Share of firms that were asked to pay a bribe
What you should know about this indicator
- Measures the share of firms that experienced at least one request for a gift or informal payment across six types of public transactions.
- Covers applications for electrical connections, water connections, construction permits, meetings with tax officials, import licenses (authorization to import specific goods), and operating licenses (permit to legally conduct business activities).
- Data are collected through structured interviews with private sector firms.
- Refusal to answer a question is treated as an affirmative response indicating bribery occurred.
- Corruption imposes administrative and financial burdens, reduces operational efficiency, and increases costs and risks for firms.
- Regional and global averages are computed by taking a simple average of country-level results using only the latest available survey data per country since 2014.
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Sources and processing
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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.
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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: Share of firms that were asked to pay a bribe”, part of the following publication: Bastian Herre, Veronika Samborska, and Esteban Ortiz-Ospina (2016) - “Corruption”. Data adapted from World Bank Enterprise Surveys. Retrieved from https://archive.ourworldindata.org/20260325-171315/grapher/bribery-incidence-for-firms.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 Enterprise Surveys (2024) – with minor processing by Our World in DataFull citation
World Bank Enterprise Surveys (2024) – with minor processing by Our World in Data. “Share of firms that were asked to pay a bribe” [dataset]. World Bank Enterprise Surveys, “Enterprise Surveys - Corruption” [original data]. Retrieved April 6, 2026 from https://archive.ourworldindata.org/20260325-171315/grapher/bribery-incidence-for-firms.html (archived on March 25, 2026).Download
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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.
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/bribery-incidence-for-firms.csv?v=1&csvType=full&useColumnShortNames=falseMetadata URL (JSON format)
https://ourworldindata.org/grapher/bribery-incidence-for-firms.metadata.json?v=1&csvType=full&useColumnShortNames=falseExcel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/bribery-incidence-for-firms.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/bribery-incidence-for-firms.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/bribery-incidence-for-firms.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()R
library(jsonlite)
# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/bribery-incidence-for-firms.csv?v=1&csvType=full&useColumnShortNames=false")
# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/bribery-incidence-for-firms.metadata.json?v=1&csvType=full&useColumnShortNames=false")Stata
import delimited "https://ourworldindata.org/grapher/bribery-incidence-for-firms.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear