The ILOSTAT database Disability Labour Market Indicators (DLMI) is a set of indicators describing the gaps in the labour market outcomes between persons with and without disabilities. It covers the labour force, employment, unemployment, working time and earnings.
Concepts and definitions
The labour force concepts and definitions, such as employment and unemployment, follow those described in the Labour Force Statistics (LFS) database.
The classification by disability status differentiates between persons with and without disability. The term “Disability”, as defined in the International Classification of Functioning, Disability and Health (ICF) (World Health Organization, Geneva, 2001), is used as an umbrella term, covering impairments, activity limitations, and participation restrictions. Impairments are problems in body function or structure such as a significant deviation or loss. Activity limitations are difficulties an individual may have in executing activities. Participation restrictions are problems an individual may experience in involvement in life situations. For measurement purposes, a person with disability is defined as a person who is limited in the kind or amount of activities that he or she can do because of ongoing difficulties due to a long-term physical condition, mental condition or health problem. The following list of broad categories of disabilities, may be used:
- seeing difficulties (even if wearing glasses)
- hearing difficulties (even if using hearing aid)
- speaking difficulties (e.g., talking)
- moving/mobility difficulties (e.g., walking, climbing stairs, standing)
- body movement difficulties (e.g., reaching, crouching, kneeling)
- gripping/holding difficulties (e.g., using fingers to grip or handle objects)
- learning difficulties (e.g., intellectual difficulties, retardation)
- behavioural difficulties (e.g., psychological, emotional problems)
- personal care difficulties (e.g., bathing, dressing, feeding)
- other difficulties
The main data source for labour force statistics, including those disaggregated by disability status, is a labour force survey or other household-based survey. These types of surveys can be designed to cover virtually the entire non-institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labour force in a coherent framework.
Population censuses are another major source of data on the labour force and its components. Other sources are establishment surveys and administrative registers.
In cases where ILO experts process the household survey microdata in order to produce the indicators published on ILOSTAT, international statistical standards are strictly applied to ensure comparability across countries. Thus, ILOSTAT data may differ from what is nationally reported. The magnitude of the differences depends on the extent to which a country is applying international statistical standards.
Interpretation and uses
The main objective of the indicators is to capture different aspects related to the labour market integration of persons with disabilities, and the disaggregation of the key labour market indicators by disability status allow identification of the gaps in the work experience between people with and without disabilities.
However, comparing labour market characteristics of people with and without disabilities is not sufficient, as it does not provide the information necessary for uncovering the barriers and facilitators that drive those outcomes. This information is needed for the proper development of policies to rectify outcome gaps. Therefore, ILO in collaboration with the Washington Group on Disability statistics has developed a LFS module that collects additional information regarding barriers people with disabilities face in the labour market. The module, together with its implementation and variable derivation guides, is available on the LFS resources page.
The compilation of additional information on a sub-group of the population, such as persons with disabilities, has implications for the determination of the sample size of a household survey. In this case, the sample must be large enough to produce information that has sufficient precision and that suits the needs of the analysis envisaged. One major determinant for this is the degree of substantive detail for the labour force overall (age, sex, status in employment, industry or occupational classification, and so forth) and for the disabled labour force (for example, type and severity of disability). Moreover, the sample size required may need to be substantially larger in a situation where changes in a small category such as people with disabilities is to be monitored.
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This Guidebook provides a detailed overview of the labour market indicators included in the Sustainable Development Goals Global Indicator Framework. It is intended to serve as a manual of best practices for calculating and interpreting the SDG labour market indicators, with a view to monitoring progress made at the national and international levels towards the achievement of the SDGs.
This volume presents the sources and methods used in the compilation of national statistics on labour force characteristics of persons with disabilities.
This guide highlights basic knowledge from the fields of labour and disability statistics which has to be combined for a comprehensive description of the employment situation of people with disabilities. It will be of great relevance to worldwide countries as they work to promote and monitor equal employment opportunities for disabled persons. It provides information on current standards and definitions in the fields of employment and disability, as well as descriptions of good practices related to the compilation of statistics on the employment situation of people with disabilities, so that better data on this topic can be produced.