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Business Response Survey to the Coronavirus Pandemic

BRS Technical Notes

The U.S. Bureau of Labor Statistics has developed data on how U.S. businesses changed their operations and employment since the onset of the novel coronavirus. Data are for the 50 states, the District of Columbia, and Puerto Rico. These tabulations, in combination with data collected by current BLS surveys, will aide in understanding how businesses responded during the pandemic.

You can send comments on these data to BRS staff by email.

Methodology

These data were collected over a two-month period from July-September 2020. The BRS survey relied on the existing data collection instrument of the BLS QCEW program’s Annual Refiling Survey (ARS). BRS survey responses were solicited via email and printed letters. Responses were collected online using the platform that is consistently relied on by the ARS. This allows for a large, nationally representative sample to be surveyed with minimal financial costs to BLS.

Definitions

Establishments. An individual establishment is generally defined as a single physical location at which one, or predominantly one, type of economic activity is conducted. Most employers covered under the state UI laws operate only one place of business.

North American Industry Classification System (NAICS) codes. NAICS codes are the standard used by federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data. Industrial codes are assigned by state agencies to each establishment based on responses to questionnaires where employers indicate their principal product or activity. If an employer conducts different activities at various establishments, separate industrial codes are assigned, to the extent possible, to each establishment.

Large/small. For these data, establishments with employment greater than 499 is considered large.

Methodology for sample selection

The sample was drawn from the establishments included in the BLS Business Register, built from the Quarterly Census of Employment and Wages (QCEW). There are currently 9 million in-scope establishments on the BLS Business Register. The universe of respondents to the QCEW are the 50 States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. The primary source of data for these 53 entities are the Quarterly Contribution Reports (QCRs) submitted to State Workforce Agencies (SWAs) by employers subject to State Unemployment Insurance (UI) laws. The QCEW data, which are compiled for each calendar quarter, provide a comprehensive business name and address file with employment and wage information by industry, at the six-digit North American Industry Classification System (NAICS) level, and at the national, State, Metropolitan Statistical Area (MSA), and county levels for employers subject to State UI laws. Similar data for Federal Government employees covered by the Unemployment Compensation for Federal Employees program (UCFE) are also included. The sample excludes Private Households (NAICS 814110); Services for the Elderly and Disabled persons (NAICS 624120 with employment < 2); U.S. Postal Service (NAICS 491110); and unclassified accounts (NAICS 999999).

BLS selected a sample of approximately 597,000 establishments. The objective was to produce statistics at detailed levels including by size class, state, industry, and some state-industry, state-size combinations. The survey analysis breakouts, including 50 states plus Washington DC and Puerto Rico are included:

  • State by Special Interest NAICS Sector Categories
    • (6 special interest NAICS categories: 23, 31-33, 44-45, 62Alt, 72, Others)
  • State by Size
    • (2 size categories: big, small)
  • NAICS Sector Categories
    • (22 NAICS sector categories; 2 size categories (big, small))
  • Industry Size Class
  • (9 classes: 1-4, 5-9, 10-19, 20-49, 50-99, 100-249, 250-499, 500-999, 1000+)

Sufficiency is determined for each survey analysis breakout listed above. The four sets of sufficiency counts are then meshed together to create a single unified sample design. The unified design specifies a targeted number of responders for each State by NAICS Sector Category by Industry Size Class combination. Sample sizes are then derived by multiplying each combination’s targeted number of responders by an estimate of the survey response rate. The overall sample size is the sum of these individual cell sample sizes. Sufficiency is determined based on estimating proportions to a certain degree of precision, where precision is based on researcher needs weighed versus survey burden and cost. The formula for the sample sufficiency of an estimation cell is based on the deconstruction of the formula for the variance of a proportion (using simple random sampling within the cell):

Technical Note Image 1  

Where:

 h is the stratum or analysis breakout cell

nh is the sample size sufficient to estimate the desired precision in stratum h

Nh is the stratum h population

ph is a guess at the eventual proporition estimate in stratum h (always set to 0.5)

sh is the standard error chosen by the researcher to set the precision level for stratum h

The following table provides overall sample sizes resulting from applying the design using different combinations of standard error and response rate settings:

P

Standard Error

95% Confidence Interval Error Bound (+/-)

90% Confidence Interval Error Bound (+/-)

Est. Resp. Rate

Total Targets

Total Sample Size

0.5

0.05

0.098

0.0825

25%

42665

167643

0.5

0.025

0.049

0.04125

25%

149388

596884

0.5

0.05

0.098

0.0825

20%

42595

208461

The sample size is based on the criteria described in the table above, specifically the second row, in addition to the number of state-industry-size class cells we wish to estimate. Given government mandates related to the virus will differ from state to state, and industries and size classes had different programs targeted towards them, it was desired to produce estimates for specific industry-state groups and size class – state groups, and given the burden estimate and the fact that this sample size is much smaller than other online surveys approved asking about business responses to the Coronavirus pandemic.

After sample sizes were finalized for each state, NAICS sector, and size class stratum, samples were selected within each stratum using simple random sampling.

Estimation Methodology

The primary measure of interest will be an estimated proportion possessing an attribute being assessed by a survey question. The proportion estimate formula is:

Each stratum weight is the population proportion of each stratum relative to the composite population of interest:

Technical Note Image 2    

The formula for the estimated sample proportion for some stratum (h), generalized for non-response adjustment, is: 

Technical Note Image 3  

The proportion of non-responders possessing the attribute of interest is generally unknowable. Therefore, the assumption is made that, within each stratum, responders and non-responders possess the attribute of interest in the same proportion, and therefore the formula reduces as follows:

Technical Note Image 4   

Reliability

Variance estimation will involve (i) the application of the general formula for the variance of a composite proportion estimator drawn from a stratified random sample and (ii) the application of the basic formula for the variance of a proportion drawn from a simple random sample. Specifically, the variance of the proportion estimator for some particular analysis breakout cell is:

Technical Note Image 5  

Under the assumption that, within each panhrticular stratum, non-responders possess the attribute of interest in the same proportion as responders, the formula for the within stratum variance of a proportion calculated from a simple random sample is:

Technical Note Image  

In the formula above, note that nh is the number of establishments in stratum h that responded to the survey question of interest. It is not the stratum h sample size. The formulas above can be tailored to the desired composite estimator by applying it across only the set of strata that are relevant to that particular composite.