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Unemployment rate

Share of the without work, but actively looking for a job and available to start soon.

Data source

ILO

Unit
%
Last updated
2026-02-27
Next expected update
2027-02-27
Managed by
Mojmír Vinkler and Pablo Arriagada

  • 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.

  • When defining the labor force, the definition of “working age” varies across countries, depending on national laws and practices. In the ILO modeled estimates shown here, this is harmonized to refer to people aged 15 and older.

  • This data comes from the ILO Modelled Estimates series. combines countries' own reported estimates with statistically modeled estimates when observations are missing. This improves comparability across countries and over time and allows the ILO to calculate regional and global aggregates for every year. You can read more about how the ILO produces these estimates in the Modelled Estimates documentation.

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  • 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.

Data sources

ILO Modelled Estimates, 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
Retrieved from
https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
ILO Modelled Estimates database (ILOEST), 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.ZS (https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

Citations

How should I cite this data in a news article?

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

ILO Modelled Estimates, via World Bank (2026) – processed by Our World in Data

How should I cite this in an academic article or report?

ILO Modelled Estimates, via World Bank (2026) – processed by Our World in Data. “Unemployment rate – ILO” [dataset]. ILO Modelled Estimates, via World Bank, “World Development Indicators 125” [original data]. Retrieved June 12, 2026 from https://datapage-v2.owid.pages.dev/grapher/unemployment-rate

All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately. This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.

All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Related research and writing

Featured image

Work and Employment

Bertha Rohenkohl, Pablo Arriagada, and Esteban Ortiz-Ospina

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://datapage-v2.owid.pages.dev/grapher/unemployment-rate.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear