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 PH: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 13.000 % in 2012. This records an increase from the previous number of 12.600 % for 2009. Philippines PH: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 12.600 % from Dec 2006 (Median) to 2012, with 3 observations. The data reached an all-time high of 13.000 % in 2012 and a record low of 12.600 % in 2009. Philippines PH: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population 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: Poverty. Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

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.

Number of poor at $1.9 a day of Philippines plummeted by 53.97% from 6.3 million persons in 2015 to 2.9 million persons in 2018. Since the 2.02% rise in 2012, number of poor at $1.9 a day sank by 71.29% in 2018. Number of people, in millions, living on less than $1.90 a day at 2011 PPP is calculated by multiplying the poverty rate and the population. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Preliminary estimates for 2023 show that the region of Zamboanga Peninsula had the highest poverty incidence among families in the Philippines at 24.2 percent. In comparison, the National Capital Region (NCR) had the lowest poverty incidence among families during this period. Overall, the total poverty incidence of families in the Philippines was 10.9 percent.

Poverty rate at $1.9 a day of Philippines plummeted by 34.57% from 8.10 % in 2021 to 5.30 % in 2023. Since the 7.41% surge in 2006, poverty rate at $1.9 a day sank by 79.69% in 2023. Population below $1.9 a day is the percentage of the population living on less than $1.9 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Philippines PH: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 21.600 % in 2015. This records a decrease from the previous number of 25.200 % for 2012. Philippines PH: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 25.200 % from Dec 2003 (Median) to 2015, with 5 observations. The data reached an all-time high of 26.600 % in 2006 and a record low of 21.600 % in 2015. Philippines PH: Poverty Headcount Ratio at National Poverty Lines: % of Population 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: Poverty. National poverty headcount ratio is the percentage of the population living below the national poverty lines. National estimates are based on population-weighted subgroup estimates from household surveys.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Poverty ratio at $1.9 a day of Philippines plummeted by 55.74% from 6.1 % in 2015 to 2.7 % in 2018. Since the 10.77% surge in 2006, poverty ratio at $1.9 a day sank by 81.25% in 2018. Poverty headcount ratio at $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Abstract

Estimated at 10 to 20 percent of the 109 million population in Philippines, Indigenous Peoples (IPs) are among the poorest and most marginalized, although they live in regions with vast natural resources. The lack of representation of IPs in official surveys and administrative data prevents an accurate assessment of their living conditions and the socio-economic challenges they face. This silences their voice, obscures state accountability towards them, and limits their agency to take on a more active role in society. The few available data and anecdotal evidence reveal that IPs face important inequalities of opportunity in several human development dimensions, which are likely aggravated by the COVID-19 pandemic. However, the extent of these inequalities is not well understood, due to scant data and research on IPs. The lack of surveys with information on ethnicity has also made it difficult to examine the type and extent of inequalities among and within ethnic groups in the country, as well as the impact of intersectionality with gender, disability, and place of residence on their inclusion. This represents a significant challenge when creating public policy at the national level or poverty reduction programs at the local level, as IPs remain unnoticed, unaccounted for, and ultimately deprived of their rights and any real benefit.

Therefore, reliable data on IPs is urgently needed, particularly in this COVID-19 era where IPs can be disproportionately disadvantaged due to legacies of inequality and exclusion. Hence, to collect data and inform evidence-based policy/decision making to better target the needs of IPs, the World Bank commissioned this first ever IP-specific household (HH) survey in Philippines to Philippine Survey and Research Center, Inc. (PSRC).

The main objective of this quantitative household survey is to improve the current understanding about the Indigenous Peoples (IPs) population in the Philippines, and eventually, craft strategies when addressing inequality or representation of the group. Specifically, the study aims to: 1. Collect as much data and inform evidence-based policy/decision making to better target the needs of IPs; 2. Gauge a better view/understanding of the IPs’ poverty, socio-economic condition and the exercise of their rights; 3. Add current knowledge into the ongoing World Bank Advisory Services and Analytics on the Indigenous Peoples of the Philippines.

Geographic coverage

Selected IP areas in the Philippines

Analysis unit

Indigenous Peoples (IPs) and Non-Indigenous Peoples (NIPs) with the following specifications: • Male/Female • 18 years old and above

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified multi-stage area probability sampling was employed as follows: • Stratification: The sample was stratified by region and by locale (i.e., urban/rural) • First Stage: Independent random selection of PSUs (barangays) within the strata • Second Stage: Selection of SSUs (households) within the sampled PSUs

A household is defined as a social unit consisting of a person or a group of persons who sleep in the same housing unit and have a common arrangement in the preparation and consumption of food. Household is often comprised of individuals related by blood . Other members of households not related to the household head by blood such as helper, borders, and non relatives can be included as member of the household as long they prepare and consume food together and do not go home to the fa mily more than once in a week. The domain was the Philippines’ 17 administrative regions. Using the Indigenous Peoples (IP) household population from the 2020 Census, the following information were computed: • Proportion of IP household population from Census for each region • Proportion of each region out of total IP household population

To manage cost and timings, sampling coverage was focused on regions greater than or about 3% from both information above and IP household population of at least 250,000. The 2,400 sample was then split into these regions to arrive at the desired area cuts: • CAR • Other Selected Luzon Regions (Cagayan Valley, MIMAROPA) • Western Visayas • Other Mindanao Regions (Zamboanga Peninsula, Northern Mindanao, Davao, SOCCSKSARGEN, CARAGA) • BARMM

From the sample of 2,400, there were 240 PSUs across the 10 covered regions. The 240 PSUs covered were split proportionately across the 10 regions using the IP household population. The table below shows the sampling breakdown at regional level.

Mode of data collection

Face-to-face [f2f]

Research instrument

Available in the English language but conducted in either English or Tagalog

Response rate

To achieve 2,400 completed interviews, 12,131 households were approached/ knocked. Of the 12,131 households knocked, 2,273 refused, 3,028 gave no reply or door locked, and 4,430 were not eligible given the specific requirements that we were looking for. The response rate among eligible interviews is 51%. Response rate is higher in Luzon and lowest in Mindanao.

Abstract

The 2008 Annual Poverty Indicators Survey (APIS) is conducted by the National Statistics Office (NSO) as a rider to the July 2008 Labor Force Survey (LFS). The 2008 APIS is the sixth in the series of annual poverty indicators surveys conducted nationwide. Since 1998, APIS has been conducted during the years when the Family Income and Expenditures Survey (FIES) is not conducted, except in 2001 and 2005 due to budgetary constraints.

The APIS is a nationwide survey designed to provide non-income indicators related to poverty at the national and regional levels. It is designed to gather data on the socio-economic profile of families and other information that are related to their living conditions. Specifically, it generates indicators which are correlated with poverty, such as indicators regarding the ownership or possession of house and lot, the types of the materials of the roofs and walls of their housing units, their access to safe water, the types of toilet facility they use in their homes, and presence of family members of specified characteristics such as children 6-12 years old enrolled in elementary, children 13-16 years old enrolled in high school, members 18 years old and over gainfully employed, working children 5-17 years old and family members with membership in any health, life and/or pre-need insurance system.

The APIS is being undertaken by the National Statistics Office as mandataed by Commonwealth Act 591 which authorizes the then Bureau of the Census and Statistics, now NSO, "to conduct by enumeration, sampling or other methods, for statistical purposes, studies of the social and economic situation of the country" and in consonance with the provision of Executive Order 121 which designated the office as the "major statistical agency responsible for generating general purpose statistics.

Geographic coverage

National Coverage Seventeen (17) Administrative Regions: National Capital Region (NCR) Cordillera Administrative Region (CAR) I - Ilocos II - Cagayan Valley III - Central Luzon IVA - CALABARZON IVB - MIMAROPA V - Bicol VI - Western Visayas VII - Central Visayas VIII - Eastern Visayas IX - Zamboanga Peninsula X - Northern Mindanao XI - Davao XII - SOCCSKSARGEN XIII - Caraga Autonomous Region in Muslim Mindanao (ARMM)

Analysis unit

Households

Universe

The survey covered all households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 APIS is a sample survey designed to provide data representative of the country and its 17 administrative regions. The survey's sample design helps ensure this representativeness. The 2008 APIS used the 2003 master sample created for household surveys on the basis of the 2000 Census of Population and Housing (CPH) results. The survey used four replicates of the master sample. For each region (domain) and stratum, a three-stage sampling scheme was used: the selection of primary sampling units (PSUs) for the first stage, of sample enumeration areas (EAs) for the second stage, and of sample housing units for the third stage. PSUs within a region were stratified based on the proportion of households living in housing units made of strong materials, proportion of households in the barangay engaged in agricultural activities and per capita income of the city/municipality.

