Our World
in Data
Oxford Martin School logoUniversity of Oxford logoGlobal Change Data Lab logo
Data

Public sector employment as a share of total employment

See all data and research on:
State Capacity

About this data

Source
World Bank (2022) – with minor processing by Our World in Data
Last updated
November 21, 2023
Next expected update
May 2026
Date range
2000–2020
Unit
%

Sources and processing

This data is based on the following sources

World Bank – Worldwide Bureaucracy Indicators (WWBI)

The Worldwide Bureaucracy Indicators (WWBI) database is a unique cross-national dataset on public sector employment and wages that aims to fill an information gap, thereby helping researchers, development practitioners, and policymakers gain a better understanding of the personnel dimensions of state capability, the footprint of the public sector within the overall labor market, and the fiscal implications of the public sector wage bill. The dataset is derived from administrative data and household surveys, thereby complementing existing, expert perception-based approaches.

The WWBI includes 302 indicators that are estimated from microdata drawn from the labor force and household welfare surveys and augmented with administrative data for 202 economies in five categories: the demographics of the private and public sector workforces; public sector wage premiums; relative wages and pay compression ratios, gender pay gaps; and the public sector wage bill.

Retrieved on
November 21, 2023
Retrieved from
https://datacatalog.worldbank.org/dataset/worldwide-bureaucracy-indicators
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.
World Bank. 2022. Worldwide Bureaucracy Indicators version 3.0

The Worldwide Bureaucracy Indicators (WWBI) database is a unique cross-national dataset on public sector employment and wages that aims to fill an information gap, thereby helping researchers, development practitioners, and policymakers gain a better understanding of the personnel dimensions of state capability, the footprint of the public sector within the overall labor market, and the fiscal implications of the public sector wage bill. The dataset is derived from administrative data and household surveys, thereby complementing existing, expert perception-based approaches.

The WWBI includes 302 indicators that are estimated from microdata drawn from the labor force and household welfare surveys and augmented with administrative data for 202 economies in five categories: the demographics of the private and public sector workforces; public sector wage premiums; relative wages and pay compression ratios, gender pay gaps; and the public sector wage bill.

Retrieved on
November 21, 2023
Retrieved from
https://datacatalog.worldbank.org/dataset/worldwide-bureaucracy-indicators
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.
World Bank. 2022. Worldwide Bureaucracy Indicators version 3.0

How we process data at Our World in Data

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.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • 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 (see below). 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.

Citations

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: Public sector employment as a share of total employment”, part of the following publication: Bastian Herre and Pablo Arriagada (2023) - “State Capacity”. Data adapted from World Bank. Retrieved from https://archive.ourworldindata.org/20260325-171315/grapher/public-sector-employment-as-a-share-of-total-employment.html [online resource] (archived on March 25, 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:

World Bank (2022) – with minor processing by Our World in Data

Full citation

World Bank (2022) – with minor processing by Our World in Data. “Public sector employment as a share of total employment” [dataset]. World Bank, “Worldwide Bureaucracy Indicators (WWBI) Version 3” [original data]. Retrieved April 6, 2026 from https://archive.ourworldindata.org/20260325-171315/grapher/public-sector-employment-as-a-share-of-total-employment.html (archived on March 25, 2026).

Download

Quick download

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.

Download full data

Includes all entities and time points

Download displayed data

Includes only the entities and time points currently visible in the chart

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://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.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://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.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/public-sector-employment-as-a-share-of-total-employment.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://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/public-sector-employment-as-a-share-of-total-employment.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear