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Freedom of association thick index

V-Dem
See all data and research on:
Democracy

What you should know about this indicator

  • V-Dem covers many more countries since 1900, which affects regional averages.
  • We provide two kinds of regional averages: country averages and population-weighted averages. Country averages weigh each country equally and give a sense of how the typical country is doing. Population-weighted averages weigh countries with larger populations more and therefore better reflect the average person's experience.

How is this data described by its producer - V-Dem?

Question: To what extent are parties, including opposition parties, allowed to form and to participate in elections, and to what extent are civil society organizations able to form and to operate freely?

Scale: Interval, from low to high (0-1).

V-Dem indicator name: v2x_frassoc_thick

Freedom of association thick index
V-Dem
Central estimate of the extent to which parties, including opposition parties, are allowed to form and participate in elections and the extent to which civil society organizations are allowed to form and operate freely.
Source
V-Dem (2026) – processed by Our World in Data
Last updated
March 17, 2026
Next expected update
March 2027
Date range
1789–2025

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Sources and processing

This data is based on the following sources

V-Dem – Democracy report

The Varieties of Democracy (V-Dem) project publishes data and research on democracy and human rights.

It acknowledges that democracy can be characterized differently and measures electoral, liberal, participatory, deliberative, and egalitarian characterizations of democracy.

The project relies on evaluations by around 3,500 country experts and supplementary work by its researchers to assess political institutions and the protection of rights.

The project is managed by the V-Dem Institute, based at the University of Gothenburg in Sweden.

This snapshot contains all 531 V-Dem indicators and 251 indices + 62 other indicators from other data sources.

For more information, please refer to https://www.v-dem.net/data/the-v-dem-dataset/

Retrieved on
March 17, 2026
Retrieved from
https://v-dem.net/data/the-v-dem-dataset/
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.
Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Fabio Angiolillo, Michael Bernhard, Agnes Cornell, M. Steven Fish, Linnea Fox, Lisa Gastaldi, Haakon Gjerløw, Adam Glynn, Ana Good God, Sandra Grahn, Allen Hicken, Katrin Kinzelbach, Joshua Krusell, Kyle L. Marquardt, Kelly McMann, Valeriya Mechkova, Juraj Medzihorsky, Natalia Natsika, Anja Neundorf, Pamela Paxton, Daniel Pemstein, Johannes von Römer, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Aksel Sundström, Marcus Tannenberg, Eitan Tzelgov, Yi-ting Wang, Felix Wiebrecht, Tore Wig, Steven Wilson and Daniel Ziblatt. 2026. "V-Dem [Country-Year/Country-Date] Dataset v16" Varieties of Democracy (V-Dem) Project. https://doi.org/10.23696/vdemds26
Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2026. "The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data". V-Dem Working Paper No. 21. 11th edition. University of Gothenburg: Varieties of Democracy Institute.

The Varieties of Democracy (V-Dem) project publishes data and research on democracy and human rights.

It acknowledges that democracy can be characterized differently and measures electoral, liberal, participatory, deliberative, and egalitarian characterizations of democracy.

The project relies on evaluations by around 3,500 country experts and supplementary work by its researchers to assess political institutions and the protection of rights.

The project is managed by the V-Dem Institute, based at the University of Gothenburg in Sweden.

This snapshot contains all 531 V-Dem indicators and 251 indices + 62 other indicators from other data sources.

For more information, please refer to https://www.v-dem.net/data/the-v-dem-dataset/

Retrieved on
March 17, 2026
Retrieved from
https://v-dem.net/data/the-v-dem-dataset/
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.
Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, Jan Teorell, David Altman, Fabio Angiolillo, Michael Bernhard, Agnes Cornell, M. Steven Fish, Linnea Fox, Lisa Gastaldi, Haakon Gjerløw, Adam Glynn, Ana Good God, Sandra Grahn, Allen Hicken, Katrin Kinzelbach, Joshua Krusell, Kyle L. Marquardt, Kelly McMann, Valeriya Mechkova, Juraj Medzihorsky, Natalia Natsika, Anja Neundorf, Pamela Paxton, Daniel Pemstein, Johannes von Römer, Brigitte Seim, Rachel Sigman, Svend-Erik Skaaning, Jeffrey Staton, Aksel Sundström, Marcus Tannenberg, Eitan Tzelgov, Yi-ting Wang, Felix Wiebrecht, Tore Wig, Steven Wilson and Daniel Ziblatt. 2026. "V-Dem [Country-Year/Country-Date] Dataset v16" Varieties of Democracy (V-Dem) Project. https://doi.org/10.23696/vdemds26
Pemstein, Daniel, Kyle L. Marquardt, Eitan Tzelgov, Yi-ting Wang, Juraj Medzihorsky, Joshua Krusell, Farhad Miri, and Johannes von Römer. 2026. "The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data". V-Dem Working Paper No. 21. 11th edition. University of Gothenburg: Varieties of Democracy Institute.

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
Notes on our processing step for this indicator

Region aggregates

The default regional aggregates (including values for the World) have been estimated by averaging the country values. These are only estimated when data for most countries and populations is available (i.e. 70% for most continents). We have used the list of countries in 1900 as a reference.

In addition, regional aggregates with names like "Region (population-weighted)" (including values for World) have been estimated by averaging the country values weighted by population. The population values are from the UN WPP 2024 revision dataset. These are only estimated when 70% of people in region have data for the given year.

Data imputation

We expand the years covered by V-Dem further: To expand the time coverage of today's countries and include more of the period when they were still non-sovereign territories, we identified the historical entity they were a part of and used that regime's data whenever available

For example, V-Dem only provides regime data since Bangladesh's independence in 1971. There is, however, regime data for Pakistan and the colony of India, both of which the current territory of Bangladesh was a part. We, therefore, use the regime data of Pakistan for Bangladesh from 1947 to 1970, and the regime data of India from 1789 to 1946. We did so for all countries with a past or current population of more than one million.

For more details on the imputation methodology and which countries are affected, refer to this file.

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: Freedom of association thick index”, part of the following publication: Bastian Herre, Lucas Rodés-Guirao, and Esteban Ortiz-Ospina (2013) - “Democracy”. Data adapted from V-Dem. Retrieved from https://archive.ourworldindata.org/20260325-171315/grapher/freedom-of-association-index.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:

V-Dem (2026) – processed by Our World in Data

Full citation

V-Dem (2026) – processed by Our World in Data. “Freedom of association thick index – V-Dem” [dataset]. V-Dem, “Democracy report v16” [original data]. Retrieved March 31, 2026 from https://archive.ourworldindata.org/20260325-171315/grapher/freedom-of-association-index.html (archived on March 25, 2026).

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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://ourworldindata.org/grapher/freedom-of-association-index.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/freedom-of-association-index.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/freedom-of-association-index.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/freedom-of-association-index.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/freedom-of-association-index.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/freedom-of-association-index.csv?v=1&csvType=full&useColumnShortNames=false")

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