Data

Income inequality: Gini coefficient in Latin America

See all data and research on:

What you should know about this indicator

This is current household income. "Current" means that all income sources are added, including labor income, pensions, capital and benefits and transfers. Income has been equivalized – adjusted to account for the fact that people in the same household can share costs like rent and heating.

We construct individual income by adding all income sources together. Whenever possible we distinguish among income from salaried work, self-employment and salaries assigned to owners. Whenever possible we compute labor income from the main activity. Individual non-labor income is divided into three categories: (i) pensions; (ii) capital and benefits; and (iii) transfers. Countries ask different questions to capture data on capital income, interests, profits, rents and dividends. For comparison purposes, we prefer to gather all these questions into a single category. The same criterion applies to transfers, although we also construct a variable that identifies those transfers made by the government, and another that captures transfers clearly associated to poverty-alleviation programs. Since we are interested in capturing current income, non-current items are not included in our definition of income. The same criterion leads to the exclusion of income from the sale of some goods and assets like vehicles, houses, or stocks. We also exclude income from gifts, life insurance, gambling and inheritances.

Once we have individual income, we construct household income by adding income for all members from the household. Household per capita income is computed as the ratio between total household income and the number of members in the household. Finally, we compute adjusted household income by several equivalence scales.

Is the implicit rent from own-housing included in the calculation of income?

Yes, it is included. The concept of income considered in SEDLAC refers to the flow of resources obtained as remuneration towards the use of all the assets owned by an individual or household. According to this definition, income should include not only returns for the use of labor and capital, but also any other rents produced by the possession of durable goods, such as houses or cars.

Families that live in their own dwellings implicitly receive a flow of income equivalent to the market value of the service that the use of this property represents for them. This remuneration should be computed as part of household income, even though it is never recorded in a formal market.

In some surveys, owners are asked to estimate the rent they would have to pay if they had to rent the houses they occupy. The answer to this question is used to impute rents to own-housing, although issues of reliability in the answers are usually raised, in particular in areas where housing markets are not well developed.

In those surveys where this information is not available or is clearly unreliable, we increase household income of housing owners by 10%, a value that is consistent with estimates of implicit rents in the region.

Income inequality: Gini coefficient in Latin America
The measures inequality on a scale from 0 to 1. Higher values indicate higher inequality.
Source
SEDLAC (CEDLAS and The World Bank) (2024) – with major processing by Our World in Data
Last updated
March 8, 2024
Next expected update
March 2025
Date range
1974–2022

Sources and processing

This data is based on the following sources

The Socio-Economic Database for Latin America and the Caribbean (SEDLAC) includes statistics on poverty and other distributional and social variables from all Latin American and several Caribbean (LAC) countries. All statistics are computed from microdata from major household surveys carried out in these countries using a homogenous methodology (data permitting). Statistics are updated periodically.

SEDLAC allows users to monitor trends in poverty and other distributional and social indicators in the region. The dataset is available as Excel tables with information for each country/year, accompanied by graphs, maps, and reports.

The Center for Distributional, Labor and Social Studies (CEDLAS) of the Universidad Nacional de La Plata, in partnership with World Bank’s Poverty and Equity Group, have developed the Socio-Economic Database for Latin America and the Caribbean (SEDLAC) with the purpose of improving the timely access to key socio-economic statistics, including indicators on poverty, inequality, income, employment, access to services, education, health, housing, social programs, and numerous demographics.

Retrieved on
March 8, 2024
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.
Socio-Economic Database for Latin America and the Caribbean (CEDLAS and The World Bank)

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

Where there were multiple observations for a particular year, we selected the observation drawn from a more recent round of a survey, or, in the case of biannual surveys, the observation drawn from the second semester.

The data is originally presented in separate survey rounds for each country, given different methodologies and aggregation levels considered. For this reason, these survey rounds are not directly comparable. Due to visualization limitations, we have connected each country series. For more detailed analysis, you can check these survey rounds on the SEDLAC dataset website.

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: Income inequality: Gini coefficient in Latin America”, part of the following publication: Joe Hasell, Max Roser, Esteban Ortiz-Ospina and Pablo Arriagada (2022) - “Poverty”. Data adapted from SEDLAC (CEDLAS and The World Bank). Retrieved from https://ourworldindata.org/grapher/income-inequality-in-latin-america [online resource]
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:

SEDLAC (CEDLAS and The World Bank) (2024) – with major processing by Our World in Data

Full citation

SEDLAC (CEDLAS and The World Bank) (2024) – with major processing by Our World in Data. “Income inequality: Gini coefficient in Latin America” [dataset]. SEDLAC (CEDLAS and The World Bank), “Socio-Economic Database for Latin America and the Caribbean (SEDLAC)” [original data]. Retrieved December 14, 2024 from https://ourworldindata.org/grapher/income-inequality-in-latin-america