Database descriptions, statistical standards (resolutions and guidelines), and guides and manuals – all the metadata to better understand the labour statistics presented on ILOSTAT.
Labour force survey (LFS) resources
The global reference for labour force survey design
National labour force surveys are the main source behind essential headline indicators of the labour market and the world of work. A wide range of economic and social policies, from monetary and fiscal policies to employment, decent work, vocational education and training, and a wide range of poverty reduction and social inclusion policies depend on labour force surveys as their main source of statistics for informed decision-making and monitoring.
To support countries in developing their national LFS, the ILO Department of Statistics maintains a set of model LFS resources to support PAPI and CAPI data collection. The ILO model LFS resources consolidate existing good survey practice and new approaches following evidence from ILO’s LFS testing programme to support the collection of work and labour market data, aligned with the latest international standards.
The ILO model LFS resources provided here include:
- Modular questionnaires
- Accompanying national adaptation guides
- Variable derivation flow-charts and syntax
- LFS integration guide (for special add-on modules)
- Build your own LFS tool (beta version) for CAPI users
Table of contents
Topics covered include:
- Basic demographics, education, international migration status, disability status to support essential disaggregations needed to monitor Decent Work, SDGs and other national and global goals.
- Labour force status, labour underutilization including time-related underemployment, unemployment, long-term unemployment, discouragement, potential labour force, previous employment experience;
- Special add-on modules covering emerging work-related topics for use on a less frequent basis, including volunteer work, skills mismatches, barriers to the labour market entry of persons with disabilities, return migrant works, and others.
- Current employment, including multiple job holding, occupation, industry, institutional sector, status in employment, informal sector employment and informal employment, contract characteristics, job-related social protection; identification of policy priority groups such as domestic workers, home-based workers, dependent contractors and others.
- Own-use production of goods in agriculture, fishing, fetching water, collecting firewood, manufacture of other household items, and own-dwelling construction or renovation, as per national relevance.
New add-on modules
Paper and pencil interviewing (PAPI) remains an important method of LFS data collection in many countries and regions around the world. Updating LFS questionnaires implemented through PAPI to incorporate the latest international standards in labour statistics can be an important challenge. The ILO model LFS for PAPI is designed using a modular approach to facilitate selection of topics relevant to the national context and simplified skip instructions to enable interviewers to manage a good quality interview flow using paper questionnaires.
PAPI LFS documentation
ILO model LFS PAPI questionnaire READ ME
Household modules (v5 Sep 2020)
Core LFS modules for persons of working age (choose one)
- Job-type start (v4 Jul 2020)
For countries with low prevalence of small-scale own-account farming or fishing
- Agriculture work start (v1 Jul 2020)
For countries with high prevalence of small-scale own-account farming or fishing
- Main activity start (v1 Jul 2020)
For countries wishing to capture main activity as self-declared in addition to labour force status
Add-on modules on special work topics
- Occupational qualifications and skills mismatches (v1 Sep 2020)
Self-perceived mismatches by level of education, field of study and type of skills among employed persons
- Volunteer Work (v1 Jul 2020)
Participation and time spent in volunteer work, including organization-based and direct volunteering, and essential characteristics of the volunteer work activities
- Functional difficulties and barriers to employment (v1 Jul 2020)
Different barriers to the labour market integration of persons with disabilities
- Occupational Injuries (v1 Aug 2022)
Occupational accidents, occupational injuries, work-related health problems, and exposure to risk factors at workplace
Computer Assisted Interview methods are being increasingly used in survey implementation. Questionnaires implemented in this way can utilise in-built features to improve the flow of the questionnaire for the interviewer and respondent versus pen and paper questionnaires. This not only lowers respondent burden, but it also increases the ability to create more varied and wide-ranging questionnaires which is more difficult to manage through PAPI. Furthermore the ability to capture data electronically creates both data quality and efficiency gains given the possibility to implement improved real-time validations and the removal of the need for manual data entry. As such, CAPI and other computer assisted interviewing methods offer a wide range of benefits both for data quality but also in efficiency, flexibility and adaptability of surveys.
