Survey of Regulatory Compliance Cost

Detailed information for 2005




Every 3 years

Record number:


This survey provides benchmark data on the current cost of regulatory compliance for small- and medium-sized businesses, in meeting key information obligations that are the responsibility of various levels of government. The survey collects both the time and salary of internal staff involved in the preparation of regulatory submissions.

Data release - July 28, 2006 (Main survey); December 12, 2006 (Service provider survey)


This survey is being conducted in order to measure Regulatory Compliance Costs for businesses in meeting key regulatory requirements that are the responsibility of various levels of government. Survey results are intended to help determine whether efficiency measures introduced by government are reducing the compliance burden facing businesses.

The survey is a key component to the Paperwork Burden Reduction Initiative (PBRI). The PBRI responds to the Budget 2004 commitment to create a working group of government officials and small business representatives to make measurable reductions in paperwork burden.

The first phase of the project is the main survey which collects detailed information on the time spent and salaries of the people involved in preparing and submitting information relating to individual regulations completed internally within a business, as well as a list of outsourced activities (including non-regulatory), and the total cost for the activities being supplied by an external service provider.

The second phase of the project is a survey of service providers intended to accurately measure the relative time spent by service providers in completing various regulatory requirements, accounting activities, and provision of financial advice on behalf of business clients. Data was collected for each of the three types of service providers (accounting firms, tax preparation specialists and bookkeeping and payroll services).

This information from service providers was essential in order to be able to allocate the total dollar costs of all outsourced services reported in the main survey to the eleven regulatory requirements of interest. Without this, a very significant portion of regulatory costs would be missing.

The eleven regulations in-scope for this survey are: Payroll Remittances, Record of Employment, T4 Summary/individual T4's, Workers' Compensation (remittances and claims), T1/T2 Income Tax Filing, Federal/Provincial Sales Taxes, Corporate Tax Installments, Corporate Registration, Mandatory Statistics Canada Surveys, Municipal and Provincial Operating Licences and Permits.


  • Business performance and ownership

Data sources and methodology

Target population

The target population includes all establishments that are on the Business Register (BR) Universe file that meet the following conditions:

1- Establishments in specific industries, identified by the North American Industry Classification System. They include manufacturing (31, 32, 33), retail trade (44, 45), professional, scientific and technical services (54), accommodation services (72), and other services (except for public administration)(81) .

2- Establishments with fewer than 500 employees.

3- Establishments with revenue greater than $30,000 and less than $50,000,000.

4- Establishments located in the Territories were excluded.

Given that certain regulations vary provincially or municipally, it was necessary to select the establishment as the unit of analysis in order to isolate those regional differences.

Instrument design

An initial draft of the survey questionnaire was jointly designed by Statistics Canada and Industry Canada in 2004, after consultation with various stakeholders in both the private and public sectors. Early in 2005, Industry Canada commissioned Phoenix Strategic Perspectives, a private sector consulting firm, to conduct focus group tests in various Canadian cities in both official languages. The results of the focus groups were then incorporated into the questionnaire.

Subsequently, Statistics Canada conducted a pre-test of the revised questionnaire. This type of qualitative testing is a necessary evaluation of the survey collection instrument that is carried out for complex questionnaires. Unlike focus group testing, pre-test respondents are required to complete the questionnaire and then discuss the process in one-on-one interviews. The pre-test was conducted in May 2005 and results of the test indicated a need to revise the questionnaire further and conduct another pre-test in July 2005. The questionnaire that evolved from the second pre-test was used in the national survey in the fall of 2005.


This is a sample survey with a cross-sectional design.

Statistics Canada's Business Register is used as the survey frame for the target population of all private sector, for-profit establishments with fewer than 500 employees and gross revenues more than $30 thousand and less than $50 million in Canada. The sampling frame contains 665,480 establishments.

The initial stratification is by region, and size. The number of employees in the establishment is used to define the size of a business. The sample size for the survey was of 32,736 establishments.

Data sources

Data collection for this reference period: September 2005 to March 2006

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data were collected via a paper mail-out, mail-back survey.

A pre-contact was done initially to confirm the mailing address of all respondents, to confirm the language of the respondents and to confirm that individual respondents were in-scope. Subsequently, all in-scope respondents were mailed a package consisting of an introductory letter and a questionnaire in the language identified during the pre-contact. This was a mail-out, mail-back survey. At least three follow-up attempts were made to all respondents in order to convince them to return their questionnaires.

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

Error detection

Both consistency and validity edits were put in place to ensure that answers were consistent and valid, and to generally ensure the quality of the data. Information is manually captured and entered into a database using BLAISE capture and edit software, in which they are subjected to edit checks which serve to illuminate real or potential response errors.


A nearest neighbour imputation system was implemented. This method involves locating a donor and a recipient of similar size and characteristics. Data values for missing or incomplete variables in the recipient's record are imputed from the donor.


Parameters of interest are estimated with Statistics Canada's Generalized Estimation System (GES).

Initial sample weights are adjusted to account for non-response.

A post-stratified estimator is used to calibrate to a known total number of establishments in each of the number of employee categories. These known counts are obtained from the BR.

Quality evaluation

Since this is the first Statistics Canada survey to collect time and cost information for regulatory compliance, little information is available to compare results.

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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Data accuracy

Sampling errors arise from the fact that the information obtained from a sample of the population is applied to the entire population. The sampling method as well as the estimation method, the sample size and the variability associated to each measured variable determine the sampling error. A possible measure of sampling errors is the coefficient of variation. It represents the proportion of the estimate that comes from the variability associated to it. For the Survey of Regulatory Compliance Cost, the coefficient of variation is about 4% at the most aggregated level (all regulations, Canada) for total and average time as well as for total and average cost. When looking at more detailed estimates, one should expect higher CVs.

Data response error may be due to questionnaire design, the characteristics of a question, inability or unwillingness of the respondent to provide correct information, misinterpretation of the questions or definitional problems. These errors are controlled through careful questionnaire design and the use of simple concepts and consistency checks.
Processing error may occur at various stages of processing such as data entry, editing and tabulation. Measures have been taken to minimize these errors.

Non-response error is related to respondents that may refuse to answer, are unable to respond or are too late in reporting. When all questions from the survey are left unanswered we are dealing with what we call total non-response which is dealt with by adjusting the weights assigned to the responding records, such that one responding record might also represent other non-responding units with similar characteristics (i.e. size, province, industry) as the responding record. When only some of the questions are left unanswered, we are dealing with what we call partial non-response. In these cases, missing data items are imputed.

Data from the main survey required imputation for at least one variable in 80% of cases. However, for two thirds of all records on which imputation was performed, imputation was needed for 10 or fewer data items among the 302 data items collected by the survey . The highest imputation rate for any given data item was 18%. Imputation was necessary for 11% of the service provider survey questionnaires.

The response rate for the main survey was 30%. For the service providers survey, the response rate was 38%.

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