The Employment Dynamics is a compilation of statistical tables on employment, payroll and the number of businesses with employees for Canada, the provinces and territories. They are published annually by Statistics Canada’s Small Business and Special Surveys Division, which derives the Dynamics figures from information supplied by the Business and Labour Market Analysis Division. Primarily, the tables are used to analyze how businesses of different sizes contribute to employment change in the economy. Net year-over-year changes in total employment are broken down according to the following gross components, which are calculated for individual employment-size groupings of firms: Job gains attributed to newly identified employers; Job losses attributed to firms that ceased to be identified as employers; Job gains attributed to continuing employers that increased their respective employment levels; Job losses attributed to continuing employers that decreased their respective employment levels; The Dynamics are also useful in that they provide estimated counts of entries and exits of businesses from the employer population in Canada. The data cover all private and public sector businesses or organizations (including public administration) that issue T4 slips to employees for taxation purposes. Both incorporated and unincorporated entities are included, but only if they issue T4 slips to employees. In other words, non-employers are not included in the figures.

Econometric analysis on R of Italian and Sweden labour market dynamics, 2001-2021

Labour market dynamics and employment in Italy and Sweden 2001-2021

The Survey of Labour and Income Dynamics (SLID) is a Statistics Canada survey intended for use in research on changes over time in Canadians labour force activity status and economic well-being. Two major characteristics of the survey design result directly from this objective. First, SLID is a longitudinal survey; each panel participates in the survey for six years. Second, SLID focuses on whole households, and the range of subjects that it covers is broad enough to allow for the collection of data on family situations and major demographic events. This aspect of the survey enables researchers to examine the links between demographic events, labour force activity patterns and income. The longitudinal job file focuses on wages, work schedules, length of employment etc. The Survey of Labour and Income Dynamics (SLID) is a longitudinal household survey conducted by Statistics Canada. It is designed to capture changes in the economic well-being of individuals and families over time and the determinants of their well-being. Individuals originally selected for the survey are interviewed once or twice per year for six years to collect information about their labour market experiences, income and family circumstances. In order to obtain complete information on families and to obtain cross-sectional data, people who live with the original respondents at any time during the six years are also interviewed during the time of cohabitation.

Abstract

Published by the US Census Department, the LODES dataset aggregates data about where people live and work in the United States. This data is for New York State.

Documentation

The Longitudinal Employer-Household Dynamics (LEHD) program is part of the Center for Economic Studies at the U.S. Census Bureau. The LEHD program produces new, cost effective, public-use information combining federal, state and Census Bureau data on employers and employees under the Local Employment Dynamics (LED) Partnership. State and local authorities increasingly need detailed local information about their economies to make informed decisions. The LED Partnership works to fill critical data gaps and provide indicators needed by state and local authorities.

LEHD Origin-Destination Employment Statistics (LODES) used by OnTheMap are available for download below. Version 7 of LODES was enumerated by 2010 census blocks. Previous versions of LODES were enumerated with 2000 census blocks.

Data are state-based and organized into three types: Origin-Destination (OD), Residence Area Characteristics (RAC), and Workplace Area Characteristics (WAC), all at census block geographic detail. Data is available for most states for the years 2002–2018.

The cross-sectional public-use microdata file for the Survey of Labour and Income Dynamics (SLID) is a collection of income, labour and family variables on persons in Canada and their families. SLID is an annual household survey covering the population of the 10 Canadian provinces with the exception of Indian reserves, residents of institutions and military barracks. The Survey of Labour and Income Dynamics began collecting data for reference year 1993. Initially, SLID was designed to be, first and foremost, a longitudinal survey, with primary focus on labour and income and the relationships between them and family composition. Then, the decision was made to extend the objectives of SLID to be the primary source of cross-sectional household income data. For many years, the Survey of Consumer Finances had provided public-use microdata files (PUMFs) to meet the needs of cross-sectional household income data users. SCF PUMFs were released up to and including reference year 1997. For the purpose of standard publications, Statistics Canada has made the transition from SCF to SLID between 1995 and 1996. Therefore, SLID cross-sectional PUMFs are being made available beginning with reference year 1996. The SLID files have been designed to be analogous to those produced for the SCF. The type of income data collected by SLID was identical to that of the former household income survey SCF (Survey of Consumer Finances), with the distinction that SLID respondents had the choice of a traditional income interview or granting permission to Statistics Canada to use their T1 income tax data.