Build your own LFS - Programme builder (beta)
The programme builder is not available on a mobile. Please use a larger device to use this tool.
The easy-to-use “Build your own LFS” tool generates a CAPI application for CSPro which can be deployed for use on android devices. This beta version is being launched to support testing and as an illustration of the added functionality and user customization coming soon!
Future updates will include more advanced tools to support national adaptation of the model LFS questions, new modules covering related topics, additional administrative modules to handle sample management, interviewer workload assignment, field supervision, French and Spanish language versions, among many others.
CAPI LFS documentation
ILO model LFS PAPI questionnaire READ ME
Household modules (v3 June 2019)
- Roster and essential background characteristics
Household roster, demographics, education, international migration status, disability status
Labour modules (v3 June 2019)
- Full set of modules for persons of working age
Current employment, main and second job characteristics, job search and availability, own-use production of goods
COVID-19 data collection guidance
The COVID-19 pandemic created many of practical and conceptual challenges, as well as a major demand for enhanced data to describe the impact on labour markets and the world of work. The ILO has produced a range of information and guides to describe the impacts COVID-19 has had on data collection, and support countries to continue to produce relevant data.
Global review of impacts of the COVID-19 pandemic on labour force surveys and dissemination of labour market statistics
In March 2021, the ILO undertook a global survey of national data producers to understand the impacts of the pandemic on their statistical operations particularly in the domain of labour statistics.
This brief highlights 5 key areas where strong and decisive action is required to achieve sustainable improvement in the availability of key gender data, including in the world of work.
Working from a distance and working at home are not new phenomena but the relevance of their measurement has increased, not least due to the Covid-19 pandemic. This notes provide guidance to data producers on how the four different concepts of remote work, telework, work at home and home-based work should be statistically understood, how they relate to each other, and how they can be measured through a household survey.
Lack of data on how households and workers are being impacted by the pandemic can severely affect the formulation of programmes and policies aimed to help those most in need. In times of crisis, rapid surveys may be an alternative source of information where official household surveys such as LFS have been halted or postponed. This note provides modules for rapid surveys to shed light on the COVID-19 impacts on paid and unpaid work.
The restrictions necessary to combat COVID-19 pose a huge obstacle to data collection operations, precisely when there is a massive increase in demand for information. The ILO reached out to national data producers to understand the impacts of the pandemic on their statistical operations particularly in the domain of labour statistics. Last update: May 2020
The most immediate impact of the pandemic on LFS data collection for most countries is the suspension of face-to-face interviewing. This note provides guidance to countries on the range of options available and challenges to deal with in order to change their data collection approach and maintain continuity in data availability.
The COVID-19 crisis is affecting data collection activities of national statistical offices (NSOs) around the world, including for consumer price indexes (CPI).
International standards are still sound reference, but due to this unprecedented pandemic, this note provides guidance to data producers to maintain labour force survey (LFS) operations. It highlights the range of topics to prioritize in national LFS and suggested clarifications to support consistent treatment of special cases becoming more prevalent, such as job absences of uncertain duration, business closures, and overall reduced job search activity.
Learn more about the international standards on labour statistics (a. conventions and recommendations and b. resolutions and guidelines).
Learn more about the ILO’s programme of methodological research to identify and promote good practices in the collection and reporting of labour statistics.
The ILO seeks partners to improve the production and dissemination of labour statistics for better evidence-based policy. See our current partnerships.
An introduction to the conceptual frameworks for forms of work and labour force statistics, including labour underutilization.
The ICLS meets every 5 years to establish international standards on labour statistics. The latest (21st) ICLS was held in October 2023.
We provide training and support with the implementation of international statistical standards, data production, analysis and dissemination.