provide enough information to be treated as responses. Nonresponse studies are conducted periodically to assess reasons for nonresponse and possible nonresponse bias. Three metrics used by NCSES and the Census Bureau to measure unit response to the BERD Survey were check-in rates, unit response rates (URRs), and coverage rates.

Check-in rate. The check-in rate is defined as the unweighted number of surveys that were either submitted online or mailed in by in-scope companies, divided by the unweighted total number of all in-scope companies in the sample. Response to individual questions did not factor into this metric.

Coverage rate. BERD Survey managers track a coverage rate that is a weighted measure of survey response based on the measure of size at the time of sample selection. The coverage rate measures how much of the weighted measure of size for in-scope companies in the sample is accounted for by respondents to the survey.

Unit response rate (URR). The URR is the unweighted number of responding companies with positive data for at least one of the survey’s key items (i.e., worldwide R&D expenses or R&D costs funded by others, worldwide or domestic sales, or worldwide or domestic employees), divided by the unweighted total number of in-scope companies in the sample.

For the 2020 BERD Survey, the check-in rate was 69%, and the URR was 67%. The coverage rate for the 2020 BERD Survey was 92% for the known positive R&D group, 65% for the unknown R&D group, and 78% for the known zero R&D group ( table A-8 and table A-9 ).

Item Response Rates

The BERD Survey collects data for over 500 variables, and the distribution of values reported by sample companies is highly skewed. Thus, rather than report unweighted item response rates, total quantity response rates are calculated, which are based on weighted data.

Total quantity response rate (TQRR). For a given published estimate other than count or ratio estimates, TQRR is the percentage of the weighted estimate based on data that were reported by units in the sample or on data that were obtained from other sources and were determined to be equivalent in quality to reported data. The TQRR for total R&D performed in the United States in 2020 was 70.

Total quantity nonresponse rate (TQNR). For a given published estimate, TQNR, defined as 100% minus TQRR, is calculated for each tabulation cell from the BERD Survey, except for cells that contain count or ratio estimates. TQNR measures the combined effect of the procedures used to handle unit and item nonresponse on the weighted BERD Survey estimate. TQNR tables giving imputation rates corresponding to each data table are available from the NCSES project officer. Also see section “ Item Nonresponse .”

Response by Mode

Overall, more than 99% of checked-in cases responded to the BERD Survey by using the online version of the survey and less than 1% responded by mailing in the paper form. Lastly, more than 97% of checked-in companies with account managers—that is, the top R&D companies (based on prior year reported or imputed data) that were assigned an analyst to act as a single point of contact for all communications—responded using the online version of the survey.

Data Editing

Given the size and complexity of the BERD Survey, many survey responses included errors that required correction or had unusual patterns that required validation. Several hundred automated edit checks were programmed to improve the efficiency of analyst data review and correction ( table A-10 ).

Approximately two-thirds of these edit checks were designed to catch arithmetic errors and logically inconsistent responses ( balance edits ). The remaining edit checks were designed to flag outliers for further analyst review ( analytical edits ). Descriptions of the data edits and edit failure rates are in annual methodology reports that are available from the NCSES project officer.

During the editing and review process, several cases were identified where companies reported zero R&D or a relatively small amount of R&D, even though subject-matter experts expected large amounts of R&D to be reported. Some of these companies were contract research organizations or federal contractors that did not account for the costs they incurred while conducting customer-sponsored research as R&D; instead, they accounted for these as the cost of sales. The largest of these companies were contacted by analysts and asked to resubmit their surveys. In rare cases, if no response could be elicited from a company and public information was available related to costs for customer-sponsored R&D, those data were used to impute an R&D estimate for that company.

Techniques for Handling Unit and Item Nonresponse

For various reasons, many firms chose to return the survey questionnaire with one or more blank items. For some firms, internal accounting systems and procedures may not have allowed quantification of specific expenditures. Others may have refused to answer any questions as a matter of company policy. Weighted estimates produced from the BERD Survey include adjustments to account for companies that did not respond to the survey ( unit nonresponse ) and for companies that did respond but left some questions blank ( item nonresponse ).

Unit Nonresponse

The BERD Survey accounts for unit nonresponse by multiplying each company’s sampling weight by a nonresponse adjustment factor. To calculate the adjustment factors, each company in the sample that is eligible for tabulation is assigned to one (and only one) adjustment cell. The adjustment cells are based on the three R&D groups, which are subdivided according to R&D size and certainty status and also on the industry sampling strata described in the section “ Stratification of the Sampling Frame ” that are updated using information on industry classification reported in the BERD Survey. For a given adjustment cell, the nonresponse adjustment factor is the ratio of the sum of the weighted measure of size for all companies in the cell to the sum of the weighted measure of size for all companies in the cell with reported or imputed data. The measure of size used to select the sample for the 2020 BERD Survey (see section “ Sampling Frame ”) was also used to adjust for unit nonresponse. For companies in the known positive R&D stratum, the measure of size was based on R&D in the United States. For companies in the unknown R&D stratum, the measure of size was based on total annual payroll in the United States. For companies in the known zero R&D stratum, a value of “1” was assigned as the measure of size so that a company’s sample weight alone would be part of each cell’s adjustment factor. Beginning in survey year 2018, this unit nonresponse adjustment was also applied to counts, patents, patent licensing agreements, and intellectual property protection. In previous survey years, no such adjustment was applied to those items.

R&D estimates for geographic areas outside the largest countries, states, and core-based statistical areas (CBSAs) that are dominated by a relatively small number of companies are particularly sensitive to changes in survey response because these areas may not be similarly represented by companies in the same adjustment cell.

