Total Population by Single-Year Age, Sex, Region, Province, City/Municipality and Barangay (admin 4) Census 2020.
It uses the new 10-digit pcode consistent with [Philippines - Subnational Administrative Boundaries] (https://data.humdata.org/dataset/cod-ab-phl).
Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.
"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023).
Philippines administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
This dataset contains agency- and open source events published in the Attacks on Health Care News Brief and included in the Safeguarding Health in Conflict Coalition (SHCC) annual reporting on violence against or obstruction of health care. This page is managed by SHCC member Insecurity Insight.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
2020 Census Total Population by Barangay (admin4) with new 10-digit pcode with Maguindanao del Sur and Norte; Missing barangays in R12 that moved to BARMM
More than 200 million businesses use Facebook globally. The goal of Meta’s quarterly Small Business Surveys is to learn about the unique perspectives, challenges and opportunities of small and medium-sized businesses (SMBs).
The Future of Business (FoB) Survey is conducted biannually in partnership with the World Bank and the Organisation for Economic Cooperation and Development (OECD) across nearly 100 countries. The target population consists of SMEs that have an active Facebook Business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. Meta also conducts the Global State of Small Business (GSoSB) Survey bi-annually in partnership with various academic partners across approximately 30 countries. Similarly to the FoB Survey, the target population is active Facebook Page Administrators, but also includes the general population of Facebook users.
Survey questions for all surveys cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, gender inequity, access to finance, digital technologies, reduction in revenues, business closures, international trade, inflation, reduction of employees and challenges/needs of the business.
Aggregated country level data for each survey wave is available to the public on HDX and controlled access microdata is available to Data for Good at Meta partners. Please visit https://dataforgood.facebook.com/dfg/tools/future-of-business-survey to apply for access to microdata or contact dataforgood@fb.com for any questions.
The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following:
Microestimates of wealth for all low- and middle-income countries
Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock
Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119
More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/
Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119
Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid
An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
Education indicators for Philippines.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Philippines: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
This dataset contains Who, What, and Where(3W) data for the Aklan Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Cavite Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Capiz Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Camarines Sur Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Biliran Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Bohol Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Antique Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Cebu Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Cotabato Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Dinagat Islands Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
