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Comparison of labor estimates: modeled vs. national data

ILO
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Comparison of labor estimates: modeled vs. national data

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What you should know about this indicator

  • The unemployment rate measures the share of the that is without a job but actively looking for work and available to start soon. It is one of the most widely used indicators of labor market conditions across countries and over time.
  • This data follows the standards of the . Under this framework, employment includes work for pay or profit, including self-employment, as well as the production of goods for own use (such as subsistence farming). Changes in the definition of employment also affect who is counted as unemployed or outside the labor force. Because definitions were updated under the , data using the newer definitions is not fully comparable with data based on the 13th ICLS. You can read more about the definitions in this explainer by the ILO.

How is this data described by its producer - ILO?

Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.

Aggregation method:

Weighted average

Statistical concept and methodology:

Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed.

Household labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.

Statistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.

Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). The working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).

Development relevance:

The unemployment rate is a useful measure of the underutilization of the labor supply. It reflects the inability of an economy to generate employment for those persons who want to work but are not doing so, even though they are available for employment and actively seeking work. It is thus seen as an indicator of the efficiency and effectiveness of an economy to absorb its labor force and of the performance of the labor market.

Given its usefulness in conveying valuable information on a country’s labor market situation and the fact that it is widely recognized as a headline labor market indicator, it was included as one of the indicators to measure progress towards the achievement of the Sustainable Development Goals (SDG), under Goal 8 (Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all).

Limitations and exceptions:

The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.

There may be also persons not currently in the labour market who want to work but do not actively "seek" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the "hidden unemployed" or "discouraged workers") is a criterion that will affect the unemployment count of both women and men.

However, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.

Other notes:

The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Unemployment rates: modeled vs. national estimates
ILO
Share of the without work, but actively looking for a job and available to start soon.
Source
Labour Force Statistics, via World Bank (2026)processed by Our World in Data
Last updated
February 27, 2026
Next expected update
February 2027
Date range
1960–2025
Unit
%

Sources and processing

Labour Force Statistics, via World Bank – World Development Indicators

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
February 27, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Labour Force Statistics database (LFS), International Labour Organization (ILO), uri: https://ilostat.ilo.org/data/bulk/, publisher: ILOSTAT, type: external database, date accessed: January 17, 2026. Indicator SL.UEM.TOTL.NE.ZS (https://data.worldbank.org/indicator/SL.UEM.TOTL.NE.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
February 27, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Labour Force Statistics database (LFS), International Labour Organization (ILO), uri: https://ilostat.ilo.org/data/bulk/, publisher: ILOSTAT, type: external database, date accessed: January 17, 2026. Indicator SL.UEM.TOTL.NE.ZS (https://data.worldbank.org/indicator/SL.UEM.TOTL.NE.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

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How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Unemployment rates: modeled vs. national estimates”, part of the following publication: Bertha Rohenkohl, Pablo Arriagada, and Esteban Ortiz-Ospina (2026) - “Work and Employment”. Data adapted from Labour Force Statistics, via World Bank. Retrieved from https://archive.ourworldindata.org/20260512-185716/grapher/ilo-national-vs-modeled-data.html [online resource] (archived on May 12, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Labour Force Statistics, via World Bank (2026) – processed by Our World in Data

Full citation

Labour Force Statistics, via World Bank (2026) – processed by Our World in Data. “Unemployment rates: modeled vs. national estimates – ILO” [dataset]. Labour Force Statistics, via World Bank, “World Development Indicators 125” [original data]. Retrieved May 16, 2026 from https://archive.ourworldindata.org/20260512-185716/grapher/ilo-national-vs-modeled-data.html (archived on May 12, 2026).

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=IMPORTDATA("https://ourworldindata.org/grapher/ilo-national-vs-modeled-data.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/ilo-national-vs-modeled-data.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

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metadata = requests.get("https://ourworldindata.org/grapher/ilo-national-vs-modeled-data.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/ilo-national-vs-modeled-data.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/ilo-national-vs-modeled-data.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/ilo-national-vs-modeled-data.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear