This layer contains information about the recurrence of poverty incidence - by second-level administrative area - observed during the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data sources: Philippines National Statistical Coordination Board (NSCB), 2006-2012. It should be noted that, in absence of national food security information, poverty data has been used as a proxy to food insecurity - assuming that families below the poverty line are likely to be food insecure. Also, in the Philippines official methodology, the poverty line may be viewed as the minimum income required to meet food requirements as well as non-food basic needs. The main indicator used for the analysis was the recurrence of poverty incidence, with a threshold set to 30% of the families to represent 1 out of 3 people below the poverty line.

Original dataset title: ICA Philippines, 2014 - Recurrence of Poverty Incidence, 2006-2012

Philippines PH: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.700 % in 2021. This records a decrease from the previous number of 12.900 % for 2018. Philippines PH: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 15.850 % from Dec 2000 (Median) to 2021, with 8 observations. The data reached an all-time high of 17.100 % in 2006 and a record low of 11.700 % in 2021. Philippines PH: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Philippines Magnitude of Poor Population: National Capital Region (NCR) data was reported at 494,630.000 Person in 2015. This records an increase from the previous number of 460,831.000 Person for 2012. Philippines Magnitude of Poor Population: National Capital Region (NCR) data is updated yearly, averaging 563,179.000 Person from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 1,909,886.000 Person in 1988 and a record low of 346,747.000 Person in 2003. Philippines Magnitude of Poor Population: National Capital Region (NCR) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Based on preliminary results in 2023, the share of individuals in the Philippines with income below the poverty threshold was estimated at 15.5 percent, down from the estimate in 2021. In that year, the average per capita food threshold reached 23,000 Philippine pesos.

Unemployment Rate in Philippines decreased to 3.70 percent in June from 3.90 percent in May of 2025. This dataset provides - Philippines Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Philippines Incidence of Poor Families: National Capital Region (NCR) data was reported at 2.700 % in 2015. This records an increase from the previous number of 2.600 % for 2012. Philippines Incidence of Poor Families: National Capital Region (NCR) data is updated yearly, averaging 4.100 % from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 21.600 % in 1988 and a record low of 2.100 % in 2003. Philippines Incidence of Poor Families: National Capital Region (NCR) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

This report is intended as an input into the Philippine Government's poverty eradication strategy. The report aims to update our understanding of the nature of poverty and the recent progress in poverty reduction in the Philippines. It examines the extent to which growth in the nineties has translated into poverty reduction and analyzes how well publicly-provided social services reach the poor and whether redistributive policies attain their objectives. The report also focuses on the social impact of the recent financial/El Nino crises and explores policies to reduce vulnerability in the Philippines. The report comprises two volumes. The main volume starts with a summary of the profile of the poor and trends in poverty. It then proposes a framework for attacking poverty built on three pillars: 1) promoting opportunity for poor people through generating broad-based growth and building up the assets of the poor; 2) enhancing security of poor people through reducing vulnerability and helping the poor manage risks; and 3) facilitating empowerment of poor people to ensure accountable institutions. Finally, the main report examines the information base for pro-poor policies and offers suggestions for future work. The second volume provides the detailed analytical basis for many of the findings presented in the main report.

Philippines Incidence of Poor Families: CALABARZON data was reported at 6.700 % in 2015. This records a decrease from the previous number of 8.300 % for 2012. Philippines Incidence of Poor Families: CALABARZON data is updated yearly, averaging 8.800 % from Dec 1991 (Median) to 2015, with 7 observations. The data reached an all-time high of 19.100 % in 1991 and a record low of 6.700 % in 2015. Philippines Incidence of Poor Families: CALABARZON data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

Sample is disproportionately allocated across the four broad regions.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size in Philippines was 1,000 individuals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

The KALAHI-CIDSS program was set up in 2002 to alleviate rural poverty in the Philippines. It provides resources to poor rural municipalities to invest in public goods and by reviving local institutions to enhance people’s participation in governance. The project targeted the poorest 25 percent of municipalities in each of the poorest 42 provinces. The government of the Philippines committed $82 million to the project, which was complemented by a $100 million loan from the World Bank. As of December 2010, the project had covered 4,583 barangays (villages) in 200 municipalities and supported 5,645 subprojects, worth Php 5.7 billion and benefiting about 1.26 million households. The program's impact evaluation was designed in 2003 to evaluate general impacts on poverty reduction, social capital, empowerment, and governance. The team collected quantitative and qualitative data before, during, and after project implementation in a sample of KALAHI-CIDSS municipalities that received support ("treatment" municipalities) and from comparable municipalities that did not receive support ("control" municipalities). The quantitative baseline survey was carried out in September-October 2003, the quantitative midterm in October-November 2006 and the quantitative endline survey in February-March 2010. Data were collected on a broad range of indicators: service delivery (access to health, education), poverty (employment, per capita consumption, self-rated poverty), empowerment and governance (group membership, participation in barangay assemblies, collective action). The quantitative sample includes 2,400 households in 135 barangays in 16 municipalities in 4 provinces.