Item Nonresponse

Item nonresponse for a given company is handled by item imputation. For account manager companies, large companies, and special cases, analysts impute these data using direct substitution of available company data (e.g., data from the company’s website, annual Form 10-K report, or administrative sources) or other methods determined appropriate by NCSES’s and the Census Bureau’s subject-matter experts. For other cases, including cases where analysts were unable to provide a superior estimate, data are imputed by programmed item imputation procedures. Depending on the particular item being imputed for a company, these procedures are based on a combination of (1) direct substitution of available company data, (2) ratio imputation using the company’s survey data for both the current and prior year, and (3) ratio imputation using survey data from both the company and other similar companies, which reported both the survey item being imputed for the company and the other survey item used in the ratio. Tables of imputation rates corresponding to each data table are available from the NCSES project officer.

The general methodology used to produce estimates from the BERD Survey 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 below.

Estimates published for the BERD Survey are computed as sums of weighted data for sample companies that reported to the survey or for sample companies for which data could be reliably imputed based on prior reports or other information. Two types of weights are used for estimates of R&D: sampling weights, and nonresponse adjustment factors. The sampling weight for a given company is calculated as the reciprocal of the company’s probability of inclusion in the sample. Nonresponse adjustment factors are used to represent companies in the sample that did not provide sufficient response data to be directly tabulated and whose data could not be imputed. For information on the calculation of the nonresponse adjustment factors, see section “ Unit Nonresponse .”

Each value that contributes to a given BERD Survey estimate is multiplied by both its sampling weight and its nonresponse adjustment factor, and these weighted values are then summed to create the estimate. Beginning in survey year 2018, the nonresponse adjustment factor was also applied to estimates of counts, patents, and patent licensing agreements. In prior survey years, the adjustment was not applied to those items.

Postsampling Industry Classification

As mentioned in the section “ Industry Classification for Sampling ,” the industry classification assigned to companies for sampling was based on either reported BERD Survey business segment data from prior years or annual payroll. To produce more accurate estimates for the current survey year, a company’s reported business code, if available for the current survey year, was used to assign an updated industry code for tabulations. The company’s response to the domestic R&D performance questions from the current survey year was used to classify each company into the business code that accounted for the largest amount of total domestic R&D performance. The business codes reported by companies with large amounts of R&D were validated, and in some cases corrected, by survey staff. If no business code data were available for a company’s domestic R&D performance, the industry code used for sampling was also used for tabulations.

R&D, by Core-Based Statistical Area (CBSA) or State

CBSA-level estimates of business R&D are modeled using BERD Survey data reported by companies on the address of each of their largest R&D locations and administrative data from the Census Business Register on the payroll for each business establishment in the United States. The weighted amount of company R&D is apportioned to CBSAs within states using the same hybrid estimator method used for state estimates (below). Current BERD Survey methodology cannot attribute all R&D to a specific location. For example, R&D reported by companies that did not respond to geographic questions and for whom no method was available to impute locations is not assigned to a location. This R&D was performed in one of the 50 U.S. states or the District of Columbia, but the specific location is not estimated and is reported as “undistributed” in BERD Survey tables.

The estimation methodology for state estimates takes the form of a hybrid estimator, combining the unweighted reported amount, by state, with a weighted amount apportioned (or raked) across states with relevant industrial activity. The hybrid estimator smooths the estimate over states with R&D activity, by industry, and accounts for real observed change within a state.

R&D estimates for CBSAs and states that are dominated by a relatively small number of companies are particularly sensitive to changes in both unit and item response. Because companies rarely publish detailed information about the geographic location of their R&D operations, it is difficult to identify and correct erroneous responses to these questions. And, as noted earlier, the method used to correct for unit nonresponse relies on data from companies in the same industry or size category. These peer companies may report relatively less (or no) R&D in the geographic areas where a nonresponsive company performs R&D.

R&D, by Business Segment Code

To provide increased granularity on R&D activities, the BERD Survey includes questions asking companies to report data for business units below the company level. To support subcompany reporting, a list of business codes based on NAICS was provided in the BERD Survey for companies to use to categorize their business operations. The list of business codes for the 2020 cycle of the BERD Survey was based on the 2017 NAICS. To assist companies in selecting appropriate business codes, likely business codes were provided to respondents by prepopulating them on the online version of the survey and by printing them on the forms mailed to companies. For companies that reported to the 2017 BRDIS or 2018 BRDS, the most recent business codes reported by the company were used to provide the business codes. For companies that did not report to the 2017 BRDIS or 2018 BRDS, establishment payroll data from the Business Register were used to provide the business codes.

Company Counts

The BERD Survey is designed primarily to produce valid, useful estimates of money amounts related to the performance and funding of R&D. Because this is the survey’s focus, estimation of meaningful company counts is difficult. Consequently, throughout the history of the survey there have been various efforts to calculate frequencies more precisely. The following is a summary of the results of recent efforts.

Beginning in survey year 2019, company count estimates reflect a change in rounding methodology. Beginning in survey year 2018, a weight adjustment to account for unit nonresponse was implemented for company counts; as a result, company count estimates are not comparable with survey years prior to 2018.

The company count estimates for 2017 are not comparable with those for 2016 for two reasons. First, the target population for 2017 was restricted to companies with 10 or more domestic employees, whereas the 2016 survey population included companies with 5 or more employees. Second, no adjustment is applied to count estimates to correct for unit nonresponse, and overall response to the survey declined from 2016 to 2017.

The company count estimates for 2014 and onward are not comparable with estimates published for previous years. BRDIS review and correction procedures were amended beginning in survey year 2014 to include a more systematic analysis of companies reporting small amounts of R&D (less than $10,000) and no R&D employees. Many of these responses were determined to be reporting errors (false-positive R&D), and their R&D was set to zero. These corrections had a negligible impact on BRDIS R&D estimates compared to earlier years. But because these companies tended to have high sample weights, these corrections had a large impact on the estimate of R&D-active companies compared to prior years (when many fewer such corrections were made).

Revision of Capital Expenditure Estimates

Review of BERD capital expenditures data in calendar year 2021 uncovered cases where reported or imputed R&D capital expenditures (CAPEX) were unrealistically high, resulting in inflated overall survey estimates. As a result of this review, a number of changes were made to the editing and imputation of CAPEX and total domestic capital expenditures (TCPEX). Survey managers determined that the magnitude of these changes warranted the recalculation of CAPEX estimates for several prior statistical periods. The revised estimates are reflected in the internationally comparable table 70 through table 87 .

In addition to an overall escalation in the priority placed on the review of these data by survey staff, the following specific procedures were implemented to improve the quality of BERD estimates of CAPEX and TCPEX:

• Use of total domestic capital expenditures data from the Census Bureau’s Annual Capital Expenditures Survey (ACES) when companies report TCPEX amounts significantly smaller than estimated in ACES.
• Imputing values of CAPEX for respondents that report the same value for CAPEX as they do for either domestic R&D expenditures (DOEXP) or domestic R&D performance.
• Flagging cases where reported CAPEX exceeds DOEXP for additional subject-matter expert review. Erroneous CAPEX values will be replaced with imputed values.
• Excluding influential outliers from the imputation bases for CAPEX. Imputation for CAPEX relies on industry ratios of reported CAPEX to reported TCPEX. These ratios can be highly influenced by outliers.

Tabulation Eligibility

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 for years prior to 2018. 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 2020 estimates, they would have contributed approximately $130 million to overall R&D expenditures and would have added approximately 9,300 companies to the estimated count of U.S. companies with R&D expenditures.

Sampling and Nonsampling Errors

The estimates produced from the BERD Survey are subject to both sampling and nonsampling errors. Sampling error is the difference between estimates obtained from the sample and results theoretically obtainable from a comparable complete enumeration of the sampling frame. This error results because only a subset of the sampling frame is measured in a sample survey. For published estimates from the BERD Survey, standard errors are produced for estimated percentages, while relative standard errors (RSEs) are produced for all other estimates. Tables of the estimated measures of sampling variability corresponding to each data table are available from the NCSES project officer.

Standard errors may be used to define confidence intervals about the corresponding estimates with a desired level of confidence. If a confidence interval were constructed for each possible sample that could be selected using the same sample design, then it would be expected that the percentage of confidence intervals containing the result of a complete enumeration of the sampling frame would equal the percentage of the level of confidence. For example, the interval defined by a margin of error of 2 standard errors yields a confidence interval of approximately 95%.

Because relatively few companies perform R&D in the United States, and because the amount of R&D they perform is quite variable, it is difficult to achieve control over the sampling error of survey estimates produced from the BERD Survey. This depends on the correlation between the measure of size on the sampling frame that was used to assign the selection probabilities and the actual data that are collected in the BERD Survey, which cannot be predicted accurately for all companies when the sample is designed. However, the companies known to perform the greatest amounts of R&D are included in the sample with certainty so that these companies will not contribute to the sampling error of the resulting estimates produced from the BERD Survey.

The sample size is sufficiently large that estimates based on the total sample are subject to low sampling error. However, because priority in designing the sample was given to industries that were identified in previous surveys as conducting large amounts of R&D expenditures, the sampling error may be larger for estimates for the lower-priority industries. The RSE for the estimate of total domestic R&D performed by the company was 0.66% in 2020.

Potential nonsampling errors include coverage error and various response and operational errors, such as errors during data collection, reporting errors, transcription errors, and bias due to nonresponse. These are errors that could also occur if a complete enumeration of the sampling frame had been conducted under the same conditions as the sample survey. Most of the important operational errors were detected and corrected during the course of reviewing the data for reasonableness and consistency. Though nonsampling error is not measured directly, quality control procedures were employed throughout the survey process to minimize this type of error.

Measurement Error

Variations in respondent interpretations of the definitions of R&D activities and variations in accounting procedures are of particular concern—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 R&D services industry (NAICS 5417); and the method used by companies, in general, to count and report numbers of employees in various categories, such as the number of employees who work full time versus part time on R&D. The sophistication and comprehensiveness of a company’s accounting and personnel tracking systems often depend on its size and activities and on its willingness to accommodate government-sponsored surveys. While no metric of measurement error is produced, 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 Comparability (Changes)

The statistics resulting from this survey are intended primarily as indicators of absolute levels of R&D spending and personnel. Nevertheless, the statistics are often taken to be a continuous time series prepared using the same collection, processing, and tabulation methods. Although estimating the business portion of the nation’s R&D enterprise accurately has always been the goal, such strict uniformity has not been the case. Since the survey was first fielded, improvements have been made to increase the reliability of the statistics and to make the survey results more useful. To that end, past practices have been changed and new procedures instituted. Preservation of the comparability of the statistics has, however, been an important consideration in making these improvements. Nonetheless, changes to survey coverage and definitions, the industry classification system, estimation methods, and the procedure used to assign industry codes to multi-establishment companies, which are documented in the annual reports, may have affected the comparability of the statistics. Among the most demonstrable changes are those made to the questionnaires, and those changes are summarized below.

Differences between the 2019 BERD and 2020 BERD Survey Questionnaires

The following changes were made to the 2020 BERD Survey from the 2019 BERD Survey:

• Questions on the contact information of the person primarily responsible for completing each section were added to the end of each section.
• A follow-up question was added to the ownership question asking whether the new owner of the sampled company is a holding company or a private equity firm.
• Question on details of R&D performed by others was cycled off.
• Question on activities with academia was cycled off.
• Question on business code(s) in which the company performed R&D and was paid for by others was cycled off.
• Question on federal R&D by government agency was cycled off.
• Question on federal R&D by types of agreements was cycled off.
• Question on source of funds for domestic R&D funded by others was added to the section 3 worksheet.
• Questions on R&D application areas were cycled off.
• Questions on patents, intellectual property, and technology transfer were rotated back on.

Differences between the 2018 BRDS and 2019 BERD Survey Questionnaires

The following changes were made to the 2019 BERD Survey from the 2018 BRDS:

• Questions on patents, intellectual property, and technology transfer were cycled off.
• A question on filing for state tax credit for research activities in 2019 was added.