The Survey of Labour and Income Dynamics (SLID) is a Statistics Canada survey intended for use in research on changes over time in Canadians labour force activity status and economic well-being. Two major characteristics of the survey design result directly from this objective. First, SLID is a longitudinal survey; each panel participates in the survey for six years. Second, SLID focuses on whole households, and the range of subjects that it covers is broad enough to allow for the collection of data on family situations and major demographic events. This aspect of the survey enables researchers to examine the links between demographic events, labour force activity patterns and income. Includes all persons living in the ten provinces of Canada, excluding residents of institutions, Indian reserves and military barracks.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (StatsSA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa. Since 2008, StatsSA have produced an annual dataset based on the QLFS data, "Labour Market Dynamics in South Africa". The dataset is constructed using data from all all four QLFS datasets in the year. The dataset also includes a number of variables (including income) that are not available in any of the QLFS datasets from 2010.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population except for those in workers' hostels. However, persons living in private dwelling units within institutions are enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

Each year the LMDSA is created by combining the QLFS waves for that year and then including some additional variables. The QLFS master frame for this LMDSA was based on the 2011 population census by Stas SA. The sampling is stratified by province, district, and geographic type (urban, traditional, farm). There are 3324 PSUs drawn each year, using probability proportional to size (PPS) sampling. In the second stage Dwelling Units (DUs) are systematically selected from PSUs. The 3324 PSU are split into four groups for the year, and at each quarter the DUs from the given group are replaced by substitute DUs from the same PSU or the next PSU on the list (in the same group). It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, two quarters and a new household moves in, the new household will be enumerated for two more quarters until the DU is rotated out. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaire consists of the following sections: - Particulars of each person in the household - Economic activities in the last week for persons aged 15 years - Unemployment and economic inactivity for persons aged 15 years - Main work activity in the last week for persons aged 15 years - Earnings in the main job for employees, employers and own-account workers aged 15 years - Migration for all persons aged 15 years

Data appraisal

The statistical release notes that missing values were "generally imputed" for item non-response but provides no detail on how Statistics SA did so.

Labour market dynamics in Italy and Sweden, 2009 - 2024 and linear projections to 2050.

Labour Market dynamics in Italy and Sweden, 2009-2024

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The QLFS uses a master sampling frame that is used by several household surveys conducted by Statistics South Africa. This wave of the QLFS is based on the 2013 master frame, which was created based on the 2011 census. There are 3324 PSUs in the master frame and roughly 33000 dwelling units.

The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. For more information see the statistical release.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaire consists of the following sections: - Biographical information (marital status, education, etc.) - Economic activities in the last week for persons aged 15 years and older - Unemployment and economic inactivity for persons aged 15 years and above - Main work activity in the last week for persons aged 15 years and above - Earnings in the main job for employees, employers and own-account workers aged 15 years and above

From 2010 the income data collected by South Africa's Quarterly Labour Force Survey is no longer provided in the QLFS dataset (except for a brief return in QLFS 2010 Q3 which may be an error). Possibly because the data is unreliable at the level of the quarter, Statistics South Africa now provides the income data from the QLFS in an annualised dataset called Labour Market Dynamics in South Africa (LMDSA). The datasets for LMDSA are available from DataFirst's website.