As earlier mentioned, a three-stage sampling design was used in each stratum within a region. In the first stage, primary sampling units (PSUs) were selected with probability proportional to the number of households in the 2000 Census. PSUs consisted of a barangay or a group of contiguous barangays. In the second stage, in each sampled PSU, EAs were selected with probability proportional to the number of households in the 2000 Census. An EA is defined as an area with discernable boundaries consisting of approximately 350 contiguous households. In the third stage, from each sampled EA, housing units were selected using systematic sampling. For operational considerations, at most 30 housing units were selected per sample EA. All households in sample housing units were interviewed except for sample housing units with more than three households. In such a housing unit, three households were randomly selected with equal probability.

The 2008 APIS was conducted simultaneously with the July 2008 Labor Force Survey (LFS). All sample households of the July 2008 LFS were interviewed for the 2008 APIS. Only household members related to the household head by blood, marriage or adoption were considered as members of the sample household in APIS. Family members of the household head who are working abroad were excluded.

Sampling deviation

NA

Mode of data collection

Face-to-face [f2f]

Research instrument

Although questions on 'Changes in Welfare' were dropped and some items were modified for the 2008 APIS, most of the questions/items in the previous APISs were retained as requested by data users. Nine items were added in order to generate data that will be more useful in assessing the poverty situation in the country. The new questionnaire for the 2008 contains the abridged version of the module on entrepreneurial activities resulting to the reduction of the number of pages from 24 to 12. The decision to use the abridged version was based on the results of the study entitled “Redesigning APIS as a Poverty Monitoring Tool” undertaken by the Demographic and Social Statistics Division in 2006. The redesigned questionnaire produced results which are not statistically different from results based on the original design in 2004. The use of the redesigned questionnaire is also cost-efficient.

A round table discussion was held for the 2008 APIS before the conduct of the pretest. The redesigned APIS questionnaire based from the project's output was presented. It was agreed upon during this meeting to adopt the redesigned APIS for this round of APIS, with the addition of item on 'Hunger'.

Cleaning operations

Flow of Processing Activity

In order to implement a systematic flow of the processing activities and reduce the movement of questionnaires from one employee to another, the same processor performed the following specific activities for the same folio. 1. General screening; 2. Editing and coding of APIS questionnaires and computations of totals ; and 3. General review of edited APIS questionnaire.

Folioing

To facilitate handling during manual and machine processing, APIS questionnaires were folioed in the Provincial Office before the start of manual processing.

The APIS questionnaires for one sample barangay/EA contained in the folio was arranged consecutively according to the sample housing serial number (SHSN) from lowest to highest.

General Screening

General screening was done by going over the submitted accomplished questionnaires and checking for the completeness of the geographic identification and other information called for in the cover page.

General screening for APIS questionnaires was done to ensure that the geographic and household identification and the entire sample households are the same with the MS Form 6.

General Instructions on Manual Processing

The following instructions was observed in manual processing.

1. Prior to editing and coding of items, the questionnaires were checked if they were properly folioed. Folioing was done in the province. Regional Offices checked if folioing was done properly by the Provincial Offices.

2. All questionnaires for one folio was assigned to only one editor/coder, unless otherwise necessary (e.g., when the one who is processing a folio is absent for more than a day).

3. In general, the editors assumed that the original entries are correct. Editing was done only when an entry is obviously incorrect. A doubtful or inconsistent item was verified in the field.

Response rate

Of the 43,020 eligible sample households for the 2008 APIS, 40,613 were successfully interviewed. This translated to a response rate of 94.4 percent at the national level. Households which were not interviewed either refused to be interviewed or were not available or were away during the enumeration period.

