| Source |
Facebook |
| Contributor |
Facebook
|
| Date of Dataset |
April 01, 2021-October 17, 2021 |
| Updated |
6 May 2021
|
| Expected Update Frequency |
As needed |
| Location |
Algeria,
Angola,
Argentina,
Bangladesh,
Belize,
Benin,
Bhutan,
Bolivia (Plurinational State of),
Botswana,
Brazil,
Burkina Faso,
Burundi,
Cabo Verde,
Cambodia,
Central African Republic,
Chad,
Colombia,
Comoros,
Congo,
Costa Rica,
Côte d'Ivoire,
Democratic Republic of the Congo,
Djibouti,
Dominica,
Dominican Republic,
Ecuador,
Equatorial Guinea,
Eritrea,
Ethiopia,
Gabon,
Ghana,
Grenada,
Guatemala,
Guinea,
Guinea-Bissau,
Guyana,
Haiti,
Honduras,
India,
Indonesia,
Jamaica,
Jordan,
Kazakhstan,
Kenya,
Kyrgyzstan,
Lao People's Democratic Republic,
Lesotho,
Liberia,
Libya,
Madagascar,
Malawi,
Malaysia,
Maldives,
Mali,
Mauritania,
Mauritius,
Mexico,
Mongolia,
Mozambique,
Namibia,
Nepal,
Netherlands,
Nicaragua,
Niger,
Pakistan,
Paraguay,
Peru,
Philippines,
Saint Lucia,
Saint Vincent And The Grenadines,
South Africa,
Sri Lanka,
Tajikistan,
Thailand,
Timor-Leste,
Togo,
Tunisia,
Turkmenistan,
Uganda,
United Republic of Tanzania,
Uzbekistan,
Viet Nam,
Zambia,
Zimbabwe
|
| Visibility |
Public
|
| License |
Other
: Creative Commons Attribution-Non Commercial 4.0 International (CC BY-NC 4.0)
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
|
| Methodology |
Researchers at the University of California - Berkeley and Facebook developed micro-estimates of wealth and poverty that cover the populated surface of all 135 low and middle-income countries (LMICs) at 2.4km resolution. The estimates are built by applying machine learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, topographic maps, as well as aggregated and de-identified connectivity data from Facebook. They train and calibrate the estimates using nationally-representative household survey 20 data from 56 LMICs, then validate their accuracy using four independent sources of household survey data from 18 countries. They also provide confidence intervals for each micro-estimate to facilitate responsible downstream use.
Research publication (preprint) for the Relative Wealth Index is available here: https://arxiv.org/abs/2104.07761
|
| Caveats / Comments |
|
| Tags |
|
| File Format |
|
Download