Labour Force Survey, 2017
hdl:11272/10439UNF:5:zScXwEcTdZkC2ImnmOIElQ==
Archived Study Version: 7View Released Version
Released: Fri Aug 04 14:55:11 PDT 2017 – Archived: Fri Oct 06 14:59:26 PDT 2017
Study Version Notes: All data replaced 4 August 2017
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TitleLabour Force Survey, 2017
Study Global IDhdl:11272/10439
Other IDStatistics Canada: 71-543-G
ProducerStatistics Canada (Statcan)
Production DateJanuary, 2017
Production PlaceOttawa
DistributorStatistics Canada (Statcan)
Distribution DateFebruary, 2017
Deposit DateFebruary 17, 2017
SeriesLFS, Labour Force Survey
Versionv2.0, August 04, 2017
Original Dataverse
Description and Scope
Description

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 10 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, the territories 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 (71-543-G), available through the "Publications" link 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 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.

Important note -- 4 August 2017

Labour Force Survey (LFS) data from January 2017 – July 2017 contained errors with numerical variables. Variables such as HRLYARN and UHRSMAIN were missing decimal place holders. As such, their values were off by a factor of 100. The issue has been addressed and the data for the year re-released

Description DateAugust 04, 2017
KeywordsLabour (ACV); Country::Canada (ACV)
Related MaterialTogether, 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.
Time Period CoveredJanuary, 2017 - December, 2017
Date of CollectionJanuary, 2017 - December, 2017
Country/NationCanada (CA)
Geographic CoverageCanada (CA)
Geographic UnitCanada, Provinces, Territories, Census Metropolitan Areas (CMAs)
Geographic BoundingWest Bounding Longitude: -141.018 East Bounding Longitude: -52.6194 North Bounding Latitude: 83.1355 South Bounding Latitude: 41.6814
Unit of AnalysisIndividuals
UniverseThe LFS covers the civilian, non-institutionalised population 15 years of age and over. It 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.
Kind of DataSurvey data
Data Collection / Methodology
Time MethodCross-sectional
Data CollectorStatistics Canada
FrequencyMonthly
Sampling Procedure

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.

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.

With the recent increase in coverage in Nunavut, the sample for all three territories is representative of the working-age population of each territory. Nunavut was initially designed to cover ten of the largest communities in the region, representing about 70% of all Nunavut residents aged 15 years and over. The increase in survey coverage in that territory, effective in the spring of 2009 and retroactive to the winter of 2008, brings it on par with the other two territories (96% in the Northwest Territories, 93% in Nunavut and 92% in Yukon).

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

To obtain details of the sample allocation guidelines and sample size by province and territory, please refer to section 4.2 and 4.5 of the Guide to the Labour Force Survey.

Collection Mode

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.

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

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.

Type of Research InstrumentStructured
Characteristic of Sources NotedSeasonal 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-12-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. Adjusting estimates for population changes - 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 2015, all estimates were adjusted to reflect 2011 Census population counts and LFS estimates have been revised back to January 2001. Also, Census metropolitan areas (CMAs), Economic regions (ERs) and Census agglomerations are based on 2011 Census boundaries rather than 2006 boundaries. These and other changes are described in the research paper The 2015 Revisions of the Labour Force Survey (LFS), Catalogue no. 71F0031XWE201501.
Weighting

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.

Cleaning Operations

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 'doThe 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). nor') with similar characteristics.

Study Level Error Notes

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.

Other Forms of Data Appraisal

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.
Data Availability
Number of Files 17
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APPENDIX II

End-use Licence Agreement for Postal CodeOM Conversion File, Postal Codes OM by Federal Ridings File and Postal CodeOM Conversion File Plus (“data product”)

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(iii) preparing unaddressed mail by householder count for delivery

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Appendix A – Approved Postal Code Data Matching Uses for DLI Accredited Canadian Post Secondary Institution

Matching Postal Code data to geography for:

  • Teaching and learning purposes.

    E.g.: Students can download PCCF on their laptop to do their assignments. This includes projects, maps, analytical papers, etc. Faculty can download and use the PCCF in teaching exercises.
  • Research purposes

    E.g.: Can be used in analysis to write articles that are published in journals. The data is not shared but the results are published. This also includes thesis for Masters or Doctorate where results are required to be public.
  • Planning purposes – where the institution can use the information in planning student recruitment activities or find out where these students are coming from.

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Other Information
NotesInfo (Misc)

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
  • Yukon 200
  • Northwest Territories 200
  • Nunavut 200

Since the sample design, rotation pattern and reliability criteria are different in the three territories from those in the ten provinces, estimates for the territories are not included with the provincial totals, but rather they are calculated and reported separately as a part of each of the extended projects.

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"Labour Force Survey, 2017", hdl:11272/10439