Sampling error estimates

Sampling errors have been calculated for the following variables: 1) Percentage of Families with Own or Ownerlike Possession of House and Lot they Occupy 2) Percentage of Families Living in Houses with Roof Made of Strong Materials 3) Percentage of Families Living in Houses with Outer Walls Made of Strong Materials 4) Percentage of Families with Electricity in the Building/House They Reside in 5) Percentage of Families with Access to Safe Water Supply 6) Percentage of Families with Sanitary Toilet 7) Percentage of Families with Children 6-12 Years Old in Elementary Grades 8) Percentage of Families with Children 13-16 Years Old in High School 9) Percentage of Families with Members 18 Years Old and Over Gainfully Employed 10) Percentage of Families with Working Children 5-17 Years Old 11) Average Family Income 12) Average Family Expenditure

Data appraisal

A series of data quality tables were generated to review the quality of the data and include the following: - Age distribution of the household population - Highest grade completed versus current grade - Highest grade completed versus age - Current grade versus age - Reason for not attending school versus highest grade completed - Reason for not attending school versus current grade - Marital status versus age - Consistency of income vs. expenditure

Number of poor at $3.2 a day of Philippines sank by 30.53% from 26.2 million persons in 2015 to 18.2 million persons in 2018. Since the 2.87% upward trend in 2012, number of poor at $3.2 a day plummeted by 43.65% in 2018. Number of people living on less than $3.20 a day at 2011 international prices. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).

Philippines Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 5.800 % in 2017. Philippines Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 5.800 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 5.800 % in 2017 and a record low of 5.800 % in 2017. Philippines Multidimensional Poverty Headcount Ratio: UNDP: % of total population 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 multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

The share of the urban population in the Philippines has continued to rise over the years. In 2024, the urban population accounted for roughly 48.61 percent of the entire population. In the Philippines, urbanized areas were primarily found in Metro Manila, located in the National Capital Region (NCR). Urban population growth in the Philippines Urban areas in the Philippines have a high influx of people due to better infrastructure and employment opportunities available. From 2011 to 2015, the urban population growth rate was over two percent. However, from 2016 to 2020, the population growth rate decreased and has been at around 1.9 percent since the Philippine government introduced the “Back to the Province” program to reduce overcrowding in Manila. Lack of affordable housing in the urbanized areas of the Philippines Poverty has been one of the reasons for slum dwellings in the Philippines. Despite better infrastructure in urban areas, there is also a lack of affordable housing for people living below the poverty level in urban areas. As a result, 43 percent of the urban population lives in slums in the Philippines, one of the highest urban populations living in slums across the Asia Pacific.

The share of the urban population in the Philippines has continued to rise over the years. In 2022, the urban population accounted for roughly 48 percent of the entire population. In the Philippines, urbanized areas were primarily found in Metro Manila, located in the National Capital Region (NCR).

 Urban population growth in the Philippines

Urban areas in the Philippines have a high influx of people due to better infrastructure and employment opportunities available. From 2011 to 2015, the urban population growth rate was over two percent. However, from 2016 to 2020, the population growth rate decreased and has been at around 1.9 percent since the Philippine government introduced “Back to the Province” program to reduce overcrowding in Manila.

Lack of affordable housing in the urbanized areas in the Philippines

Poverty has been one of the reasons for slum dwellings in the Philippines. Despite better infrastructures in urban areas, there is also a lack of affordable housing for people living below the poverty level in urban areas. As a result, 43 percent of the urban population live in slums in the Philippines, one of the highest urban population living in slums across the Asia Pacific.

Philippines PH: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 33.700 % in 2015. This records a decrease from the previous number of 38.700 % for 2012. Philippines PH: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 43.100 % from Dec 1985 (Median) to 2015, with 11 observations. The data reached an all-time high of 57.600 % in 1985 and a record low of 33.700 % in 2015. Philippines PH: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population 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: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 4.100 % in 2021. This records a decrease from the previous number of 4.400 % for 2018. Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 6.500 % from Dec 2012 (Median) to 2021, with 4 observations. The data reached an all-time high of 13.600 % in 2012 and a record low of 4.100 % in 2021. Multidimensional Poverty Headcount Ratio: World Bank: % of total population 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 multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;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 PH: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data was reported at 8.300 % in 2015. This records a decrease from the previous number of 12.100 % for 2012. Philippines PH: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data is updated yearly, averaging 14.700 % from Dec 1985 (Median) to 2015, with 11 observations. The data reached an all-time high of 28.100 % in 1985 and a record low of 8.300 % in 2015. Philippines PH: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population 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: Poverty. Poverty headcount ratio at $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Climate change and its associated shocks have a disproportionate adverse impact on the poor and most vulnerable. Poor and vulnerable families, especially those living near or within the areas with high exposure to risks and that are isolated from markets and social services, are less prepared to respond to and cope with shocks. Affected households with limited or no income/assets often resort to negative coping strategies, such as selling assets like farm animals or farmlands, taking their children off from school, reducing their food intake, selling their farm inputs or small farms, and migrate to urban centers to find jobs, some resulting to furthervulnerability and risks. Almost half a million Filipinos are estimated to annually face transient consumption poverty as a result of natural disasters, and poverty increases vulnerability to adverse natural events. The climate vulnerable population is bigger than the income poor population, with over a third of non-poor households in most provinces along the Eastern Seaboard being at risk of poverty in the case of a typhoon.

Abstract

The 2003 Family Income and Expenditure Survey (FIES) had the following primary objectives:

1) to gather data on family income and family expenditure and related information affecting income and expenditure levels and patterns in the Philippines;

2) to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

3) to provide benchmark information to update weights for the estimation of consumer price index; and

4) to provide information for the estimation of the country's poverty threshold and incidence.

Geographic coverage

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 2003 FIES has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2003 MS considers the country's 17 administrative regions as defined in Executive Orders (EO) 36 and 131 as the sampling domains. A domain is referred to as a subdivision of the country for which estimates with adequate level of precision are generated. It must be noted that while there is demand for data at the provincial level (and to some extent municipal and barangay levels), the provinces were not treated as sampling domains because there are more than 80 provinces which would entail a large resource requirement. Below are the 17 administrative regions of the country:

National Capital Region Cordillera Administrative Region Region I - Ilocos Region II - Cagayan Valley Region III - Central Luzon Region IVA - CALABARZON Region IVB - MIMAROPA Region V - Bicol Region VI - Western Visayas Region VII - Central Visayas Region VIII - Eastern Visayas Region IX - Zamboanga Peninsula Region X - Northern Mindanao Region XI - Davao Region XII - SOCCSKSARGEN Region XIII - Caraga Autonomous Region in Muslim Mindanao

As in most household surveys, the 2003 MS made use of an area sample design. For this purpose, the Enumeration Area Reference File (EARF) of the 2000 Census of Population and Housing (CPH) was utilized as sampling frame. The EARF contains the number of households by enumeration area (EA) in each barangay.

This frame was used to form the primary sampling units (PSUs). With consideration of the period for which the 2003 MS will be in use, the PSUs were formed/defined as a barangay or a combination of barangays with at least 500 households.

The 2003 MS considers the 17 regions of the country as the primary strata. Within each region, further stratification was performed using geographic groupings such as provinces, highly urbanized cities (HUCs), and independent component cities (ICCs). Within each of these substrata formed within regions, the PSUs were further stratified, to the extent possible, using the proportion of strong houses (PSTRONG), indicator of engagement in agriculture of the area (AGRI), and a measure of per capita income (PERCAPITA) as stratification factors.

The 2003 MS consists of a sample of 2,835 PSUs. The entire MS was divided into four sub-samples or independent replicates, such as a quarter sample contains one fourth of the total PSUs; a half sample contains one-half of the four sub-samples or equivalent to all PSUs in two replicates.

The final number of sample PSUs for each domain was determined by first classifying PSUs as either self-representing (SR) or non-self-representing (NSR). In addition, to facilitate the selection of sub-samples, the total number of NSR PSUs in each region was adjusted to make it a multiple of 4.

