Labour Force Survey (LFS)

Detailed information for March 2005





Record number:


The Labour Force Survey provides estimates of employment and unemployment which are among the most timely and important measures of performance of the Canadian economy.

Data release - April 8, 2005


The Labour Force Survey provides estimates of employment and unemployment which are among the most timely and important measures of performance of the Canadian economy. With the release of the survey results only 13 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released.

The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these.

LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. For a full listing and description of LFS variables, see the Guide to the Labour Force Survey, available under Questionnaire(s) and reporting guide(s) above.

These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Human Resources Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector.

Statistical activity

Together, three monthly surveys tell a more complete story of current labour market events. These surveys are: the Labour Force Survey (LFS), the Survey of Employment, Payrolls and Hours (SEPH) and the Employment Insurance Statistics (EIS). The LFS focuses on its strengths: timeliness and demographic analysis of the labour market. SEPH reports, which come out later each month, show greater detail on industry and wages. The EIS provide substantial detail by geography.

Reference period: The 15th of the month

Collection period: The week following the reference period


  • Employment and unemployment
  • Hours of work and work arrangements
  • Industries
  • Labour
  • Occupations
  • Unionization and industrial relations
  • Wages, salaries and other earnings

Data sources and methodology

Target population

The LFS covers the civilian, non-institutionalised population 15 years of age and over. Excluded from the survey's coverage are residents of the Yukon, Northwest Territories and Nunavut, persons living on Indian Reserves, full-time members of the Canadian Armed Forces and inmates of institutions. These groups together represent an exclusion of less than 2% of the population aged 15 and over.

More details about the survey population can be found in the Guide to the Labour Force Survey, section 4.1- Population coverage, available under Questionnaire(s) and reporting guide(s) above.

To view the LFS geographical maps, please select the "Additional documentation" link below.

Instrument design

The Labour Force Information questionnaire is redesigned periodically. The current Labour Force Information questionnaire was redesigned in 1997 when questions were added. These additions included:

measures of average weekly and hourly earnings of employees, union membership, permanence of job, size of workplace

Previously questions on these topics were not in the questionnaire.

The Labour Force Survey Information questionnaire has used several vehicles for testing, including review committee, focus groups and pilot tests.

In addition to the Labour force Information component, the LFS application also consists of four other components, These are Contact, Household, Demographics, Rent, and Exit).

Selected dwellings are in the survey for six consecutive months. A birth interview corresponds to the first interview for a new household, and is usually conducted in person. Some birth interviews are now also conducted by telephone from centralized CATI work sites.

Starting in 2015, LFS respondents who met certain criteria were also offered the option of completing the survey on-line for subsequent interviews.


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

The LFS uses a probability sample that is based on a stratified multi-stage design. Each province is divided into large geographic stratum. The first stage of sampling consists of selecting smaller geographic areas, called clusters, from within each stratum. The second stage of sampling consists of selecting dwellings from within each selected cluster.

The LFS uses a rotating panel sample design so that selected dwellings remain in the LFS sample for six consecutive months. Each month about 1/6th of the LFS sampled dwellings are in their first month of the survey, 1/6th are in their second month of the survey, and so on. One feature of the LFS sample design is that each of the six rotation groups can be used as a representative sample by itself.

Within selected dwellings, basic demographic information is collected for all household members. Labour force information is collected for all civilian household members who are aged 15 and over.

Since July 1995, the monthly LFS sample size has been approximately 54,000 households, resulting in the collection of labour market information for approximately 100,000 individuals. It should be noted that the LFS sample size is subject to change from time to time in order to meet data quality or budget requirements.

The LFS sample is allocated to provinces and regions within provinces to meet the need for reliable estimates at various geographic levels. These include national, provincial, census metropolitan areas (large cities), economic regions and employment insurance regions.

To obtain details of the sample allocation guidelines and sample size by province, please refer to section 4.2 of the Guide to the Labour Force Survey, available under Questionnaire(s) and reporting guide(s) above.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Data collection for the LFS is carried out each month during the week following the LFS reference week. The reference week is normally the week containing the 15th day of the month.

LFS interviews are conducted by telephone by interviewers working out of a regional office CATI (Computer Assisted Telephone Interviews) site or by personal visit from a field interviewer. Since 2004, dwellings new to the sample in urban areas are contacted by telephone if the telephone number is available from administrative files, otherwise the dwelling is contacted by a field interviewer. The interviewer first obtains socio-demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces. The majority of subsequent interviews are conducted by telephone. In subsequent monthly interviews the interviewer confirms the socio-demographic information collected in the first month and collects the labour force information for the current month. Persons aged 70 and over are not asked the labour force questions in subsequent interviews, but rather their labour force information is carried over from their first interview.

In each dwelling, information about all household members is usually obtained from one knowledgeable household member. Such 'proxy' reporting, which accounts for approximately 65% of the information collected, is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent.

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

Error detection

The LFS Computer Assisted Interviewing (CAI) questionnaire incorporates many features that serve to maximize the quality of the data collected. There are many edits built into the CAI questionnaire to compare the entered data against unusual values, as well as to check for logical inconsistencies. Whenever an edit fails, the interviewer is prompted to correct the information (with the help of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if they cannot resolve the apparent discrepancy. As well, for most questions the interviewer has the ability to enter a response of Don't Know or Refused if the respondent does not answer the question.

Once the data is received back at head office an extensive series of processing steps is undertaken to thoroughly verify each record received. This includes the coding of industry and occupation information and the review of interviewer entered notes. The editing and imputation phases of processing involve the identification of logically inconsistent or missing information items, and the correction of such conditions. Since the true value of each entry on the questionnaire is not known, the identification of errors can be done only through recognition of obvious inconsistencies (for example, a 15 year-old respondent who is recorded as having last worked in 1940).


All identified discrepancies, logical inconsistencies and missing information are resolved either automatically by the head office processing system or through manual intervention. This is accomplished through the imputation of logically consistent values.

Where possible, deterministic imputation is used to resolve any inconsistent or missing information using other information provided by the respondent. When this is not possible, information for an individual may be carried forward from the previous month (if it exists) under certain circumstances. In other instances hot deck imputation is used, which involves copying information from another individual (i.e., a 'donor') with similar characteristics.


The final step in the processing of LFS data is the assignment of a weight to each individual record. This process involves several steps. Each record has an initial weight that corresponds to the inverse of the probability of selection. Adjustments are made to this weight to account for non-response that cannot be handled through imputation. In the final weighting step all of the record weights are adjusted so that the aggregate totals will match with independently derived population estimates for various age-sex groups by province and major sub-provincial areas. One feature of the LFS weighting process is that all individuals within a dwelling are assigned the same weight.

In January 2000, the LFS introduced a new estimation method called Regression Composite Estimation. This new method was used to re-base all historical LFS data. It is described in the research paper "Improvements to the Labour Force Survey (LFS)", Catalogue no. 71F0031X. Additional improvements are introduced over time; they are described in different issues of the same publication.

Quality evaluation

Selected data from the LFS are regularly compared to similar data from the Survey of Employment, Payroll and Hours (SEPH, survey record 2612), Employment Insurance data and the Census.

As well, economists working with the LFS often compare Gross Domestic Product (GDP) data with that of the LFS to see if labour market trends are in line with general economic performance. Other comparisons include:

Manufacturing shipment data and LFS manufacturing employment;
Dwelling starts, building permits and construction employment;
Retail and wholesale sales and trade employment.

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.

The LFS produces a wide range of outputs that contain estimates for various labour force characteristics. Most of these outputs are estimates in the form of tabular cross-classifications. Estimates are rounded to the nearest hundred and a series of suppression rules are used so that any estimate below a minimum level is not released.

The LFS suppresses estimates below the following levels:

Canada 1,500
Newfoundland 500
Prince Edward Island 200
Nova Scotia 500
New Brunswick 500
Quebec 1,500
Ontario 1,500
Manitoba 500
Saskatchewan 500
Alberta 1,500
British Columbia 1,500

Revisions and seasonal adjustment

Seasonal Adjustments - Most estimates associated with the labour market are subject to seasonal variation, that is, annually-recurring fluctuations attributable to climate and regular institutional events such as vacations, and holiday seasons. Seasonal adjustment is used to remove seasonal variations from almost 3,000 series, in order to facilitate analysis of short-term change for major indicators such as employment and unemployment by age and sex, employment by industry, and class of worker (employee or self-employed). Many of these indicators are seasonally adjusted at national and provincial levels. Seasonal adjustments are made using the X-11-ARIMA method. Main labour force status estimates are also seasonally adjusted for census metropolitan areas (CMAs), and published as three-month moving averages to reduce irregular movements caused by relatively small sample sizes.

At the start of each year the seasonally adjusted series are updated and revised according to the latest data and information for seasonal models and factors. The seasonally adjusted series are usually revised back three years.

Estimate adjustments further to census - Adjustments are also made to LFS data every five years after new population estimates become available following the most recent census. At that time, all LFS data back to the previous census is re-weighted using the new population estimates (since the new population estimates will cover the inter-censal period between the two most recent censuses), and all corresponding historical LFS estimates are revised.

Therefore, at the beginning of 2005, all estimates were adjusted to reflect 2001 Census population counts and LFS estimates have been revised back to January 1976. It is further described in the research paper Improvements in 2005 to the Labour Force Survey, Catalogue no. 71F0031XIE200502.

Data accuracy

Since the LFS is a sample survey, all LFS estimates are subject to both sampling error and non-sampling errors.

Non-sampling errors can arise at any stage of the collection and processing of the survey data. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors and other types of processing errors.

Non-response to the LFS tends to average about 10% of eligible households. Interviews are instructed to make all reasonable attempts to obtain LFS interviews with members of eligible households. Each month, after all attempts to obtain interviews have been made, a small number of non-responding households remain. For households non-responding to the LFS, a weight adjustment is applied to account for non-responding households.

Sampling errors associated with survey estimates are measured using coefficients of variation for LFS estimates as a function of the size of the estimate and the geographic area.

At the Canada level, the approximate coefficient of variation (CV) can be obtained using the table included in the attached document, by finding the monthly (or annual average) estimate less than or equal to the estimate of the characteristic of interest. For example, for a monthly estimate of 340,000 unemployed youth 15-24, the approximate CV would be 2.5%.


  • History of the Labour Force Survey
  • Labour Force Survey - Data Quality Statements
    This statement provides information to assist users of data from the Labour Force Survey (LFS) in assessing how well the data fits their statistical needs. It describes the quality objectives of the LFS' the factors that affect LFS data quality and assessment of impact of those factors on LFS data. Factors affecting data quality discussed in this statement include both those that impact on the overall quality of LFS estimate and a number of factors that impact on specific LFS data items and classifications.

    This statement compliments information contained in the Guide to the Labour Force Survey, Catalogue no. 71-543-GIE which provides useful background information on the survey concepts and definitions, the questionnaire, and a brief discussion of the methodology and quality issues. A more complete description of the survey methodology can be found in Methodology of the Canadian Labour Force Survey, Catalogue no. 71-526-XPB.
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