1 

Business Dynamics Statistics: Single-Establishment Firms 

(BDS-SU-REV) Codebook and Glossary (2021 Release) 

NOTE: The 2021 release of the BDS-SU-REV includes several payroll statistics in both real and nominal 

terms. Data users can download files with inflation-adjusted payroll variables (real) or non-inflation-adjusted 

payroll variables (nominal). Each file will contain the standard set of establishment and employment variables 

outlined below. The inflation-adjusted file names and variable names will have the “_real” suffix. The noninflation-adjusted file names will have the “_nominal” suffix; note that there is no suffix attached to nominal 

payroll variable names. To construct real payroll measures, the GDP implicit price deflator from the BEA is 

used. Note that the base year is 2012. 

BDS-SU-REV Variable Definitions and Codes

year

Values: 2007-2021 

Description: record year

quarter

Values: 1-4 

Description: record quarter

sector

Values: 11,21,22,23,31-33,42,44-45,48-49,51,52,53,54,55,56,61,62,71,72,81

Description: 2-digit NAICS 2017 codes

11 - Agriculture, Forestry, Fishing and Hunting 

21 - Mining, Quarrying, and Oil and Gas Extraction 

22 - Utilities 

23 - Construction 

31-33 - Manufacturing 

42 - Wholesale Trade 

44-45 - Retail Trade 

48-49 - Transportation and Warehousing 

51 - Information 

52 - Finance and Insurance 

53 - Real Estate and Rental and Leasing 

54 - Professional, Scientific, and Technical Services 

55 - Management of Companies and Enterprises 

56 - Administrative and Support and Waste Management and Remediation Services 

61 - Educational Services 

62 - Health Care and Social Assistance 

71 - Arts, Entertainment, and Recreation 

72 - Accommodation and Food Services 

81 - Other Services (except Public Administration)

vcnaics3

Values: Numeric 

Description: Vintage-consistent 3-digit NAICS 2017 codes. 
2 

vcnaics4

Values: Numeric 

Description: Vintage-consistent 4-digit NAICS 2017 codes. 

fsize

Values: a) 1 to 2, b) 3 to 9, c) 10 to 99, d) 100 to 499, e) 500+

Description: Firm (establishment) size. A categorical variable defined as the average of the singleestablishment firm’s employment in quarter qt and qt-4. 

fsizecoarse

Values: a) 1 to 2, b) 3 to 9, c) 10+ 

Description: Firm (establishment) size coarse. This is the coarse version of fsize defined above. Includes 

three broader firm-size classes.

fage 

Values: a) 0, b) 1 to 3, c) 4 to 20, d) 21 to 40, e) 41+, f) Left Censored

Description: The number of calendar quarters that have elapsed since a single-establishment firm’s first 

quarter of operation. 

fagecoarse 

Values: a) 0 to 3, b) 4 to 20, c) 21 to 40, d) 41+, e) Left Censored

Description: Firm age coarse with five broad firm-age classes.

estabs

Values: Numeric

Description: A simple count of the number of single-establishment firms in the cell.

emp

Values: Numeric

Description: Paid employment consists of full- and part-time employees, including salaried officers and 

executives of corporations, who are on the payroll in the pay periods including March 12 (q1), June 12 (q2), 

September 12 (q3), and December 12 (q4). Included are employees on paid sick leave, holidays, and 

vacations.

denom

Values: Numeric

Description: Davis-Haltiwanger-Schuh (DHS) denominator. For quarter qt, denom is the average of 

employment in quarters qt and qt-4. This variable attempts to prevent transitory shocks from creating a 

bias to the relationship between net growth from qt-4 to qt and size.

estabs_entry

Values: Numeric 

Description: A count of single-establishment firms born within the cell during the previous four quarters.

estabs_entry_rate

Values: Numeric

Description: 100 x (estabs_entry in quarter qt divided by the average of estabs in quarters qt and qt-4)
3 

estabs_exit 

Values: Numeric 

Description: A count of single-establishment firms exiting from within the cell during the previous four 

quarters.

estabs_exit_rate 

Values: Numeric 

Description: 100 x (estabs_exit in quarter qt divided by the average of estabs in quarters qt and qt-4)

job_creation 

Values: Numeric 

Description: A count of all employment gains within the cell occurring over the previous four quarters from 

expanding and opening single-establishment firms. The reference weeks are as follows: March 12 (q1), 

June 12 (q2), September 12 (q3), and December 12 (q4). 

job_creation_births

Values: Numeric 

Description: A count of all employment gains within the cell occurring over the previous four quarters from 

opening single-establishment firms (births). The reference weeks are as follows: March 12 (q1), June 12 

(q2), September 12 (q3), and December 12 (q4).

job_creation_continuers 

Values: Numeric 

Description: A count of all employment gains within the cell occurring over the previous four quarters from 

continuing single-establishment firms. The reference weeks are as follows: March 12 (q1), June 12 (q2), 

September 12 (q3), and December 12 (q4).

job_creation_rate_births 

Values: Numeric 

Description: 100 x (job_creation_births/denom)

job_creation_rate 

Values: Numeric 

Description: 100 x (job_creation/denom)

job_destruction

Values: Numeric 

Description: A count of all employment losses within the cell occurring over the previous four quarters from 

contracting and closing single-establishment firms. The reference weeks are as follows: March 12 (q1), 

June 12 (q2), September 12 (q3), and December 12 (q4). 

 

job_destruction_deaths 

Values: Numeric

Description: A count of all employment losses within the cell occurring over the previous four quarters from 

closing single-establishment firms (deaths). The reference weeks are as follows: March 12 (q1), June 12 

(q2), September 12 (q3), and December 12 (q4). 
4 

job_destruction_continuers

Values: Numeric

Description: A count of all employment losses within the cell occurring over the previous four quarters from 

contracting single-establishment firms. The reference weeks are as follows: March 12 (q1), June 12 (q2), 

September 12 (q3), and December 12 (q4). 

 

job_destruction_rate_deaths 

Values: Numeric 

Description: 100 x (job_destruction_deaths/denom) 

job_destruction_rate

Values: Numeric 

Description: 100 x (job_destruction/denom)

net_job_creation 

Values: Numeric 

Description: job_creation – job_destruction 

net_job_creation_rate 

Values: Numeric 

Description: job_creation_rate – job_destruction_rate 

pay 

Values: Numeric 

Description: Payroll (in thousands of dollars) at single-establishment firms with positive employment during 

the pay periods including March 12 (q1), June 12 (q2), September 12 (q3), and December 12 (q4).

Included are employees on paid sick leave, holidays, and vacations.

denom_pay 

Values: Numeric 

Description: The average of payroll in quarters qt and qt-4 among single-establishment firms with positive 

employment. This variable is analogous to denom for employment.

pay_creation 

Values: Numeric 

Description: The dollar value of payroll gains (in thousands of dollars) occurring over the previous four 

quarters from expanding and opening single-establishment firms. The reference weeks are as follows: 

March 12 (q1), June 12 (q2), September 12 (q3), and December 12 (q4). 

pay_creation_births

Values: Numeric

Description: The dollar value of payroll gains (in thousands of dollars) occurring over the previous four 

quarters from opening single-establishment firms (births). The reference weeks are as follows: March 12 

(q1), June 12 (q2), September 12 (q3), and December 12 (q4). 

pay_creation_continuers 

Values: Numeric

Description: The dollar value of payroll gains (in thousands of dollars) occurring over the previous four 
5 

quarters from expanding single-establishment firms. The reference weeks are as follows: March 12 (q1), 

June 12 (q2), September 12 (q3), and December 12 (q4). 

pay_creation_rate_births 

Values: Numeric 

Description: 100 x (pay_creation_births/denom_pay)

pay_creation_rate 

Values: Numeric 

Description: 100 x (pay_creation/denom_pay)

pay_destruction 

Values: Numeric

Description: The dollar value of payroll losses (in thousands of dollars) occurring over the previous four 

quarters from contracting and closing single-establishment firms. The reference weeks are as follows: 

March 12 (q1), June 12 (q2), September 12 (q3), and December 12 (q4). 

pay_destruction_deaths 

Values: Numeric

Description: The dollar value of payroll losses (in thousands of dollars) occurring over the previous four 

quarters from closing single-establishment firms (deaths). The reference weeks are as follows: March 12 

(q1), June 12 (q2), September 12 (q3), and December 12 (q4). 

pay_destruction_continuers

Values: Numeric

Description: The dollar value of payroll losses (in thousands of dollars) occurring over the previous four 

quarters from contracting single-establishment firms that contracted. The reference weeks are as follows: 

March 12 (q1), June 12 (q2), September 12 (q3), and December 12 (q4). 

 

pay_destruction_rate_deaths

Values: Numeric 

Description: 100 x (pay_destruction_deaths/denom_pay)

pay_destruction_rate 

Values: Numeric 

Description: 100 x (pay_destruction/denom_pay)

net_pay_creation 

Values: Numeric 

Description: pay_creation – pay_destruction

net_pay_creation_rate

Values: Numeric 

Description: pay_creation_rate – pay_destruction_rate

pay_emp

Values: Numeric 

Description: Payroll per worker at single-establishment firms (in thousands of dollars).
6 

pay_emp_continuers

Values: Numeric 

Description: Payroll per worker at continuing single-establishment firms (in thousands of dollars).

pay_emp_births

Values: Numeric 

Description: Payroll per worker at opening single-establishment firms (in thousands of dollars).

pay_emp_deaths

Values: Numeric 

Description: Payroll per worker at closing single-establishment firms (in thousands of dollars).

rev 

Values: Numeric

Description: Annual Revenue (in thousands of dollars) at single-establishment firms with positive 

employment in quarter “qt”, denoted rev(qt). Note that rev(qt) is the annual revenue of all the firms with 

positive employment in “qt”. The formula is rev(qt). 

denom_rev 

Values: Numeric

Description: The average of the annual revenue between quarters qt and qt-4 (four quarters ago) among 

single-establishment firms with positive employment. This variable is analogous to denom for employment.

The formula is 0.5[rev(qt) + rev(qt-4)]. 

rev_creation 

Values: Numeric

Description: The dollar value of revenue gains (in thousands of dollars) occurring over the previous year 

from expanding and opening single-establishment firms. The formula is rev_creation(qt)=rev(qt) -rev(qt-4)

if this difference is positive, otherwise rev_creation(qt)=0.

rev_creation_births

Values: Numeric

Description: The dollar value of revenue gains (in thousands of dollars) occurring over the previous year 

from opening single-establishment firms (births) in each quarter. The reference weeks are as follows: March 

12 (q1), June 12 (q2), September 12 (q3), and December 12 (q4). The formula is rev_creation_births(qt)= 

rev_creation(qt) if the firm in the current quarter (qt) is a newly opened firm (birth) compared to the firm 

four quarters ago (qt-4).

rev_creation_continuers 

Values: Numeric

Description: The dollar value of revenue gains (in thousands of dollars) occurring over the previous year

from expanding single-establishment firms. The reference weeks are as follows: March 12 (q1), June 12 

(q2), September 12 (q3), and December 12 (q4). The formula is rev_creation_continuers(qt)= 

rev_creation(qt if the firm in the current quarter (qt) is a continuer firm compared to the firm four quarters 

ago (qt-4).
7 

rev_creation_rate_births 

Values: Numeric

Description: 100 x (rev_creation_births/denom_rev) 

rev_creation_rate 

Values: Numeric

Description: 100 x (rev_creation/denom_rev) 

rev_destruction 

Values: Numeric

Description: The dollar value of revenue losses (in thousands of dollars) occurring over the previous year 

from expanding and opening single-establishment firms in quarter t. The formula is 

rev_destruction(qt)=|rev(qt) -rev(qt-4)| if the difference rev(qt) -rev(qt-4) is negative, otherwise 

rev_destruction(qt)=0.

rev_destruction_deaths 

Values: Numeric

Description: The dollar value of revenue losses (in thousands of dollars) incurred due to the closure of 

single-establishment firms (deaths) in each quarter. The reference weeks are as follows: March 12 (q1), 

June 12 (q2), September 12 (q3), and December 12 (q4). The formula is rev_destruction_deaths(qt)= 

rev_destruction(qt) if the firm in the current quarter (qt) is no longer active (death) compared to the firm 

four quarters ago (qt-4). 

rev_destruction_continuers

Values: Numeric

Description: The dollar value of revenue losses (in thousands of dollars) occurring over the previous year

from contracting single-establishment firms. The reference weeks are as follows: March 12 (q1), June 12 

(q2), September 12 (q3), and December 12 (q4). The formula is rev_destruction_continuers(qt)= 

rev_destruction(qt) if the firm in the current quarter (qt) is a continuer firm compared to the firm four 

quarters ago (qt-4).

 

rev_destruction_rate_deaths

Values: Numeric

Description: 100 x (rev_destruction_deaths/denom_rev) 

rev_destruction_rate 

Values: Numeric

Description: 100 x (rev_destruction/denom_rev) 

net_rev_creation 

Values: Numeric

Description: rev_creation – rev_destruction

net_rev_creation_rate

Values: Numeric

Description: rev_creation_rate – rev_destruction_rate
8 

rev_emp

Values: Numeric

Description: Revenue per worker at single-establishment firms (in thousands of dollars).

rev_emp_continuers

Values: Numeric

Description: Revenue per worker at continuing single-establishment firms (in thousands of dollars).

rev_emp_births

Values: Numeric

Description: Revenue per worker at opening single-establishment firms (in thousands of dollars).

rev_emp_deaths

Values: Numeric

Description: Revenue per worker at closing single-establishment firms (in thousands of dollars).

metro

Values: M,N,SW,U

Description: Single-establishment firms located in Metropolitan or Micropolitan Statistical Areas are in cells 

designated with “M” while those in non-metropolitan areas are aggregated into cells designated with “N”. 

Cells designated “SW” (signifying “statewide”) are assigned to single-establishment firms without a fixed 

location such as employee leasing establishments. Cells designated as “U” (signifying “unclassified”) are 

assigned to single-establishment firms without a valid county code.

Rural

 Values: PU, MU, MR, PR, SW, U

 Description: Single-establishment firms are classified into one of four urban/rural categories based on the 

percentage of their county's population living in urban areas. “PU” (predominantly urban): 80% or more of 

the county population lives in an urban area. “MU” (mostly urban): at least 50% but less than 80% of the 

county population lives in an urban area. “MR” (mostly rural): at least 20% but less than 50% of the county 

population lives in an urban area. “PR” (predominantly rural): less than 20% of the county population lives in 

an urban area. For firms without a fixed location or firms without a valid county code, “SW” and “U” are used 

in the same manner as for metro.

msac 

Values: Numeric

Description: Numeric code for metropolitan and micropolitan statistical areas, as established by the Office 

of Management and Budget (OMB). This is a coarse msa identifier in that micropolitan statistical areas are 

grouped together under the identifier, “Micro”. The February 2013 definitions are used: 

https://www.census.gov/geographies/reference-files/time-series/demo/metro-micro/delineation-files.html 

cty

Values: Numeric

Description: Three-character FIPS code for counties within a given state. Users can refer to the CBP county 

reference files for listings of valid county codes here: https://www.census.gov/programs-
9 

surveys/cbp/technical-documentation/reference/state-county-geography-reference.html. The BDS-SU-REV 

also includes statewide (999) and unclassified (998) county codes. Statewide county codes are assigned to 

single-establishment firms without a fixed location such as employee leasing establishments. Unclassified 

single-establishment firms are those with a county code that cannot be found in any of the CBP county 

reference files.

st

Values: 01,02,04,05,06,08,09,10,11,12,13,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29, 

30,31,32,33,34,35,36,37,38,39,40,41,42,44,45,46,47,48,49,50,51,53,54,55,56

Description: 2-digit FIPS codes

01 – Alabama (AL)

02 – Alaska (AK)

04 – Arizona (AZ)

05 – Arkansas (AR)

06 – California (CA)

08 – Colorado (CO)

09 – Connecticut (CT)

10 – Delaware (DE)

11 – District of Columbia (DC)

12 – Florida (FL)

13 – Georgia (GA)

15 – Hawaii (HI)

16 – Idaho (ID)

17 – Illinois (IL)

18 – Indiana (IN)

19 – Iowa (IA)

20 – Kansas (KS)

21 – Kentucky (KY)

22 – Louisiana (LA)

23 – Maine (ME)

24 – Maryland (MD)

25 – Massachusetts (MA)

26 – Michigan (MI)

27 – Minnesota (MN)

28 – Mississippi (MS) 