Differences between the 2017 BRDS and 2018 BRDS Questionnaires

The following changes were made to the 2018 BRDS from the 2017 BRDS:

• A question on land acquisition capital expenditures for R&D operations was added.
• Questions related to R&D on artificial intelligence (AI) were added.
• Questions asking for country and state location of employees and R&D employees were added.
• A question asking for counts of temporary and leased employees working on R&D was added.

Differences between the 2016 BRDIS and 2017 BRDS Questionnaires

The following changes were made to the 2017 BRDS from the 2016 BRDIS:

• Questions on product and process innovation were removed.
• A question on whether R&D paid for by the company included customer-sponsored R&D was added.
• Questions on R&D funded by foreign governments or agencies and R&D funded by universities and colleges located outside the United States were added.
• A question on whether any capital expenditures for R&D were funded, paid for, or reimbursed by others not owned by your company was added.

Differences between the 2015 and 2016 BRDIS Questionnaires

The following changes were made to the 2016 BRDIS from the 2015 BRDIS:

• Questions on royalties and licensing fees were added to both the R&D paid for by the company and the R&D paid for by others type-of-cost sections.
• Questions on the type of worldwide R&D paid for by the company were added to Form BRDI-1(S).
• Questions on the type of worldwide R&D paid for by others were added to Form BRDI-1(S).
• A question on all other contract R&D services paid for by customers was added to Form BRDI-1(S).
• A question on R&D performed by universities, colleges, and academic researchers located inside the United States was added, while a question on R&D performed by foreign governments was removed.
• A question on R&D funded by universities, colleges, and academic researchers located inside the United States was added, while a question on R&D funded by foreign governments was removed.
• A question on whether utility patent sales and licensing revenues were received from companies or organizations outside the United States was added to Form BRDI-1.
• A question on whether utility patent purchases and licensing payments were made to companies or organizations outside the United States was added to Form BRDI-1.
• A question on whether the company filed for the tax credit for increasing research activities (IRS Form 6765) in tax year 2016 was added to Form BRDI-1.
• Questions on the importance of intellectual property protections were removed.

Differences between the 2014 and 2015 BRDIS Questionnaires

The following changes were made to the 2015 BRDIS from the 2014 BRDIS:

• A question on phase IV clinical trials was added to Form BRDI-1.
• A question on R&D performed by others that was paid for by U.S. federal government agencies or laboratories was added to Form BRDI-1.
• Questions on the type of foreign R&D paid for and performed by the company were added to Form BRDI-1.
• Questions on the type of foreign R&D performed by the company but paid for by others were added to Form BRDI-1.
• A question on nonprovisional utility patents was added to Form BRDI-1.
• Questions related to R&D in photonics and optics application areas were removed from Form BRDI-1.

Differences between the 2013 and 2014 BRDIS Questionnaires

The following changes were made to the 2014 BRDIS from the 2013 BRDIS:

• A question on monetary gifts to universities or colleges restricted to supporting R&D was added to Form BRDI-1.
• A question on revenue received from patent licensing was added to Form BRDI-1.
• A question on purchasing patents from others was added to Form BRDI-1.
• A question on licensing patents from others was added to Form BRDI-1.
• One business code was added to the list of business codes collected on the survey: 33333, Digital cameras manufacturing. In prior years, this line of business was included in the business code 33412, Computers and peripheral equipment manufacturing and magnetic and optical media.
• Questions related to patenting were removed from Form BRDI-1(S).
• Questions related to innovation were added to Form BRDI-1(S).

Differences between the 2012 and 2013 BRDIS Questionnaires

The following changes were made to the 2013 BRDIS from the 2012 BRDIS:

• The list of countries for which foreign R&D performance data were collected was expanded by three: Hungary, Luxembourg, and Norway.
• A question was restored asking the amount of R&D that the company plans to recoup through indirect charges on U.S. federal government contracts (independent R&D). This question was last asked on the 2010 BRDIS.
• Questions on R&D for software products and R&D for embedded software were combined.
• A question on R&D for software products and embedded software paid for by the federal government was added.
• A question related to the educational attainment of scientists and engineers was restored. This question was last asked on the 2010 BRDIS.
• Two business codes were added to the list of business codes collected on the survey: 32542, Biotechnology-based pharmaceutical and biological products (except diagnostics), and 51801, Cloud computing applications and Internet-based software services.
• Delinquent companies in the known positive R&D stratum for the past two survey cycles were sent Form BRD-1(S) to see if they would report at least the high-level numbers.

Differences between the 2011 and 2012 BRDIS Questionnaires

For 2012, a much shorter (8-page) version of the short form, BRD-1(S), was implemented. The form included 19 high-level-detail items on worldwide sales; domestic sales; R&D expenses funded both by the company and by others; employment both worldwide and domestic, including R&D employment; and patents applied for and issued. Companies that reported $1 million or more of domestic R&D performance were then sent the long form (BRDI-1) for additional details. The BRD-1(S) form was sent to companies in the unknown and known zero R&D strata. In section 2, the questionnaire collected the additional detail categories for capital expenditures. In section 3, four agencies were added to the type of agency question so as to reduce the amount reported in the All other category. In section 4, the percentage of R&D that was directed toward business areas or product lines new to the respondent’s company and also the percentages that pertain to defense applications, health or medical applications, or agricultural applications were added for R&D funded by the company and R&D funded by others.

Differences between the 2010 and 2011 BRDIS Questionnaires

For the 2011 data collection, the innovation questions and instructions in section 1 were changed based on the results of the 2010 experiment. Cycling continued for data items that were not needed every year. The survey was expanded in several ways to address data gaps: the list of countries in which companies could report foreign R&D performance was expanded, a question was added to collect intracompany R&D transactions, and questions were added about companies’ second-largest R&D location. In addition, questions pertaining to full-time equivalent (FTE) R&D scientists and engineers were revised to improve respondent understanding of survey concepts.

