Provincial Wage and Salary Survey

Detailed information for 1999 (New Brunswick and Ontario)

The objective of this survey is to produce statistical information on wages and salaries paid for various occupations classified to the National Occupation Classification (NOC).

Data release - October 12, 1999 (New Brunswick) and December 1, 1999 (Ontario)

• Description
• Data sources and methodology

Description

This is a client-sponsored special survey that has been conducted in various provinces at different times. The objective of this survey is to produce statistical information on wages and salaries paid for various occupations classified to the National Occupation Classification (NOC).

The results of the survey help governments and businesses by providing accurate and up-to-date information on the wages paid by employers for workers in different occupations and industries.

Subjects

• Labour
• Occupations
• Wages, salaries and other earnings

Data sources and methodology

Sampling

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

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.