The Egypt Labor Market Panel Survey, carried out by the Economic Research Forum (ERF) in cooperation with Egypt’s Central Agency for Public Mobilization and Statistics (CAPMAS). Over its twenty-year history, the ELMPS has become the mainstay of labor market and human development research in Egypt, being the first and most comprehensive source of publicly available micro data on the subject. The 2018 wave of the Egypt Labor Market Panel Survey (ELMPS) is the fourth wave of a longitudinal survey carried out by the Economic Research Forum (ERF) in cooperation with the Egyptian Central Agency for Public Mobilization and Statistics (CAPMAS). The 2018 wave follows previous waves in 1998, 2006 and 2012. Over its twenty-year history, the ELMPS has become the mainstay of labor market and human development research in Egypt, being the first and most comprehensive source of publicly available micro data on the subject. The ELMPS is a wide-ranging, nationally representative panel survey that covers topics such as parental background, education, housing, access to services, residential mobility, migration and remittances, time use, marriage patterns and costs, fertility, women’s decision making and empowerment, job dynamics, savings and borrowing behavior, the operation of household enterprises and farms, besides the usual focus on employment, unemployment and earnings in typical labor force surveys. ELMPS 2018 also provided more detailed information on health, gender role attitudes, food security, hazardous work, community infrastructure and the cost of housing. It incorporated specific questions on vulnerability, coping strategies and access to social safety net programs. (Krafft, C, Assaad, R., and Rahman, K .,2019) In addition to the survey’s panel design, which permits the study of various phenomena over time, the survey also contains a large number of retrospective questions about the timing of major life events such as education, residential mobility, jobs, marriage and fertility. The survey provides detailed information about place of birth and subsequent residence, as well information about schools and colleges attended at various stages of an individual’s trajectory, which permit the individual records to be linked to information from other data sources about the geographic context in which the individual lived and the educational institutions s/he attended. The data may be accessed through the ERF Data Portal: http://www.erfdataportal.com/index.php/catalog/157

At the heart of the survey's objectives is the understanding of the economic well-being of Canadians: what economic shifts do individuals and families live through, and how does it vary with changes in their paid work, family make-up, receipt of government transfers or other factors? The survey's longitudinal dimension makes it possible to see such concurrent and often related events.

Below you will find the diagnosis of job skills carried out in different basins of the Burgundy-Franche-Comté region. Each diagnosis proposes: — an AFOM summary — a structural portrait — employment dynamics and sectors of activity — key sectors — interim — commuting to work — jobs sought, labour needs, difficulties — jobseekers — level of qualification — impact of the crisis on employment: — job application — use of partial activity — on companies (including examples) — on sectors and sectors — mechanisms put in place — stakes for the basin — strategic recommendations and action plan You can find other publications on Decidata

What is the causal impact of local employment dynamics on electoral behaviour? We combine Italian labour market area-level data for four national elections (2008, 2013, 2018 and 2022) with a shift-share IV estimation design to identify how local labour market conditions, captured by changes in the employment rate, affect voter participation and incumbent support. Our baseline estimates show that a 1 p.p. drop in the employment rate yields a significant 0.76 p.p. increase in turnout and a 0.80 p.p. decline in incumbent vote share. Further analyses reveal crucial nuances. First, exploring mediation, we find that higher turnout in response to worsening labour market conditions accounts for roughly one-quarter of the total negative impact on incumbent support via a participation channel. Second, the effects appear driven entirely by adverse conditions: we find strong electoral reactions in areas actually experiencing employment declines, but no significant response where conditions improve, consistent with a protest voting framework. Third, while regional-national partisan alignment slightly moderates effect magnitudes, national accountability for economic performance largely dominates the local electoral reaction.

The Household, Income and Labour Dynamics in Australia (HILDA) Survey is a nationally representative longitudinal study of Australian households which commenced in 2001. Funded by the Australian Government Department of Social Services (DSS), the HILDA Survey is managed by the Melbourne Institute of Applied Economic and Social Research at the University of Melbourne. The HILDA Survey provides longitudinal data on the lives of Australian residents. Its primary objective is to support research questions falling within three broad and inter-related areas of income, labour market and family dynamics. The HILDA Survey is a household-based panel study of Australian households and, as such, it interviews all household members (15 years and over) of the selected households and then re-interviews the same people in subsequent years. This dataset is the 22nd release of the HILDA data, incorporating data collected from 2001 through 2022 (Waves 1-22). The special topic module in Wave 22 is wealth, and includes questions on employment-related discrimination, updates to citizenship and permanent residency and material deprivation