29 – Missouri (MO)

30 – Montana (MT)

31 – Nebraska (NE)

32 – Nevada (NV)

33 – New Hampshire (NH)

34 – New Jersey (NJ)

35 – New Mexico (NM)

36 – New York (NY)

37 – North Carolina (NC)

38 – North Dakota (ND)

39 – Ohio (OH)

40 – Oklahoma (OK)

41 – Oregon (OR)

42 – Pennsylvania (PA)
10

44 – Rhode Island (RI)

45 – South Carolina (SC)

46 – South Dakota (SD)

47 – Tennessee (TN)

48 – Texas (TX)

49 – Utah (UT)

50 – Vermont (VT)

51 – Virginia (VA)

53 – Washington (WA)

54 – West Virginia (WV)

55 – Wisconsin (WI)

56 – Wyoming (WY)

sba_program_status_all

Values: COVID-EIDL only, PPP and COVID-EIDL, PPP and RRF, PPP only, RRF only, SVOG only, two or more 

other programs, non-recipient (active in 2020), non-recipient (died before 2020), non-recipient (born after 

2020)

Description: Indicates whether a firm participated in a SBA COVID Relief program and received financial 

assistance during the Covid-19 pandemic. The four programs are Paycheck Protection Program (PPP), 

COVID Economic Injury Disaster Loans (COVID-EIDL), Restaurant Revitalization Fund (RRF), and Shuttered 

Venues Operator Grants (SVOG). Many firms received assistance under multiple programs. These groupings 

capture the major combinations present in the data (PPP plus one other program) and all other multiple 

recipients are grouped into “two or more other programs.” Non-recipients are distinguished by whether they 

were active during 2020 or only before or after that year.

BDS-SU-REV Glossary

Business Dynamics Statistics (BDS) – A public dataset on the LBD that describes United States business 

dynamics across a wide range of measures. Disclosure analysis is performed prior to release to the public to 

protect the confidentiality of the underlying LBD data.

Business Register (BR) – A comprehensive database of all U.S. business establishments developed and 

maintained by the U.S. Census Bureau, with data beginning in 1975 and continuing to the present. This is 

restricted data and is the source data for the Longitudinal Business Database (LBD). 

Censoring – A statistical term indicating that a value cannot be known with certainty. Within the BDS, all 

firms/establishments born prior to 1976 have an unknown birth year and are therefore of an unknown age 

and are grouped into the age category “Left Censored”. 

Data Quality Suppression – Data quality suppressions are made when a cell is determined to be unreliable 

due to its time series characteristics. Cells suppressed due to data quality concerns will appear as “(S)”.

Disclosure Suppression – Disclosure suppressions are made when a cell has too few firms. Cells suppressed 

due to containing too few firms will appear as “(D)”.

Gross Domestic Product (GDP) Implicit Price Deflator – The price index produced by the Bureau of 

Economic Analysis (BEA), which is used to construct inflation-adjusted (real) payroll measures. The data can 

be found on FRED here: https://fred.stlouisfed.org/series/GDPDEF. In using this deflator, we maintain the 

2012 base year.
11

Nominal Variables – Data that are unadjusted for inflation. Nominal data series are in “current” dollar terms.

Real Variables – Data that are adjusted for inflation. Real data series are in “constant” dollar terms.

Structurally Missing Flag – Structurally missing flags are applied to cells that are “structurally zero” or 

“structurally missing.” These are cells in the firm and establishment datasets where activity is not possible 

given the nature or structure of the BDS data. These cells appear as “(X)”. An example of a “structurally 

zero” cell is the variable ‘estabs_exit’ for firms age ‘0’. These cells will always be ‘0’ given the nature of data 

for firms age ‘0’. An example of a “structurally missing” cell is any variable for firms age ‘5’ in the years 1978 

to 1981. These cells will always be missing for the years 1978 to 1981 because the source data for the BDS –

the LBD – begins in 1976.

North American Industrial Classification System (NAICS) – NAICS is the standard used by Federal statistical 

agencies in classifying business establishments for the purposes of collecting, analyzing, and publishing 

statistical data released to the U.S. business economy. The system is used by the United States, Canada, and 

Mexico. Note that the 2020 BDS-SU-REV release I based on the 2017 NAICS vintage.