Labour Force Survey

Statistics Canada publishes monthly labour force statistics for all Canadian Census Metropolitan Areas (CMAs) and provinces. In addition, the City of Toronto purchases a special run from Statistics Canada of Labour Force Survey (LFS) data for city of Toronto residents (i.e. separate from the rest of the Toronto CMA).

LFS data are collected by place of residence, and therefore city of Toronto's "employment" represents "employed residents" and not "jobs" in the city of Toronto. There are more jobs in the city of Toronto than employed city of Toronto residents.

In this LFS database, you will find 22 monthly tables and 28 annual tables. Most of the tables contain data for five geographies: city of Toronto, Toronto CMA, Toronto/Hamilton/Oshawa CMAs, Ontario and Canada ( see attachment Table of Contents below a full description ).

LFS data in the IVT tables are not seasonally adjusted. Top level seasonally adjusted LFS data are available in our monthly Toronto Economic Bulletin on Open Data.

LFS is based on a monthly sample of approximately 2,800 households in the Toronto CMA, about half of the sample is from the city of Toronto; therefore, estimates will vary from the results of a complete census.

LFS follows a rotating panel sample design, in which households remain in the sample for six consecutive months. The total sample consists of six representative sub-samples of panels, and each month a panel is replaced after completing its six month stay in the survey. Outgoing households are replaced by households in the same or similar area. This results in a five-sixths month-to-month sample overlap, which makes the design efficient for estimating month-to-month changes. The rotation after six months prevents undue respondent burden for households that are selected for the survey ( see attachment Guide to the Labour Force Survey for more information).

Upon reviewing the data, you will see that at least some cells in the IVT tables have been suppressed. For confidentiality reasons, Statistics Canada suppresses Labour Force Survey data for any cell that corresponds to less than 1,500 persons.

At the beginning of 2015, Statistics Canada substantially changed the methodology used to produce LFS population estimates for the city of Toronto. These changes have resulted in large and inexplicable swings in population and related counts, which are not real. However, the unemployment and participation rates for city residents showed very little change in this revision.

City of Toronto Population Age over 15 from 1986 to 2016

The red dots in the chart above represents Statistics Canada's Annual Demographics estimates for the populations of the city of Toronto, age 15 and over. These are only estimates, but they are generally accepted as the most accurate estimates for the city's population. (Source: https://www150.statcan.gc.ca/n1/pub/91-214-x/91-214-x2018000-eng.htm).

The most recent Statistics Canada population estimate for the city of Toronto is for July 1, 2015; therefore, we have to use projections thereafter. There are several population projections for the city. The projection that EDC staff has chosen to use for rebasing city of Toronto LFS data is the Ontario Ministry of Finance Population Projections 2017-2041 and downloaded June, 2017 from http://www.fin.gov.on.ca/en/economy/demographics/projections/

Please see attachment Rebased Labour Force Survey for City of Toronto below for annual adjustment factors, monthly adjustment factors and an example of how to rebase the absolute numbers for the city of Toronto.

Datasets available for download

Additional Info

Field Value
Last Updated October 4, 2024, 04:48 (UTC)
Created October 4, 2024, 02:37 (UTC)
Domain / Topic
Domain or topic of the dataset being cataloged.
Business
Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
.htm, .html - text/html, .xlsx - application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, .zip - application/zip, .docx - application/vnd.openxmlformats-officedocument.wordprocessingml.document, .pdf - application/pdf
Dataset Size
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Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
Published Date
Published date of the dataset.
2019-07-23
Time Period Data Span (start date)
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Time Period Data Span (end date)
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GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
Field Value
Access category
Type of access granted for the dataset (open, closed, service, etc).
Limits on use
Limits on use of data.
Location
Location of the dataset.
https://open.toronto.ca/dataset/labour-force-survey
Data Service
Data service for accessing a dataset.
Owner
Owner of the dataset.
Economic Development & Culture, edcresearch@toronto.ca
Contact Point
Who to contact regarding access?
Publisher
Publisher of the dataset.
Publisher Email
Email of the publisher.
edcresearch@toronto.ca
Author
Author of the dataset.
edcresearch@toronto.ca
Author Email
Email of the author.
edcresearch@toronto.ca
Accessed At
Date the data and metadata was accessed.
Field Value
Identifier
Unique identifier for the dataset.
Language
Language(s) of the dataset
Link to dataset description
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Persistent Identifier
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Globally Unique Identifier
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Contains data about individuals
Does the data hold data about individuals?
Contains data about identifiable individuals
Does the data hold identifiable data about individual?
Contains Indigenous Data
Does the data hold data about Indigenous communities?
Field Value
Source
Source of the dataset.
https://www.toronto.ca/city-government/data-research-maps/city-stats-in-detail/
Version notes
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Other versions
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GeoSpatial resolution in meters
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GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
Field Value
Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
Community Permission
Community permission (who gave permission).
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
Field Value
Number of data rows
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Number of data columns
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Number of data cells
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Number of data relations
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Number of entities
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Number of data properties
If RDF dataset, total number of unique properties used by the triples.
Data quality
Describes the quality of the data in the dataset.
Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.

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