Differences between the 2009 and 2010 BRDIS Questionnaires

For the 2010 data collection, the most notable changes made to the questionnaire were the inclusion of a one-time section (section 7) on R&D time frame and R&D product life, the inclusion of an experiment testing the impact of different innovation questions and instructions, and the addition of a survey supplement to collect detailed information from companies reporting R&D paid for by others. In addition, questions and instructions about company ownership were expanded to clarify, especially for foreign-owned companies, the information that should be reported on the survey. Cycling began for data items that were not needed every year from every company. These items will be returned to the questionnaire cyclically, depending on the demand for and quality of the collected data. Finally, data items that were poorly reported during the first two cycles of BRDIS were deleted.

The section titled “R&D Time Frame and R&D Product Life” was added for the 2010 cycle to aid in estimating the depreciation of R&D when it is treated as an investment in the U.S. System of National Accounts.

An experiment testing the impact of different innovation questions and instructions used two versions of the BRDIS short form. The innovation questions on the 2010 Form BRDI-1A were identical to questions used on the 2009 Form BRDI-1A, and the 2010 Form BRDI-1B altered the questions and instructions to replicate innovation questions on the European Union’s Community Innovation Survey. The experiment did not produce statistically significant differences in measured rates of innovation.

Differences between the 2008 and 2009 BRDIS Questionnaires

Several changes were made to the 2009 BRDIS questionnaire—in part, to address reporting errors observed during the 2008 survey cycle. These changes included the following:

• A screening question at the beginning of the form asking companies whether they had R&D activity during the reporting period was removed.
• Exclusion instructions in the main R&D expense question were replaced with a series of targeted questions. This approach was based on the premise that the economic concepts requested by BRDIS do not always conform to the R&D measures tracked by companies. Rather than directly asking for concepts that may diverge from respondent preconceptions about R&D, the approach in 2009 guided respondents to derive amounts that conformed to the BRDIS definition of R&D.
• Instructions in the question about R&D paid for by others were replaced with a series of targeted questions.
• Data for R&D performed by others were derived rather than collected directly. For the 2009 cycle of BRDIS, R&D performed by others was the sum of two R&D costs known to be tracked by companies: payments to business partners for collaborative R&D and purchased R&D services.
• The order of the “Management and Strategy of R&D” and the “Financial Schedule B” (R&D paid for by others) sections was switched.

Definitions

Capital expenditure. Capital expenditures are payments by a business for assets that usually have a useful life of more than 1 year, like buildings, equipment, or software. The value of assets acquired or improved through capital expenditures is recorded on a company’s balance sheet. Expenditures for long-lived assets used in a company’s R&D operations are not included in its R&D expense, but any depreciation recorded for those assets would be included in its R&D expense. Data are collected in the BERD Survey for capital expenditures for R&D operations for land acquisition, structures, equipment, capitalized software, and other items.

Core-based statistical area (CBSA). A CBSA is a U.S. geographic area that consists of one or more counties (or equivalents) anchored by an urban center of at least 10,000 people plus adjacent counties that are socioeconomically tied to the urban center by commuting. CBSAs are defined by OMB in the Executive Office of the President.

Employment, total and R&D. Involves the number of people employed by R&D-performing or R&D-funding companies in all locations, both foreign and domestic, during the pay period that included 12 March of the survey year. (The date 12 March is what most employers use when paying first-quarter employment taxes to IRS.) R&D employees are those who provide direct support to R&D, such as researchers, R&D managers, technicians, clerical staff, and others assigned to R&D groups. Those not included are employees who provide indirect support to R&D, such as corporate personnel, security guards, and cafeteria workers. In addition to providing head counts of total and R&D employees, the BERD Survey also produces estimates of FTE domestic R&D employment. This is the number of persons employed who were assigned full time to R&D, plus a prorated number of employees who worked on R&D only part of the time.

Employment, leased and temporary. The number of people who work for R&D-performing or R&D-funding companies, but who are not considered employees of the reporting company. These workers perform tasks similar to the reporting companies’ own employees but are technically employed by another company (such as a temp or staffing agency or a consulting firm) or are independent on-site consultants.

Expense and R&D expense. Involves money spent or costs incurred in an organization’s efforts to generate revenue, representing the cost of doing business. Expenses may be in the form of actual cash payments (such as wages and salaries), a computed expired portion of an asset (depreciation), or an amount taken out of earnings (such as bad debts). Expenses are summarized and charged in the income statement as deductions from the income before assessing income tax. Whereas all expenses are costs, not all costs are expenses (e.g., costs incurred in acquisition of income-generating assets—see the definition of capital expenditure above). R&D expense is the cost of R&D funded by the company itself and performed within the respondent company’s facilities, both foreign and domestic, or performed by others outside of the company under contract, subcontract, grant, or other funding arrangement.

R&D and business R&D. R&D is planned, creative work aimed at discovering new knowledge or devising new applications of available knowledge. This includes (1) activities aimed at acquiring new knowledge or understanding without specific immediate commercial applications or uses ( basic research ), (2) activities aimed at solving a specific problem or meeting a specific commercial objective ( applied research ), and (3) systematic use of research and practical experience and resulting in additional knowledge, which is directed to producing new or improved goods, services, or processes ( development ). R&D includes both direct costs , such as salaries of researchers, and administrative and overhead costs clearly associated with the company’s R&D. However, R&D does not include expenditures for routine product testing, quality control, and technical services unless they are an integral part of an R&D project. R&D also does not include market research; efficiency surveys or management studies; literary, artistic, or historical projects, such as films, music, or books and other publications; and prospecting or exploration for natural resources.

R&D, artificial intelligence (AI). AI is a branch of computer science and engineering devoted to making machines intelligent. Intelligence is that quality that enables an entity to perceive, analyze, determine response, and act appropriately in its environment.

Systems with AI perform functions including, but not limited to, speech recognition, machine vision, or machine learning:

• Speech recognition transforms human speech into a format useful for computer applications (e.g., a digital assistant).
• Machine vision uses sensors and software that allow images to be used as an input for computer applications (e.g., systems that sort or inspect objects or support navigation in mobile equipment).
• Machine learning uses statistical software and data to “learn” and make better predictions without reprogramming (e.g., recommender systems for websites, or sales and demand forecasting).

