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Data

Countries with gender-equal inheritance

About this data

Source
Carmichael, Dili, and Rijpma (2014) – processed by Our World in Data
Last updated
March 21, 2018
Date range
1920–2000
Unit
1=yes, 0=no

Related research and writing

A dark blue background with a lighter blue world map superimposed over it. Yellow text that says Economic Inequality by Gender by Our World in Data

Economic Inequality by Gender

Esteban Ortiz-Ospina, Joe Hasell, and Max Roser

Sources and processing

This data is based on the following sources

Carmichael, Dili, and Rijpma – How Was Life? Gender inequality since 1980

Gendered inheritance practices for immovables in 1920 are obtained from the Murdock data, while 1980 and 2000 are from the World Bank.

Information on inheritance practices at the start of the 20th century comes from George Murdock's Ethnographic Atlas (1969). To compare Murdock's figures to contemporary data available from the World Bank's Fifty Years of Women's Legal Rights database, a dichotomous scheme had to be used where 0 indicates inequality and 1 equality.

For further information of these data, see the link above from page 221, under the heading "Historical sources".

Retrieved on
March 21, 2018
Retrieved from
https://dspace.library.uu.nl/bitstream/handle/1874/306236/3014041ec016.pdf?sequence=1
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.
Carmichael, S., Dili, S., and Rijpma, A. (2014). How Was Life? Gender inequality since 1980.

Gendered inheritance practices for immovables in 1920 are obtained from the Murdock data, while 1980 and 2000 are from the World Bank.

Information on inheritance practices at the start of the 20th century comes from George Murdock's Ethnographic Atlas (1969). To compare Murdock's figures to contemporary data available from the World Bank's Fifty Years of Women's Legal Rights database, a dichotomous scheme had to be used where 0 indicates inequality and 1 equality.

For further information of these data, see the link above from page 221, under the heading "Historical sources".

Retrieved on
March 21, 2018
Retrieved from
https://dspace.library.uu.nl/bitstream/handle/1874/306236/3014041ec016.pdf?sequence=1
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.
Carmichael, S., Dili, S., and Rijpma, A. (2014). How Was Life? Gender inequality since 1980.

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: Countries with gender-equal inheritance”. Our World in Data (2026). Data adapted from Carmichael, Dili, and Rijpma. Retrieved from https://archive.ourworldindata.org/20260511-092124/grapher/map-gender-equal-inheritance.html [online resource] (archived on May 11, 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:

Carmichael, Dili, and Rijpma (2014) – processed by Our World in Data

Full citation

Carmichael, Dili, and Rijpma (2014) – processed by Our World in Data. “Countries with gender-equal inheritance” [dataset]. Carmichael, Dili, and Rijpma, “How Was Life? Gender inequality since 1980” [original data]. Retrieved May 12, 2026 from https://archive.ourworldindata.org/20260511-092124/grapher/map-gender-equal-inheritance.html (archived on May 11, 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/map-gender-equal-inheritance.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/map-gender-equal-inheritance.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/map-gender-equal-inheritance.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/map-gender-equal-inheritance.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/map-gender-equal-inheritance.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/map-gender-equal-inheritance.csv?v=1&csvType=full&useColumnShortNames=false")

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