five

Labour Force Survey, March 2022 [Canada]

收藏
DataONE2023-10-23 更新2024-06-08 收录
下载链接:
https://search.dataone.org/view/sha256:a8d6f6e0f6f38f29c88494fc0f2ce76bd953759cc0128bc8d32b7f482f7fd97e
下载链接
链接失效反馈
官方服务:
资源简介:
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

劳动力调查(Labour Force Survey,LFS)所提供的就业与失业估计数据,是衡量加拿大经济表现最及时且最重要的指标之一。该调查于数据采集完成后仅10天便发布结果,是加拿大首个公布的主要月度经济数据序列。 加拿大劳动力调查诞生于第二次世界大战后,旨在满足当时对劳动力市场可靠及时数据的迫切需求:彼时从战争经济向和平时期经济转型引发了大规模劳动力市场变革,相关数据的需求极为紧迫。 LFS的核心目标是将劳动年龄人口划分为就业、失业与非劳动力三大互斥分类,并为每一类提供描述性与解释性数据。 LFS数据可用于计算广为人知的失业率,以及就业率、劳动参与率等其他标准劳动力市场指标。此外,LFS还可按行业、职业、公私部门、工作时长等维度生成就业估计数据,且可结合多种人口统计特征进行交叉分类。统计范围覆盖加拿大全国、各省、各地区以及大量省以下区域。针对雇员群体,调查还会生成工资水平、工会身份、工作稳定性以及工作场所规模等数据。 上述数据被加拿大各级政府用于就业项目的评估与规划。加拿大就业与社会发展部会利用区域失业率,来确定特定就业保险区域内居民的保险福利资格、福利水平与给付时长。劳动力市场分析师、经济学家、咨询顾问、规划人员、预测人员以及学术界人士,无论来自私营还是公共部门,也都会使用该数据集。 备注:由于本数据集已剔除缺失值,任何形式的无应答(如有效跳答、未说明情况)或不知道/拒绝回答均不得被编码为缺失值。统计模块中的"Sysmiss"标签代表各变量的无应答记录数,而"Valid"值则代表各变量的有效应答记录数;各变量的总记录数由系统缺失值与有效应答值两部分构成。 LFS修订说明:此前LFS估计数据基于2001年人口普查的人口估计数,现已调整为2006年人口普查的人口估计数,并回溯修订至1996年。普查都会区(Census Metropolitan Area,CMA)变量已从加拿大三大最大普查都会区扩展至九大。两项基于2016年国家职业分类(National Occupation Classicifcation)的职业变量已重新引入:分别为涵盖10类的通用职业变量(NOC_10)与涵盖40类的细分职业变量(NOC_40)。一项全新的移民身份(IMMIG)变量已上线,可区分新近移民与定居移民。另有14项与家庭及配偶/伴侣相关的变量
创建时间:
2023-12-28
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作