AI technologies also include virtual agents, deep learning platforms, decision management systems, biometrics, text analytics, and natural language generation and processing.

R&D, biotechnology. Biotechnology is the application of S&T to living organisms, as well as parts, products, and models thereof, to alter living or nonliving materials for the production of knowledge, goods, and services. The following list provides examples of areas of biotechnology in which R&D may be performed.

• DNA or RNA: genomics; pharmacogenomics; gene probes; genetic engineering; DNA or RNA sequencing, synthesis, or amplification; gene expression profiling; and use of antisense technology, large-scale DNA synthesis, genome editing and gene editing, and gene drive
• Proteins and other molecules: sequencing, synthesis, or engineering of proteins and peptides (including large-molecule hormones); improved delivery methods for large molecule drugs; proteomics; protein isolation and purification; signaling; and identification of cell receptors
• Cell and tissue culture and engineering: cell or tissue culture, tissue engineering (including tissue scaffolds and biomedical engineering), cellular fusion, vaccine or immune stimulants, embryo manipulation, marker-assisted breeding technologies, and metabolic engineering
• Process biotechnology techniques: fermentation using bioreactors, biorefining, bioprocessing, bioleaching, biopulping, biobleaching, biodesulfurization, bioremediation, biosensing, biofiltration and phytoremediation, and molecular aquaculture
• Gene and RNA vectors: gene therapy and viral vectors
• Bioinformatics: construction of databases on genomes, protein sequences, and modeling complex biological processes, including systems biology
• Nanobiotechnology: application of the tools and processes of nano- or microfabrication to build devices for studying biosystems and applications in, for example, drug delivery or diagnostics

R&D, domestic. R&D performed in the 50 U.S. states and the District of Columbia. Adjusted domestic R&D is calculated in tables designed to enable comparisons between U.S. BERD Survey statistics and those of other nations ( table 70 through table 87 ). There are three types of tables corresponding to the three principal measures of domestic R&D in the U.S. BERD Survey—that is, R&D paid for by the respondent company and others outside of the company and performed by the respondent company, R&D paid for and performed by the respondent company, and R&D paid for by others and performed by the company. In each table, an internationally comparable adjusted domestic R&D estimate is calculated by subtracting depreciation relating to R&D operations, which is included in U.S. BERD Survey domestic R&D, and adding capital expenditures relating to R&D operations, which is excluded from U.S. BERD Survey domestic R&D. Also shown in each table are the differences between the U.S. BERD Survey estimates in this report and the adjusted internationally comparable estimates for domestic R&D.

R&D intensity , or R&D-to-sales ratio. R&D intensity is a ratio, expressed as a percentage, calculated by dividing the cost of R&D by sales. The ratio serves as an indicator of the relative incidence of R&D among groups of companies, primarily among industries and company size classifications. In this report, R&D intensity ratios are calculated in various ways, depending on the measure of R&D (R&D paid for by the respondent company, paid for by others outside of the company, or both) and whether the respondent company performs and funds or only performs R&D.

R&D, nanotechnology. The understanding of processes and phenomena and the application of S&T to organisms and to organic and inorganic materials—as well as parts, products, and models thereof—at the nanometer scale (but not exclusively below 100 nanometers) in one or more dimensions, where the onset of size-dependent phenomena usually enables novel applications. These applications utilize the properties of nanoscale material that differ from the properties of individual atoms, molecules, and bulk matter for the production of knowledge, goods, and services, like improved materials, devices, and systems that exploit these new properties. The following list provides examples of areas of nanotechnology in which R&D may be performed.

• Nanomaterial: material with any external dimension in the nanoscale or having internal structure or surface structure in the nanoscale
• Nanoelectronics: field of S&T concerned with the development and production of functional electronic devices with nanoscale components
• Nanophotonics: branch of photonics concerned with interaction of photons with nanomaterials aiming to design optical or optoelectronic components
• Nanomedicine: medical application of nanotechnology (e.g., medical application of nanomaterials and biological devices, nanoelectronics biosensors, and possible future applications of molecular nanotechnology, such as biological machines)
• Nanomagnetics: the study of the magnetic response of nanomaterials to an applied magnetic field and their applications
• Nanomechanics: a branch of nanoscience studying fundamental mechanical (elastic, thermal, and kinetic) properties of physical systems at the nanometer scale
• Nanofiltration: a membrane filtration process used for the softening of water and the removal of organic matter; includes nanomembranes
• Nanotools: multicomponent tools and devices used for manipulation, nanolithography, and nanofabrication
• Nanoinstruments or nanodevices: multicomponent instruments or devices used for observation, analysis, or control of matter at the nanometer scale
• Nanomanufacturing: intentional synthesis generation of control of nanomaterials, or fabrication steps in the nanoscale, for commercial purposes

R&D paid for by others, worldwide and domestic. The cost of R&D funded by others outside of the company, including the U.S. federal government, and performed within the respondent company’s facilities, both foreign and domestic.

R&D paid for by the company and others, worldwide and domestic. The cost of R&D funded by the company or by others outside of the company and performed within the respondent company’s facilities, both foreign and domestic, or performed by others outside of the company under contract, subcontract, grant, or other funding arrangement.

R&D performed by the company, worldwide and domestic. The cost of R&D performed within the respondent company’s facilities, both foreign and domestic, funded by the company itself or by others outside of the company.

R&D performed by the company and others, worldwide and domestic. The cost of R&D performed within the respondent company’s facilities, both foreign and domestic, or performed by others outside of the company under contract, subcontract, grant, or other funding arrangement.

R&D performed by others, worldwide and domestic. The cost of R&D funded by the company or by others outside of the company and performed by others outside of the company under contract, subcontract, grant, or other funding arrangement.

