DOI: 10.5683/sp3/faycsj
title: Labour Force Survey, February 2023 [Canada]
title: Labour Force Survey, February 2023
title: LFS February 2023
title: Enquête sur la population active, février 2023 [Canada]

description: The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest 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. 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. Note: Because missing values are removed from this dataset, any form of non-response (e.g. valid skip, not stated) or don't know/refusal cannot be coded as a missing. The "Sysmiss" label in the Statistics section indicates the number of non-responding records for each variable, and the "Valid" values in the Statistics section indicate the number of responding records for each variable. The total number of records for each variable is comprised of both the sysmiss and valid values. LFS revisions: LFS estimates were previously based on the 2001 Census population estimates. These data have been adjusted to reflect 2006 Census population estimates and were revised back to 1996. The census metropolitan area (CMA) variable has been expanded from the three largest CMAs in Canada to nine. Two occupation variables based on the 2016 National Occupation Classicifcation have been reintroduced: a generic 10- category variable (NOC_10) and a detailed 40-category variable (NOC_40). A new variable on immigrant status (IMMIG) has been introduced, which distingushes between recent immigrants and established immigrants. Fourteen variables related to family and spouse/partner's
description: Migration from Nesstar
description: Labour Force Survey
description: Notes: 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-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.;