SR PSUs refers to a very large PSU in the region/domain with a selection probability of approximately 1 or higher and is outright included in the MS; it is properly treated as a stratum; also known as certainty PSU. NSR PSUs refers to a regular too small sized PSU in a region/domain; also known as non-certainty PSU. The 2003 MS consists of 330 certainty PSUs and 2,505 non-certainty PSUs.

To have some control over the sub-sample size, the PSUs were selected with probability proportional to some estimated measure of size. The size measure refers to the total number of households from the 2000 CPH. Because of the wide variation in PSU sizes, PSUs with selection probabilities greater than 1 were identified and were included in the sample as certainty selections.

At the second stage, enumeration areas (EAs) were selected within sampled PSUs, and at the third stage, housing units were selected within sampled EAs. Generally, all households in sampled housing units were enumerated, except for few cases when the number of households in a housing unit exceeds three. In which case, a sample of three households in a sampled housing unit was selected at random with equal probability.

An EA is defined as an area with discernable boundaries within barangays consisting of about 150 contiguous households. These EAs were identified during the 2000 CPH. A housing unit, on the other hand, is a structurally separate and independent place of abode which, by the way it has been constructed, converted, or arranged, is intended for habitation by a household.

The 2003 FIES involved the interview of a national sample of about 51,000 sample households deemed sufficient to gather data on family income and family expenditure and related information affecting income and expenditure levels and patterns in the Philippines at the national and regional level. The sample households covered in the survey were the same households interviewed in the July 2003 and January 2004 round of the LFS.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The 2003 FIES questionnaire contains about 800 data items and a summary for comparing income and expenditures. The questionnaires were subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency.

The major steps in the machine processing are as follows: 1. Data Entry 2. Completeness Check 3. Matching of visit records 4. Consistency and Macro Edit (Big Edit) 5. Generation of the Public Use File 6. Tabulation

Steps 1 to 2 were done right after each visit. The remaining steps were carried out only after the second visit had been completed.

Steps 1 to 4 were done at the Regional Office while Steps 5 and 6 were completed in the Central Office.

After completing Steps 1 to 4, data files were transmitted to the Central Office where a summary file was generated. The summary file was used to produce the consistency tables as well as the preliminary and textual tables.

When the generated tables showed inconsistencies, selected data items were subjected to further scrutiny and validation. The cycle of generation of consistency tables and data validation were done until questionable data items were verified.

The FAME (FIES computer-Aided Consistency and Macro Editing), an interactive Windows-based application system was used in data processing. This system was used starting with the 2000 FIES round. The interactive module of FAME enabled the following activities to be done simultaneously. a) Matching of visit records b) Consistency and macro edit (big edit) c) Range check

The improved system minimized processing time as well as minimized, if not eliminated, the need for paper to generate the reject listing.

Note: For data entry, CSPro Version 2.6 was used.

Response rate

The response rate for this survey is 95.7%. The response rate is the ratio of the total responding households to the total number of eligible households. Eligible households include households who were completely interviewed, refused to be interviewed or were temporarily away or not at home or on vacation during the survey period.

Sampling error estimates

As in all surveys, two types of non-response were encountered in the 2003 FIES: interview non-response and item non-response. Interview non-response refers to a sample household that could not be interviewed. Since the survey requires that the sample households be interviewed in both visits, households that transferred to another dwelling unit, temporarily away, on vacation, not at home, household unit demolished, destroyed by fire/typhoon and refusal to be interviewed in the second visit contributed to the number of interview non-response cases.

Item non-response, or the failure to obtain responses to particular survey items, resulted from factors such as respondents being unaware of the answer to a particular question, unwilling to provide the requested information or ENs’ omission of questions during the interview. Deterministic imputation was done to address item nonresponse. This imputation is a process in which proper entry for a particular missing item was deduced from other items of the questionnaire where the non-response item was observed. Notes and remarks indicated in the questionnaire were likewise used as basis for imputation.

Data appraisal

Refer to the

Philippines PH: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 64.200 % in 2015. This records a decrease from the previous number of 67.000 % for 2012. Philippines PH: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 69.200 % from Dec 1985 (Median) to 2015, with 11 observations. The data reached an all-time high of 82.700 % in 1985 and a record low of 64.200 % in 2015. Philippines PH: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population 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: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.