The ELMPS is a nationally representative panel survey, collected by the Economic Research Forum and CAPMAS in Egypt, that covers topics such as parental background, education, housing, access to services, residential mobility, time use, marriage patterns and costs, fertility, women’s decision making and empowerment, job dynamics, savings and borrowing behavior, the operation of household enterprises and farms, besides the usual focus on employment, unemployment and earnings in typical labor force surveys. A particular module focuses on return migration and remittances. In addition to the survey’s panel design, which permits the study of various phenomena over time, the survey also contains a large number of retrospective questions about the timing of major life events such as education, residential mobility, jobs, marriage and fertility. The survey provides detailed information about place of birth and subsequent residence, as well information about schools and colleges attended at various stages of an individual’s trajectory, which permit the individual records to be linked to information from other data sources about the geographic context in which the individual lived and the educational institutions s/he attended PLEASE NOTE: To access the complete data collection please click on the related resource entitled "Economic Research Forum: Data portal" Contacts(S) erfdataportal@erf.org.eg, www.erf.org.eg Confidentiality To access the micro data, researchers are required to register on the ERF website and comply with the data access agreement. The data will be used only for scholarly, research, or educational purposes. Users are prohibited from using data acquired from the Economic Research Forum in the pursuit of any commercial or private ventures. The Egypt Labour Market Panel Survey 2012 (ELMPS 12) is a follow-up survey to the Egypt Labour Market Surveys of 2006 & 1998 (ELMPS06 & ELMS 98), which were carried out by the Economic Research Forum in cooperation with the Egyptian Central Agency for Public Mobilization and Statistics (CAPMAS). The ELMPS 12 is the third round of a periodic longitudinal survey that tracks the labour market characteristics of the households and the individuals interviewed in 1998 and 2006, any new households that might have split from them, as well as a refresher sample to ensure that the data continue to be nationally-representative. Our project funded by the ESRC-DFID allowed the addition of a refresher sample of 2,000 households to the ELMPS 12, to over-sample high migration areas to allow more detailed measures of migration trends, determinants, consequences and return migration in Egypt. In addition, we were able to include a new revised extended module on return migration and additional questions on current migrants. The data on current and return migration where driven by our objective to enlarge the evidence base of the triple-win policy vision of temporary migration, by focusing on the return migrants and considering the extent to which, and the leading dimensions along which, the returnee can impact positively on the source country, and in turn how the sending country can maximise its benefits from temporary migration by supporting the returnee. This dynamic relationship in turn informs the incentives of migrants to stay temporarily rather than permanently in the host country, and to become directly a driver or contributor to economic development in the source country. Hence, resulting in a win-win-win situation for migrants, sending countries and receiving countries. The 2012 data collection process was made by CAPMAS and proceeded in two phases. First, in late 2011, an enumeration phase was undertaken. This phase focused on locating households and individuals from the 2006 sample. If households or individuals had moved, every effort was made to collect current contact information. Additionally, the refresher sample (funded by the ESRC-DFID) was designed to over-sample high-migration areas, and refresher sample PSUs and households were randomly selected based on this sampling approach to enable a study of return migration in Egypt.

The Survey of Program Dynamics (SPD) provides estimates of the economic status and activities of the population of the United States. SPD provides monthly labor force data and, in addition, supplies supplemental data on work experience, income, and noncash benefits. Comprehensive work experience information is given on the employment status, occupation, and industry of persons 15 years old and older, as well as weeks worked and hours per week worked, reasons for not working full-time, total income, and income components. Information is available not only for persons currently in the labor force but also for those who are outside the labor force. Variables cover unemployed respondents' current desire for work, their past work experience, and their intentions for job-seeking. SPD also provides data covering nine noncash income sources: food stamps, school lunch programs, employer-provided group health insurance plans, employer-provided pension plans, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Basic demographic, social, and economic characteristics are supplied for each member of the household surveyed, including age, sex, race, ethnic origin, marital status, household relationship, education, and veteran status. Limited data are provided on housing unit characteristics, such as number of units in structure and tenure. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR02917.v2. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Social assistance is a means-tested benefit that is supposed to be a short-term, temporary economic support. Understanding why some individuals are in repeated or continuous need of social assistance is thus of obvious policy relevance, but the dynamics of social assistance receipt remain poorly understood. In 2005, a survey among long-term recipients of social assistance in Norway collected data on (a) childhood disadvantages, (b) health status, (c) health behaviors, (d) psychological resources, and (e) social ties, in addition to basic sociodemographic information. This rich survey data has been linked with tax register data from 2005–2013, enabling us to explore the detailed characteristics of long-term social assistance recipients who are unable to reach financial self-sufficiency. Results from linear probability models show that surprisingly few of the 28 explanatory variables are statistically associated with social assistance dynamics, with two important exceptions: People with drug problems and immigrants both have a much higher probability of social assistance receipt. Yet overall, it is challenging to ‘predict’ social assistance dynamics, indicating that randomness most likely plays a non-negligible role. The 28 explanatory variables do a far better job in predicting both labor market success (employment), labor market preparation (work assessment allowance), and labor market withdrawal (disability benefit utilization). Thus, there seems to be something distinctive about the processes leading to continued social assistance recipiency, where randomness could be a more influential force.

