Updated
14 December 2021
| Dataset date: October 07, 2021-October 15, 2022
This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2021 methodology is detailed in Alkire, Kanagaratnam & Suppa (2021).
Updated
14 December 2021
| Dataset date: October 07, 2021-October 15, 2022
This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2021 methodology is detailed in Alkire, Kanagaratnam & Suppa (2021).
Updated
15 September 2021
| Dataset date: November 14, 2020-May 17, 2021
Overview
The dataset contains harmonized indicators created from high-frequency phone surveys collected by the World Bank and partners. The surveys capture the socioeconomic impacts of the COVID-19 pandemic on households and individuals from all developing regions. Data are available for over 90 indicators in 14 topic areas, including education, food security, income, safety nets, and others. For more information, please refer to our Technical Note and Data Dictionary.
Unit of Measure
Percentages.
Aggregation Method:
The data is aggregated by Urban/Rural/National and Industry Sector
Disclaimer:
This harmonized dataset is an ongoing collation and harmonization of COVID-19 high-frequency phone survey (HFPS) data. Harmonization involves redefining indicators and categories so that they are comparable across countries. As a result, even if the names and definitions of indicators appear similar, numbers in this global database might differ slightly from those of each country's publications or dashboard. If you see large discrepancies or other issues, please reach out.
Version Notes:
COVID-19 Harmonized Household Data Feb 18 • Temporarily suppressed select income, labor, and government assistance indicators collected after wave 2 surveys for harmonization review • Added need for, and access to medical care in multiple countries • Temporarily suppressed select income, labor and government assistance indicators collected after wave 2 surveys for harmonization review
Funding Name, Abbreviation, Role:
The project received support from the Trust Fund for Statistical Capacity Building III (TFSCB-III). TFSCB-III is funded by the United Kingdom’s Foreign, Commonwealth & Development Office, the Department of Foreign Affairs and Trade of Ireland, and the Governments of Canada and Korea.
Other Acknowledgments:
This dashboard was created by the Data for Goals (D4G) team and the Regional High-Frequency Phone Survey (HFPS) Focal Points in the EFI Poverty and Equity Global Practice (POV GP), under the guidance of POV GP management, using data collected under the World Bank-wide COVID-19 HFPS initiative.
Time Periods:
March, 2021
Updated
27 November 2020
| Dataset date: July 10, 2019-July 10, 2019
Based on Republic Act 8425, otherwise known as Social Reform and Poverty Alleviation Act, dated 11 December 1997, the poor refers to individuals and families whose income fall below the poverty threshold as defined by the government and/or those that cannot afford in a sustained manner to provide their basic needs of food, health, education, housing and other amenities of life. It may be estimated in terms
of percentages (poverty incidence) and total number of poor families (magnitude of poor families). Also, this dataset has been generated by combining Philippine Standard Geographic Codes (PSGC) and poverty estimates from Philippine Statistics Authority (PSA).
For more details, please refer to the following documents:
https://psa.gov.ph/poverty-press-releases/referenceshttps://psa.gov.ph/poverty-press-releases/technoteshttps://psa.gov.ph/poverty-press-releases/glossaryhttps://psa.gov.ph/sites/default/files/Technical%20Notes%20on%202015%20SAE.pdf
Updated
28 September 2020
| Dataset date: January 01, 1990-December 31, 1990
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.
Updated
27 September 2020
| Dataset date: January 01, 1990-December 31, 1990
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.
Updated
27 September 2020
| Dataset date: January 01, 1990-December 31, 2005
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.
Updated
28 August 2020
| Dataset date: January 01, 1990-December 31, 1990
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.
Updated
28 August 2020
| Dataset date: January 01, 1990-December 31, 1990
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.
Updated
6 July 2020
| Dataset date: April 01, 2018-April 01, 2018
Community facilities surveys for Gihembe, Kigeme and Nyabiheke refugee camps in Rwanda. The surveys contain information on community facility type and operations, energy for lighting and other uses, access to electricity technologies, respondent needs and priorities, and other energy-related issues.
Updated
6 July 2020
| Dataset date: April 01, 2018-April 01, 2018
Enterprise surveys for Gihembe, Kigeme and Nyabiheke refugee camp in Rwanda. The datasets contain information on enterprise type and operations, energy for lighting and productive uses, access to electricity technologies, respondent needs and priorities, and other energy-related issues.
Updated
6 July 2020
| Dataset date: April 01, 2018-April 01, 2018
Household surveys for Gihembe, Kigeme and Nyabiheke refugee camps in Rwanda. The surveys contain information on household demographics, energy use for lighting and cooking, access to electricity technologies, respondent needs and priorities, and other energy-related issues.
Updated
10 November 2019
| Dataset date: January 01, 2005-March 31, 2015
Población con Necesidades Básicas Insatisfechas. La metodología del NBI busca determinar, con ayuda de algunos indicadores simples, si las necesidades básicas de la población se encuentran cubiertas. Los grupos que no alcancen un umbral mínimo fijado, son clasificados como pobres. Los indicadores simples seleccionados, son: Viviendas inadecuadas, Viviendas con hacinamiento crítico, Viviendas con servicios inadecuados, Viviendas con alta dependencia económica, Viviendas con niños en edad escolar que no asisten a la escuela.
Updated
6 February 2018
| Dataset date: May 02, 2016-May 02, 2016
La brecha que existe entre la población sobre la pobreza. La brecha de pobreza está íntimamente relacionada con las condiciones de vida y por consiguiente con la disponibilidad de recursos en caso de desastre
Updated
30 January 2018
| Dataset date: May 02, 2016-May 02, 2016
Engloba aspectos tangibles e intangibles relacionados a la incapacidad de las personas de tener una vida digna. Los indicadores de pobreza rural evidencian insuficiencia de servicios básicos, falta de empleo, salud y educación.
Updated
10 February 2017
| Dataset date: February 10, 2017-February 10, 2017
Here we provide poverty data created using Bayesian model-based geostatistics in combination with high resolution gridded spatial covariates and aggregated mobile phone data applied to geolocated household survey data on poverty from the DHS wealth index (2011), the Progress out of Poverty Index (2014), and household income (2013). Citation: Steele, J. E. et al. Mapping poverty using mobile phone and satellite data. J. R. Soc. Interface 14, 20160690 (2017). Online here: http://rsif.royalsocietypublishing.org/content/14/127/20160690
Updated
16 October 2015
| Dataset date: December 31, 2005-December 31, 2005
The estimates for 2005 were revised following the recomputation of the food thresholds. Completely urban areas; no thresholds for rural areas. The provinces of Batanes, Marinduque, Siquijor, Southern Leyte and Abra were not considered in the computation of the urban and rural food thresholds of their respective regions (Regions II, IV-B, VII, VIII, and CAR). Urban and rural food thresholds were not computed for the provinces of Batanes, Marinduque, Siquijor, Southern Leyte, and Abra. The 2003 Family Income and Expenditure Survey does not include any sample urban barangays from these provinces.
