National Construction Industry Wage Rate Survey

Detailed information for 2010 (British Columbia, Northwest Territories and Nunavut)





Record number:


This survey collects data on wages paid for specific occupations in the construction industry in all provinces and territories except Québec, Manitoba and Yukon on behalf of the Labour Branch of Human Resources and Skills Development Canada.

Data release - September 28, 2011


This survey collects data on wages paid for specific occupations in the construction industry in all provinces and territories except Québec, Manitoba and Yukon on behalf of the Labour Branch of Human Resources and Skills Development Canada (HRSDC). This survey is conducted region by region on a rotating basis. Estimates are produced for three wage rates -- starting, maximum and most frequently paid wages -- by occupation for both unionized and non-unionized workers, by province / territory and by economic region. The estimates are used by HRSDC to establish wage schedules for workers on federal construction projects. Québec, Manitoba and Yukon are excluded because equivalent wage schedules are established by the provincial or territorial government.


  • Construction
  • Labour
  • Wages, salaries and other earnings

Data sources and methodology

Target population

The survey population comprises all establishments in the North American Industry Classification System 2007 construction sector (code 23) which carried out commercial or institutional construction work in the year prior to the survey. For the provinces, establishments with fewer than 6 employees (based on Statistics Canada's Business Register) are excluded. In the case of Northwest Territories and Nunavut, all establishments are included regardless of the number of employees. Establishments in Quebec, Manitoba and Yukon are not included in the survey population.

Instrument design

The questionnaire was based on previous general wage rate surveys undertaken by Statistics Canada. The questionnaire is modified slightly for each province and territory based on consultations with provincial and territorial unions and employer associations in the construction industry.


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

The population of interest for this survey are establishments that are involved in commercial and institutional construction; defined as construction or renovation of office buildings, hotels, shopping centers and stores, parking lots, roads, wharves, bridges and tunnels, schools, churches, hospitals, libraries, prisons, museums and fire stations. Also included is residential construction on military bases. Excluded from this type of work are dams, power and communication transmission lines, plants for manufacturing goods, oil refineries, sewer systems and other related types of work. This definition was developed by Human Resources and Skills Development Canada (HRSDC).

Considering that it is a sub-population where there are no indicators or a standard classification found in the Business Register to identify these units, methodology has recommended that a census be drawn. The census approach allows us to reach the desired population with the best chance of collecting sufficient responses in order to produce quality estimates, given that in the end, between 40 and 50% of the establishments surveyed are reported as out of scope.

We are interested in producing estimates by occupation. In order to obtain information on occupations we need to contact an establishment. The establishment records are classified based on the North American Industry Classification System (NAICS) but do not have occupation information for employees working in the establishment. Targeting for occupations is done using Census tables of people employed by 4-digit level NAICS, by 4-digit National Occupation Classification (NOC), and by economic region. Twelve occupations are associated with each 4-digit level NAICS in a way that optimizes coverage of all the occupations selected for the survey.

Although 12 occupations are assigned to each unit in the sample, to keep the response burden low the respondents are asked to provide wage information for a maximum of 6 of the 12. To preserve optimal coverage, the occupations associated with a given 4-digit level NAICS are ordered randomly for each establishment in that NAICS. This is done so that each occupation has an equal probability of being among the first six.

In cases where fewer than 12 occupations have employment in a 4-digit level NAICS according to current Census data, the tables are collapsed to the 3-digit level NAICS to try and complete the list of 12. If the list of occupations is still fewer than 12 (due to there being fewer than 12 occupations with employment at the 3-digit level NAICS), then fewer than 12 occupations are associated with the 4-digit level NAICS.

Data sources

Data collection for this reference period: 2011-01-25 to 2011-03-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

An introductory letter is sent to all establishments in the sample.

The data are collected directly from respondents through a telephone interview. The data are captured by the interviewers during the interview via the Computer Assisted Telephone Interview (CATI) system.

Telephone follow-up is conducted for partially completed and for problematic cases such as extreme wage values. Respondents are asked to provide missing information or to confirm or correct the extreme values.

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

Error detection

Error detection is applied at both the collection and the processing stages of the survey. A series of validity and consistency edits is built into the CATI system. The edits trigger a message to the interviewers to allow corrections to be made during the collection phase. The edits ensure that the relationships between wage and other variables are legitimate. These include, for example, flagging reported wages which are below the provincial or territorial legal minimum wage.

Outlier detection is performed on the wage variables to detect values that are improbable or influential. If a declared wage rate is further than three standard deviations from its mean it is flagged as an outlier. All unusual values and outliers are resolved using computer programs or manually on a case-by-case basis.


Imputation is used to replace partially missing data and invalid or inconsistent entries using a combination of mean, ratio and hot deck methods. For the wage variables, the starting wage is imputed using the mean imputation method. The most frequently paid wage and maximum wage are imputed with the ratio method using the starting wage for the base. The total number of employees working on commercial or institutional construction by occupation is imputed using the mean method. The union variable is imputed using a hot deck imputation methodology (i.e. donor imputation).


Before estimation and weighting, sample counts are adjusted for non-response. The adjustment of counts is based on the assumptions that the non-response is random and that a non-respondent is not characteristically different from a respondent. Estimates are produced using the Generalized Estimation System (GES).

Records are assigned weights based on the number of employees in the occupations; establishments with more employees for an occupation make a larger contribution to the estimates for that occupation. A weighted-average estimate is calculated for every occupation and for three different hourly wage rates: starting wage, most frequently paid wage and maximum wage. Estimates are also produced by sub-provincial area and by union status. Domain estimation is applied. For this survey, the domain regroups all records for a given occupation for the purposes of calculating statistics, regardless of industry and, in some cases, region.

Quality evaluation

Quality control for this survey includes outlier detection during data collection, data validation following capture, and telephone follow-up for partially completed or problematic cases. Data validation is conducted using both comparison with published data from both Statistics Canada and other sources and historical trend analysis to gauge the consistency of reporting. Statistics Canada data used include the Labour Force Survey, the Survey of Employment Payroll and Hours, and the Construction union wage rate index.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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.

Confidentiality analysis includes the detection of possible "direct disclosure", which occurs when the value in a tabulation cell is composed of a few respondents or when the cell is dominated by a few companies.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

Since the National Construction Industry Wage Rate Survey estimates are based on sample results, they are subject to sampling error. This error can be expressed as a coefficient of variation (CV). The CV is the standard error expressed as a percentage of the estimate. In the output tables, the CVs are converted to a code. Code A indicates a coefficient of variation in the range 0 to .05 (very good quality), B is .051 to .15 (good quality), E is .151 to .33 (good to poor quality -- use with caution) and F is .331 or higher (very poor quality).

Survey estimates may also contain non-sampling error, for example population coverage errors, differences in the interpretation of questions, incorrect information from respondents, and mistakes in recording, coding and processing data. Non-response is an important source of non sampling error. While the impact of non-sampling errors is difficult to evaluate, measures such as response rates and imputation rates can be used as indicators of the potential level of non-sampling error. The 2010 survey covering British Columbia, Northwest Territories and Nunavut, had a response rate of 66%, which is considered good for a voluntary survey.

The imputation rates for the 2010 survey were as follows:

. Employees are unionized or not: 0%
. Number of full-time employees in the occupation at any time during the last 12 months: 0.23%
. Starting hourly wage for full-time employees: 0.16%
. Most frequently paid hourly wage for full-time employees: 0.23%
. Number of employees who earned most frequently paid wage: 4.01%
. Maximum hourly wage for full-time employees: 0.12%

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