R&D, software and Internet. R&D activity in software and Internet applications refers only to activities that have an element of uncertainty and that are intended to close knowledge gaps and meet scientific and technological needs. This item is reported in this survey regardless of the eventual user (internal or external). R&D activity in software includes software development or improvement activities that expand scientific or technological knowledge and construction of new theories and algorithms in the field of computer science. R&D activity in software excludes software development that does not depend on a scientific or technological advance, such as supporting or adapting existing systems, adding functionality to existing application programs, routine debugging of existing systems and software, creating new software based on known methods and applications, converting or translating existing software and software languages, and adapting a product to a specific client, unless knowledge that significantly improved the base program was added in that process.

Sales, worldwide and domestic. Dollar values for goods sold or services rendered by R&D-performing or R&D-funding companies located in the 50 U.S. states and the District of Columbia to customers outside the company, including the U.S. federal government, foreign customers, and the company’s foreign subsidiaries. Included are revenues from a company’s foreign operations and subsidiaries and from discontinued operations. If a respondent company is owned by a foreign parent company, sales to the parent company and to affiliates not owned by the respondent companies are included. Excluded are intracompany transfers, returns, allowances, freight charges, and excise, sales, and other revenue-based taxes.

Data Availability

The data from the BERD Survey can be found online at https://www.nsf.gov/statistics/industry/ . Detailed historical statistics from the predecessor survey, SIRD, can be obtained from NCSES’s Industrial Research and Development Information System at https://www.nsf.gov/statistics/iris/ . Information from the BERD Survey is also included in Science and Engineering Indicators and in National Patterns of R&D Resources .

Electronic Access

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 Federal Statistical Research Data Centers (FSRDCs) administered by the Census Bureau. FSRDCs are partnerships between federal statistical agencies and leading research institutions. FSRDCs provide secure environments supporting qualified researchers using restricted-access data while protecting respondent confidentiality. Researchers interested in using the microdata can submit a proposal to the Census Bureau, which evaluates proposals based on their benefit to Census, scientific merit, feasibility, and risk of disclosure. To learn more about the FSRDCs and how to apply, please visit https://www.census.gov/about/adrm/fsrdc.html .

Disclosure Avoidance

Disclosure is the release of data that reveals information or permits deduction of information about a particular survey unit through the release of either tables or microdata. Disclosure avoidance is the process used to protect each survey unit’s identity and data from disclosure. Using disclosure avoidance procedures, the Census Bureau modifies or removes the characteristics that put information at risk of disclosure. Although it may appear that a table shows information about a specific survey unit, the Census Bureau has taken steps to disguise or suppress a unit’s data that may be “at risk” of disclosure while making sure the results are still useful.

The BERD Survey uses cell suppression and rounding to avoid disclosing information about a particular company. Cell suppression is a disclosure avoidance technique that protects the confidentiality of individual survey units by withholding cell values from release and replacing the cell value with a data code, usually a “D” or an estimate range. If the suppressed cell value were known, it would allow one to estimate an individual survey unit’s value too closely.

The cells that must be protected are called primary suppressions . To make sure the cell values of the primary suppressions cannot be closely estimated by using other published cell values, additional cells may also be suppressed. These additional suppressed cells are called complementary suppressions . The process of suppression does not usually change the higher-level totals. Values for cells that are not suppressed remain unchanged. Before the Census Bureau releases data, computer programs and analysts ensure that primary and complementary suppressions have been correctly applied.

The Census Bureau has reviewed the data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied. For the 2020 tabular statistics, the approval ID was CBDRB-FY22-125, on 14 February 2022.

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Key data tables.

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Worldwide, domestic, and foreign R&D paid for by the company and by others and performed by the company

Domestic r&d paid for by the company and others and performed by the company, foreign r&d paid for by the company and others and performed by the company, projected r&d costs, internationally comparable tables: domestic r&d paid for by the company or others and performed by the company, data tables.

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Survey aggregate estimates

Worldwide r&d paid for by the company and performed by the company and others, worldwide r&d paid for by others and performed by the company and others, worldwide, domestic, and foreign sales for companies located in the united states that performed or funded r&d, domestic r&d paid for by the company and others and performed by the company in technology focus areas, domestic r&d paid for and performed by the company, domestic r&d paid for by the company and performed by the company and others, domestic r&d paid for by others and performed by the company, domestic r&d paid for by the u.s. federal government and performed by the company, domestic r&d paid for by sources outside the united states and performed by the company, domestic r&d paid for by the company and others and performed by the company and others, r&d paid for by the company and others and performed by the company outside of the united states, capital expenditures and r&d capital expenditures for domestic r&d paid for and performed by the company, employment and r&d employment, multiyear tables: worldwide, domestic, and foreign r&d paid for by the company and others and performed by the company, multiyear tables: worldwide, domestic, and foreign sales for companies located in the united states that performed or funded r&d, multiyear table: domestic r&d paid for by the company and others and performed by the company, by business activity, intellectual property (ip) and ip transfer activities, general notes.

The Business Enterprise Research and Development (BERD) Survey is the primary source of information on domestic and global research and development expenditures and the R&D workforce for companies operating in the 50 U.S. states and the District of Columbia. The survey is conducted annually by the Census Bureau in accordance with an interagency agreement with the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation. NCSES has cosponsored an annual business R&D survey since 1953. The Survey of Industrial Research and Development (SIRD) collected data for 1953–2007, and its successor, the Business R&D and Innovation Survey (BRDIS), collected data for 2008–16. Beginning with 2017, the collection of innovation data was moved to the Annual Business Survey, another survey cosponsored with the Census Bureau, and the 2017 and 2018 business R&D data collections reported in this report series were renamed the Business Research and Development Survey (BRDS). Beginning with the data collection for 2019, the survey was renamed for international comparability. The BERD Survey questionnaires , publications , and data can be found at https://www.nsf.gov/statistics/industry/ .

