Business Payrolls Survey (BPS)

Detailed information for this survey

Status:

Active

Frequency:

Monthly

Record number:

2614

The Business Payrolls Survey (BPS) is the collection instrument for the Survey of Employment Payrolls and Hours (SEPH, record number 2612). The results of the BPS and administrative data are combined to produce the SEPH estimates.

For more information, please see record number 2612, Survey of Employment, Payrolls and Hours (SEPH) in the Documentation section below.

Data release - The information is included in record number 2612.

Description

The Survey of Employment, Payrolls and Hours (SEPH) provides a monthly portrait of the amount of earnings, as well as the number of jobs (i.e., occupied positions) and hours worked by detailed industry at the national, provincial and territorial levels.

SEPH data provide the principal input to labour income estimates; they also serve as a proxy output measure for about 15% of real gross domestic product and 'nominal' gross domestic product. SEPH data are also used by the Canada Revenue Agency (CRA), to revise the maximum pensionable earnings and retirement savings plan contribution limits, and by the private sector, for contract escalations and wage rate determinations.

Subjects

  • Employment and unemployment
  • Labour
  • Wages, salaries and other earnings

Data sources and methodology

Target population

The program's target population is composed of all businesses in Canada that have at least one employee and, thus issued at least one payroll deduction remittance during the reference month. Excluded are businesses that are primarily involved in agriculture, fishing and trapping, private household services, religious organizations, international and other extraterritorial public administration and military personnel of defence services.

Instrument design

The questionnaires (education and non-education versions) were last revised in 2012. At the same time, an electronic questionnaire was also introduced. Testing was conducted by QDRC with respondents. The paper questionnaires were designed by the Questionnaire Design group.

Sampling

The BPS uses a stratified simple random sample of 15,000 establishments.

Data sources

Precontact: Computer assisted telephone interview.
Collection: Computer assisted telephone interview, paper questionnaire captured in Blaise, electronic questionnaire transfered to Blaise, electronic file transfer.
Follow-up: Computer assisted telephone interview.
Collection in French and in English are available.
Time required to complete the questionnaire: approximately 10 minutes.

View the Questionnaire(s) and reporting guide(s).

Error detection

Both manual and automated editing procedures are employed to detect and correct problematic data provided by the respondent on the BPS questionnaire. Historical edits (weighted and unweighted) are performed at the data collection stage.

Imputation

For the BPS portion, only units that are permanently in sample are imputed using historical data. Imputation avoids respondent follow-up while using as much respondent-provided data as possible. Reweighting is employed to correct for all other missing establishments.

Estimation

The estimation of population characteristics from a survey is based on the premise that each sampled unit represents, in addition to itself, a certain number of units in the population that were not selected into the sample. A basic survey weight is attached to each record to indicate the number of units in the population that are represented by that unit in the sample.

Two adjustments are applied to the basic BPS weights to improve the reliability of the estimates. These basic BPS weights are first inflated to compensate for non-response. The non-response adjusted weights are then calibrated to ensure that estimates of total monthly payroll employment and monthly payrolls respect estimates from the Canada Revenue Agency Payroll Deduction (PD7) administrative source.

The calibration is done using a generalized regression estimator. The model groups are mostly defined at the national and sub-sector levels (i.e., three-digit North American Industry Classification System (NAICS) code or, in a few instances, four-digit); in a few cases, the enterprise size (employment) and the provincial dimensions are used. Regression coefficients, calculated at the model group level, are applied to the estimates of total employment and payrolls from the administrative sources to estimate the additional variables.

The information obtained from the BPS is used to estimate the weekly component of the gross monthly payrolls, the total number of paid hours (regular hours and overtime) and the allocation of hours, earnings and employment for three categories of employees: salaried, paid by the hour and others, such as commission workers.

Non-farm payroll employment data are for all hourly and salaried employees, as well as the 'other employees' category, which includes piece-rate and commission-only employees.

Average weekly hours data are for hourly and salaried employees only. They exclude businesses that could not be classified to a NAICS code by the time monthly processing was completed.

All earnings data include overtime pay, and exclude businesses that could not be classified to a NAICS code. Earnings data are based on gross taxable payroll before source deductions.

Average weekly earnings are derived by dividing total weekly earnings by the total number of employees.

Quality evaluation

Data collection for the BPS is monitored for changes in response rates and failed edit rates.

Coefficients of variation (CV) are analyzed every month to identify the domains having the least accurate estimates. Sampling fractions are adjusted occasionally, to obtain comparable CVs across domains.

A micro-match is performed every month to compare the BPS data with the administrative source data for employment and payrolls. Large differences are looked at and corrected if necessary.

Prior to the release, comparisons with independent sources such as the Labour Force Survey are performed.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data. The G-CONFID software is used to control disclosure of the data.

The results of the SEPH are reviewed using the appropriate security measures complying with the Statistics Act to assure the safeguarding of the respondent's information and to ensure that no enterprise may be identified through the release of the SEPH estimates.

Revisions and seasonal adjustment

With each release, data are revised for the previous month to take into account late remitters. Users are encouraged to request and use the most up-to-date data for each month.

Each year, additional revision processes are done at the same time as the December monthly revision:

- Seasonally adjusted data are revised back three years.
- Annual revisions to fine-tune some estimates of the previous 12 months.
- Occasionally, historical revisions are done to introduce changes related to concepts, new data sources, revised industrial or geographical classifications, as well as methodology.

Data accuracy

For the BPS portion of the survey, response rates are produced every month. The total response rate for Canada as a whole usually varies between 80% and 90%.

Every month, SEPH coefficients of variation (CV) are produced for all variables and every domain. These CVs take into account the sampling variance coming from the BPS as well as the variance due to imputation of the administrative source.

The CVs are usually very low - less than 5% - for the administrative data component of SEPH (e.g., monthly number of employees and gross payroll). The coefficients are higher for those associated with the BPS (e.g., average weekly earnings, average weekly hours). Quality indicators are included in the CANSIM tables for both surveys published regularly by Statistics Canada.

Documentation

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