Labor Dispatch Service Market Outlook

The global labor dispatch service market was valued at approximately USD 45 billion in 2023 and is projected to reach around USD 78 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5%. This market size expansion is primarily driven by the increasing demand for flexible workforce solutions and the rising trend of outsourcing non-core activities to specialized service providers. With companies across various industries seeking to optimize operational costs and enhance productivity, the labor dispatch service market is poised for significant growth over the forecast period.

One of the primary growth factors for the labor dispatch service market is the evolving nature of work and employment structures. As businesses face fluctuating market demands and economic uncertainties, there is a growing preference for flexible staffing solutions. Labor dispatch services offer an adaptable workforce that can be scaled up or down based on business needs, providing companies with the agility required to navigate dynamic market conditions. This shift towards more flexible employment arrangements is anticipated to continue, driving demand for labor dispatch services in the coming years.

Technological advancements also play a critical role in the expansion of the labor dispatch service market. The integration of advanced technologies such as artificial intelligence, machine learning, and big data analytics into staffing processes has revolutionized the way labor dispatch services are managed and delivered. These technologies enable more efficient matching of workers with job requirements, streamline administrative tasks, and enhance the overall effectiveness of staffing solutions. As technology continues to evolve, it is expected to further boost the growth of the labor dispatch service market by improving service quality and operational efficiency.

Another significant factor contributing to the market's growth is the increasing globalization of business operations. Companies are expanding their footprints across multiple regions, leading to a greater need for diverse and geographically dispersed workforces. Labor dispatch services facilitate this by providing access to a broader talent pool and offering localized staffing solutions that meet regional labor regulations and cultural nuances. This global expansion of businesses is likely to sustain the demand for labor dispatch services, particularly in emerging markets where economic development is creating new job opportunities.

The regional outlook for the labor dispatch service market indicates robust growth across various geographies. North America and Europe are expected to lead the market due to their well-established industrial bases and high adoption of flexible staffing solutions. The Asia Pacific region is projected to exhibit the highest growth rate, driven by rapid industrialization, economic development, and a large labor force. Latin America and the Middle East & Africa are also anticipated to experience steady growth, supported by ongoing infrastructure projects and increasing foreign investments. Each region's unique economic conditions and labor market dynamics will shape the specific growth trajectories within the global labor dispatch service market.

Service Type Analysis

The labor dispatch service market is segmented by service type into temporary staffing, long-term contract staffing, project-based staffing, and others. Temporary staffing is one of the most prominent segments, driven by the need for short-term workforce solutions to address seasonal demands, peak workloads, and special projects. Temporary staffing provides businesses with the flexibility to manage their workforce dynamically, responding quickly to changing market conditions without the long-term commitments associated with permanent hires. This segment is expected to maintain strong growth due to its inherent advantages in terms of cost-effectiveness and operational flexibility.

Long-term contract staffing, another critical segment, involves the placement of workers for extended periods, often spanning several months to years, based on specific contract durations. This segment caters to industries where there is a need for sustained workforce support, such as manufacturing, healthcare, and IT. The stability and continuity offered by long-term contract staffing make it an attractive option for businesses seeking to maintain