The results of the survey are used to assess trends in the performance and funding of R&D. Government agencies, corporations, and research organizations use the data to investigate productivity, formulate tax policy, and compare individual company performance with industry averages. Individual researchers in industry and academia use the data to investigate a variety of topics and to prepare professional papers, dissertations, and books. Total R&D expenditure statistics are used by the Bureau of Economic Analysis for inclusion in its System of National Accounts and Foreign Direct Investment programs.

Further, statistics from the BERD Survey make it possible to evaluate more fully the status of R&D in the United States and to compare the R&D activities of the United States with those of other nations. The usefulness of the information collected in this survey is enhanced by linking it to the Census Bureau’s Longitudinal Establishment and Enterprise Microdata file, which contains information on the outputs and inputs of companies’ manufacturing plants. Response to this survey is mandatory and confidential under Title 13 of the United States Code.

For the BERD Survey, data are collected from a probability sample of for-profit companies, which are classified in select manufacturing and nonmanufacturing industries. The BERD Survey is administered both to companies known to have performed R&D and to companies with no known history of R&D activity. The survey is sent to a single coordinator within each company, but it is organized into sections that help the coordinator collect specific types of information from different experts (human resources, accounting, R&D managers, etc.) in the company. Foreign-owned companies are instructed to report only for company operations owned by the U.S. subsidiary and, for purposes of the survey, to treat the foreign owners as if they were unrelated third parties.

The target population for the BERD Survey consists of all for-profit companies that have 10 or more paid employees in the United States, that have at least one establishment located in the United States in business during the survey year, and that are classified in certain industries, with a particular focus on those companies that perform R&D in the United States. A company is defined as one or more establishments under common domestic ownership or control.

The Census Bureau’s Business Register contains information on more than 7.3 million establishments with paid employees. It serves as the primary input to the sampling frame from which the sample is selected. For companies with more than one establishment, data are summed to the company level to assign an industry classification code and a measure of size, which are used in designing the sample. Companies are excluded from the frame if they are classified in an industry that is outside the scope of the BERD Survey or if they have fewer than 10 employees, based on their prior year aggregated annual payroll and employment data.

In addition to single-year tables for 2020 ( table 1 through table 57 , table 66 through table 69 ), this report includes tables containing statistics for multiple years ( table 58 through table 65 ). In these tables, most prior year statistics have been revised since originally published. Revised statistics include adjustments based on information obtained after the original statistics were prepared. For any given year, after the tables are published, the statistical file used to produce the tables stays open for about 1 year before it is permanently closed. During that year, respondents may provide updated data; also, information from other Census Bureau surveys or publicly available sources may become available. The new data and information are evaluated and tested; if appropriate, revisions are made to the statistical file. The multiyear tables in this report were prepared using the statistical files for the 2020 BERD Survey, the revised 2019 BERD Survey, and the revised BRDIS and BRDS statistical files for 2008–18.

Also in this report are tables designed to enable comparisons between U.S. BERD Survey statistics and those of other nations. There are three groups of tables corresponding to the three principal measures of domestic R&D in the U.S. BERD Survey—that is, R&D paid for by the respondent company and others outside of the company and performed by the respondent company ( table 70 through table 75 ), R&D paid for and performed by the respondent company ( table 76 through table 81 ), and R&D paid for by others and performed by the company ( table 82 through table 87 )—for 2015–20. In each table, an internationally comparable adjusted domestic R&D estimate is calculated by subtracting depreciation relating to R&D operations, which is included in U.S. BERD Survey domestic R&D, and then adding capital expenditures relating to R&D operations, which is excluded from U.S. BERD Survey domestic R&D. Also shown in each table are the differences between U.S. BERD Survey estimates in this report and the adjusted internationally comparable estimates for domestic R&D.

Beginning with the tables for the 2017 survey year, disclosure avoidance is now handled differently than it had been in prior years’ tables. Cell suppression is a disclosure avoidance technique that protects the confidentiality of individual survey units by withholding cell values from release and replacing the cell value with a data code. This technique was used in SIRD, BRDIS, and BRDS tables; data in affected cells were replaced with a “D.” For most of the tables in this report, disclosure avoidance is accomplished by replacing cells with an estimate range. Confidentiality is maintained while the usefulness of the statistics is enhanced because most of the completely suppressed cells in past years’ tables have been eliminated. For cases where confidentiality cannot be maintained even with the new estimate range technique, a “D” is substituted.

Terms used in business accounting and incorporated throughout the tables are defined in the section “ Technical Notes .” The information and statistics in this report supersede information and statistics in previously published reports.

Acknowledgments and Suggested Citation

Acknowledgments.

Raymond M. Wolfe (retired) of the National Center for Science and Engineering Statistics (NCSES) developed and coordinated this report under the guidance of Gary Anderson, former NCSES Acting Program Director, and John Jankowski, former NCSES Program Director, and under the leadership of Emilda B. Rivers, NCSES Director; Vipin Arora, former NCSES Deputy Director; and John Finamore, NCSES Chief Statistician.

The Census Bureau, under National Science Foundation interagency agreement number NCSE-2103021, collected and tabulated the data and produced the statistics for this report. This work was performed by Ebenezer Amoako, Lucia Chavez, Melvin Dangan, Robert Ford, David Garrow, Deena Grover, Kristy Harley, Neil Hillis, Bibi Khan, Michael Osman, and Jessica White, supervised by Jeffrey Kellner, Yvette Moore, Susan Shrieves, and Steven Wilkinson, under the direction of Michael Flaherty. Under the same interagency agreement, mathematical statistician support was provided by Lucas Streng and Abigail Legge, under the direction of James Hunt and Roberta Kurec, and business accounting and subject-matter support was provided by Ron Lee and Brandon Shackelford. RTI International provided editing services.

Suggested Citation

National Center for Science and Engineering Statistics (NCSES). 2023. Business Enterprise Research and Development: 2020 . NSF 23-314. Alexandria, VA: National Science Foundation. Available at https://ncses.nsf.gov/pubs/nsf23314/ .

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