Philippines Per Capita Poverty Threshold: Cordillera Administrative Region (CAR) data was reported at 21,770.000 PHP in 2015. This records an increase from the previous number of 19,483.000 PHP for 2012. Philippines Per Capita Poverty Threshold: Cordillera Administrative Region (CAR) data is updated yearly, averaging 13,471.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 21,770.000 PHP in 2015 and a record low of 5,116.000 PHP in 1988. Philippines Per Capita Poverty Threshold: Cordillera Administrative Region (CAR) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 1000.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

Philippines Incidence of Poor Population: Northern Mindanao data was reported at 36.600 % in 2015. This records a decrease from the previous number of 39.500 % for 2012. Philippines Incidence of Poor Population: Northern Mindanao data is updated yearly, averaging 41.950 % from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 54.100 % in 1994 and a record low of 36.600 % in 2015. Philippines Incidence of Poor Population: Northern Mindanao data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

This dataset measures food availability and access for 76 low- and middle-income countries. The dataset includes annual country-level data on area, yield, production, nonfood use, trade, and consumption for grains and root and tuber crops (combined as R&T in the documentation tables), food aid, total value of imports and exports, gross domestic product, and population compiled from a variety of sources. This dataset is the basis for the International Food Security Assessment 2015-2025 released in June 2015. This annual ERS report projects food availability and access for 76 low- and middle-income countries over a 10-year period. Countries (Spatial Description, continued): Democratic Republic of the Congo, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Gambia, Georgia, Ghana, Guatemala, Guinea, Guinea-Bissau, Haiti, Honduras, India, Indonesia, Jamaica, Kenya, Kyrgyzstan, Laos, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Moldova, Mongolia, Morocco, Mozambique, Namibia, Nepal, Nicaragua, Niger, Nigeria, North Korea, Pakistan, Peru, Philippines, Rwanda, Senegal, Sierra Leone, Somalia, Sri Lanka, Sudan, Swaziland, Tajikistan, Tanzania, Togo, Tunisia, Turkmenistan, Uganda, Uzbekistan, Vietnam, Yemen, Zambia, and Zimbabwe. Resources in this dataset:Resource Title: CSV File for all years and all countries. File Name: gfa25.csvResource Title: International Food Security country data. File Name: GrainDemandProduction.xlsxResource Description: Excel files of individual country data. Please note that these files provide the data in a different layout from the CSV file. This version of the data files was updated 9-2-2021

More up-to-date files may be found at: https://www.ers.usda.gov/data-products/international-food-security.aspx

The Poverty Alleviation in the Wake of Typhoon Yolanda Surveys are household surveys of 800 over three years (800 x 3) individuals in selected communities, in Tacloban, Tanauan and Palo in the province of Leyte, the Philippines. The survey covers experiences from pre- to post-Yolanda. Disaster response, resilience and community support are its main focus. Respondents were asked questions on their experiences, attitudes and perceptions on assistance, relief and relocation. Questions about their access to food, health services and education, livelihood, and community support were also included. The respondents’ background characteristics and the household roster were also gathered by survey.This project monitors the effectiveness of the Typhoon Yolanda relief efforts in the Philippines in relation to good governance and building sustainable routes out of poverty. This project focuses on urban risk, vulnerability and resilience in the aftermath of Yolanda. The key themes of the project are risk, vulnerability, resilience and shocks in relation to environmental disaster and pathways in and out of poverty. The project aims to identify the extent to which resource allocation can go beyond disaster 'relief' and build sustainable livelihoods beyond the immediate aftermath of the disaster. It will assess the extent to which disaster relief funding is related to need and what factors dictate the efficient allocation of funds over the immediate and medium term. It will assess whether communities have actually been built back better and if not then why not. The project will also engage with the theoretical framework of human security e.g. in relation to food, health, environmental, personal, and community security but also individual and community resilience and agency. Survey. There are two types of data generated by the survey: one is the individual as unit of analysis and the other is the household level data, derived from the household roster form. To generate the individual data, the household head or the spouse of the household head was interviewed. In cases when both are not available, any responsible adult who is knowledgeable about the personal details of the members of the household is interviewed. The data generated from this survey serves as baseline data of this study on poverty alleviation four years after selected localities of Tacloban, Tanauan and Palo were devastated by Yolanda.

Philippines Incidence of Poor Population: CALABARZON data was reported at 9.100 % in 2015. This records a decrease from the previous number of 10.900 % for 2012. Philippines Incidence of Poor Population: CALABARZON data is updated yearly, averaging 11.900 % from Dec 1991 (Median) to 2015, with 7 observations. The data reached an all-time high of 22.700 % in 1991 and a record low of 9.100 % in 2015. Philippines Incidence of Poor Population: CALABARZON data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Magnitude of Poor Families: Philippines data was reported at 3,746,513.000 Unit in 2015. This records a decrease from the previous number of 4,214,921.000 Unit for 2012. Magnitude of Poor Families: Philippines data is updated yearly, averaging 4,091,789.000 Unit from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 4,531,170.000 Unit in 1994 and a record low of 3,293,096.000 Unit in 2003. Magnitude of Poor Families: Philippines data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Philippines Per Capita Poverty Threshold: CALABARZON data was reported at 22,121.000 PHP in 2015. This records an increase from the previous number of 19,137.000 PHP for 2012. Philippines Per Capita Poverty Threshold: CALABARZON data is updated yearly, averaging 13,670.000 PHP from Dec 1991 (Median) to 2015, with 7 observations. The data reached an all-time high of 22,121.000 PHP in 2015 and a record low of 6,409.000 PHP in 1991. Philippines Per Capita Poverty Threshold: CALABARZON data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Philippines Incidence of Poor Families: Central Luzon data was reported at 8.900 % in 2015. This records a decrease from the previous number of 10.100 % for 2012. Philippines Incidence of Poor Families: Central Luzon data is updated yearly, averaging 13.050 % from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 29.300 % in 1988 and a record low of 8.900 % in 2015. Philippines Incidence of Poor Families: Central Luzon data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Philippines Incidence of Poor Families: Cagayan Valley data was reported at 11.700 % in 2015. This records a decrease from the previous number of 17.000 % for 2012. Philippines Incidence of Poor Families: Cagayan Valley data is updated yearly, averaging 23.500 % from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 40.400 % in 1988 and a record low of 11.700 % in 2015. Philippines Incidence of Poor Families: Cagayan Valley data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.