Labour Force Survey (LFS)
Detailed information for September 2019
The Labour Force Survey provides estimates of employment and unemployment. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. 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.
Data release - October 11, 2019
- Questionnaire(s) and reporting guide(s)
- Data sources and methodology
- Data accuracy
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, the territories and a large number of sub-provincial regions. For employees, data on wage rates, union status, job permanency and establishment size are also produced.
These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social 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.
Together, five surveys tell a more complete story of current labour market events. These surveys are: the Labour Force Survey (LFS, record number 3701), the Survey of Employment, Payrolls and Hours (SEPH, record number 2612), Employment Insurance Statistics (EIS, record number 2604), Job Vacancy Statistics (JVS, record number 5202), and the Job Vacancy and Wage Survey (JVWS, record number 5217). Every month, the LFS provides timely data on the labour market, including the unemployment rate and demographic analysis. Later on, the SEPH report shows greater detail on non-farm industry employment and earnings. EIS provides substantial detail on Employment Insurance benefits by geography, socio-demographics and former occupation. JVS (as part of SEPH) offers monthly information on labour demand by reporting on the number of job vacancies by industry. JVWS provides information on job vacancies (quarterly) and wages (annually) by occupation and economic region.
Reference period: Usually the week containing the 15th day of the month
Collection period: The week following the reference period
- Employment and unemployment
- Hours of work and work arrangements
- Unionization and industrial relations
- Wages, salaries and other earnings
Data sources and methodology
The target population is the non-institutionalised population 15 years of age and over. The survey is conducted nationwide, in both the provinces and the territories. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; full-time members of the Canadian Armed Forces, the institutionalized population, and households in extremely remote areas with very low population density. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over.
There are no questions in the LFS that ask respondents whether they are temporary foreign workers. Therefore it is not possible to produce counts of, or employment numbers for, temporary foreign workers from the LFS. If contacted for the LFS, temporary foreign workers will be included only if they identify the selected dwelling as their usual place of residence. In addition, they cannot be separated from a larger group of respondents who were not born in Canada and who are not landed immigrants. In 2014, the 'other' category represented 2% of the employed population and would therefore have a negligible impact on the overall employment numbers. Also included in this group are: Canadian citizens by descent who were born elsewhere, foreign students with a study permit, claimants of refugee status or family members of immigrants who are not landed immigrants themselves.
National Labour Force Survey estimates are derived using the results of the LFS in the provinces. Territorial LFS results are not included in the national estimates, but are published separately.
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, and establishment size.
The Labour Force Survey Information questionnaire has used several vehicles for testing, including review committee, focus groups and pilot tests.
As indicated above, there were major additions to the questionnaire in 1997. These changes included adding questions about average weekly and hourly earnings of employees, union membership, permanence of job, size of workplace.
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 one-sixth of the LFS sampled dwellings are in their first month of the survey, one-sixth 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.
The sample is allocated to provinces and to strata within provinces in the way that best meets the need for reliable estimates at various geographic levels.
Recently, the monthly LFS sample size has been approximately 56,000 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.
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Responses to survey questions are captured directly by the interviewer at the time of the interview, using a computerized questionnaire on a laptop or desktop computer. The response data are encrypted to ensure confidentiality and sent electronically to appropriate Statistics Canada Regional Office. From there, they are transmitted over a secure line to head office in Ottawa for further processing.
LFS interviews are conducted by telephone in English or French by interviewers working out of a regional office CATI (Computer Assisted Telephone Interview) site or by personal visit from a field interviewer.
All LFS interviewers are under the supervision of senior interviewers who are responsible for ensuring that their staff are familiar with survey concepts and procedures, as well as periodically monitoring their interviews.
Information about all household members is usually obtained from one knowledgeable household member. Such 'proxy' reporting accounts for approximately 65% of the information collected.
Respondents are in the survey for six months. The birth interview takes approximately 20 minutes to complete. The subsequent five interviews take about 10 to 12 minutes to complete.
View the Questionnaire(s) and reporting guide(s) .
Some editing is done directly at the time of interview. Where the information entered is out of range (too large or too small) of expected values or inconsistent with previous entries, the interviewer is prompted, through message screens on the computer, to modify the information. However, interviewers have the option of bypassing the edits or skipping questions if the respondent does not know the answer or refuses to answer. Therefore, the response data are subjected to further edit and imputation processes once they arrive at head office.
The editing and imputation phases of processing involve the identification of logically inconsistent or missing information items and the modification of such data. 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). If a value is suspicious but reasonable, the value will find its way into the monthly statistics. For that reason, emphasis must be placed on quality controls and interviewer training to ensure errors are both minimal in number and non-systematic in nature.
During the editing phase of processing, it may be observed that all questionnaire items for individuals (persons) in the household are missing. This is referred to as complete (or total) non-response. Item non-response occurs when only some questionnaire data items are missing. Imputation and non-response weight adjustment are the methods used to resolve complete non-response. Imputation alone is the method used to resolve item non-response.
The imputation methods employed for the LFS include carry-forward, deterministic and donor (hot-deck) imputation.
Where errors or omissions are detected, the erroneous or missing items are replaced by the imputation of logically consistent values. This is referred to as deterministic (or substitution) imputation. Such changes are made automatically by the edit and imputation system or through intervention of experts. These changes are based on pre-specified criteria and may involve the internal logic of the questionnaire, reference to earlier month's information (if available) or the use of similar records to impute one or more values.
Some missing items are resolved by carrying forward last month's data, if available and appropriate. Other missing items may require the use of donor (hot-deck) imputation, which involves the copying of data from another person (i.e., a 'donor') with similar characteristics. In all cases, editing and imputation changes are recorded and this information is used to assess various aspects of survey performance. These records of errors are also used to advise interviewers of mistakes made in the past in order to avoid repetition of these mistakes in the future.
The sample data are weighted to enable tabulations of estimates at national, provincial, and sub-provincial levels of aggregation.
The sample design determines a certain number of weighting factors to be used in the calculation of the individual weights. The main component is the inverse of the probability of selection, known as the basic weight. For example, in an area where 2% of the households are sampled, each household would be assigned a basic weight of 1/.02=50. The basic weight is then adjusted for any sub-sampling due to growth that may have occurred in the area. This weight is then adjusted for non-response and coverage error.
In the LFS, some survey non-response is compensated for by imputation: carry forward, substitution or donor imputation methods. Any remaining non-response is accounted for by adjusting the weights for the responding households in the same area. This non-response adjustment assumes that the characteristics of the responding households are not significantly different from the non-responding households.
The weights derived after the non-response adjustments are called the subweights. The final adjustment to the weight is made to correct for coverage errors. The subweights are adjusted so that the survey estimates of population conform to control totals. These final weights are used in the LFS tabulations.
Each month, the Labour Force Survey indicators that are released are the most timely.
Any validation of LFS data with other sources involves caution. However, selected data from the LFS are regularly compared to similar data from the Survey of Employment, Payrolls and Hours (SEPH), Employment Insurance Statistics and the census. 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.
In addition, the LFS is put through a rigorous series of activities to ensure that the estimates are of acceptable quality.
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:
Newfoundland and Labrador: 500
Prince Edward Island: 200
Nova Scotia: 500
New Brunswick: 500
British Columbia: 1,500
Northwest Territories: 200
Revisions and seasonal adjustment
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 the LFS 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 employment by class of worker (public and private employees or self-employed). Many of these indicators are seasonally adjusted at national and provincial levels. 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. The method being used for seasonal adjustment is X-12-ARIMA.
At the start of each year, the Labour Force Survey revises its estimates for the previous three years, using the latest seasonal factors.
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. Generally, the introduction of the latest classification systems for industry, occupation and geography, along with other changes, occur at this time.
As of January 2015, LFS estimates have been adjusted to reflect population counts from the 2011 Census, adjusted for net undercoverage, with revisions going back to 2001. For more information, see "The 2015 Revisions of the Labour Force Survey (LFS)" (71F0031X).
Since the LFS is a sample survey, all estimates are subject to both sampling 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. Interviewers 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. 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 standard error and the size of the estimate.
- Guide to the Labour Force Survey
The Guide to the Labour Force Survey contains a dictionary of concepts and definitions and covers topics such as survey methodology, data collection, data processing and data quality.
Last review : September 7, 2018.
- LFS Geographical Maps (based on 2011 Census boundaries)
- Concordance Files
- History of the Canadian Labour Force Survey, 1945 to 2016
- Comparing current LFS estimates to those prior to 1976
- Use of the Canadian Labour Force Survey for Collecting Additional Labour-related Information
This paper focuses on describing the questions, concepts and methods used to produce the data from the Canadian Labour Force Survey (CLFS) which describe work quality, in keeping with the International Labour Organization's (ILO) need for information on how countries can provide indicators of "Decent Work".
- Labour Force Survey: Differences between the North and the provinces - Sampling
- Work Absence Rates: Data quality, concepts and methodology
The discontinued Work Absence Rates report (catalog number 71-211-X) was last published for reference year 2011 on April 20, 2012. It contained a breakdown of absences from work for personal reasons (illness or disability and personal or family responsibilities) by various demographic and labour market characteristics. Only full-time employees were considered in the analysis.
The purpose of the linked file is to document the data quality, concepts and methodology portions of the report. Any further analysis on this topic will appear in other publications such as Insights on Canadian Society (catalog number 75-006-X). Time series of data going back to 1987 are available in CANSIM tables 279-0029 through 279-0039.
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