100+ datasets found
  1. Poverty incidence among families Philippines 2015-2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 26, 2025
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    Statista (2025). Poverty incidence among families Philippines 2015-2023 [Dataset]. https://www.statista.com/statistics/1321266/philippines-poverty-incidence-of-families/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    Based on preliminary results in 2023, the proportion of families in the Philippines with income below the poverty threshold was estimated at **** percent, lower than the estimate for 2018. In that year, the average per capita food threshold reached ****** Philippine pesos.

  2. School Neighborhood Poverty Estimates, 2015-16

    • catalog.data.gov
    • s.cnmilf.com
    Updated Oct 21, 2024
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    National Center for Education Statistics (NCES) (2024). School Neighborhood Poverty Estimates, 2015-16 [Dataset]. https://catalog.data.gov/dataset/school-neighborhood-poverty-estimates-2015-2016-01098
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    The 2015-2016 School Neighborhood Poverty Estimates are based on school locations from the 2015-2016 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2012-2016 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools. All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

  3. Urban poverty line in Indonesia 2015-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jul 9, 2025
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    Statista (2025). Urban poverty line in Indonesia 2015-2024 [Dataset]. https://www.statista.com/statistics/867672/indonesia-urban-poverty-line/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Indonesia
    Description

    In 2024, Indonesia had an urban poverty line of approximately ******* Indonesian rupiah per month, indicating a constant increase since 2015. The poverty line is the minimum amount of income needed for day to day necessities.

  4. o

    Poverty in Laos by province 2015 - Dataset OD Mekong Datahub

    • data.opendevelopmentmekong.net
    Updated Jan 9, 2019
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    (2019). Poverty in Laos by province 2015 - Dataset OD Mekong Datahub [Dataset]. https://data.opendevelopmentmekong.net/dataset/poverty-in-laos-by-province-2015
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    Dataset updated
    Jan 9, 2019
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Laos
    Description

    This dataset displays under indicators of poverty, namely density, % urban population, poverty headcount, poverty gap, poverty severity, access to sanitation, water, electricity, telephone of Laos at provincial administrative level. This data is based on population and housing census 2015.

  5. d

    Poverty rate - ACS 2015-2019 - Tempe Tracts

    • catalog.data.gov
    • performance.tempe.gov
    • +4more
    Updated Sep 20, 2024
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    City of Tempe (2024). Poverty rate - ACS 2015-2019 - Tempe Tracts [Dataset]. https://catalog.data.gov/dataset/poverty-rate-acs-2015-2019-tempe-tracts-3b34b
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    Dataset updated
    Sep 20, 2024
    Dataset provided by
    City of Tempe
    Description

    Notice: The U.S. Census Bureau is delaying the release of the 2016-2020 ACS 5-year data until March 2022. For more information, please read the Census Bureau statement regarding this matter. -----------------------------------------This layer shows poverty status by age group. This layer is Census data from Esri's Living Atlas and is clipped to only show Tempe census tracts. This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online).Data is from US Census American Community Survey (ACS) 5-year estimates. Vintage: 2015-2019 ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.) Data downloaded from: Census Bureau's API for American Community Survey Date of Census update: December 10, 2020 National Figures: data.census.gov Additional Census data notes and data processing notes are available at the Esri Living Atlas Layer: https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)

  6. c

    Poverty Rate

    • data.ccrpc.org
    csv
    Updated Oct 17, 2024
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    Champaign County Regional Planning Commission (2024). Poverty Rate [Dataset]. https://data.ccrpc.org/dataset/poverty-rate
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    csv(393)Available download formats
    Dataset updated
    Oct 17, 2024
    Dataset provided by
    Champaign County Regional Planning Commission
    Description

    This poverty rate data shows what percentage of the measured population* falls below the poverty line. Poverty is closely related to income: different “poverty thresholds” are in place for different sizes and types of household. A family or individual is considered to be below the poverty line if that family or individual’s income falls below their relevant poverty threshold. For more information on how poverty is measured by the U.S. Census Bureau (the source for this indicator’s data), visit the U.S. Census Bureau’s poverty webpage.

    The poverty rate is an important piece of information when evaluating an area’s economic health and well-being. The poverty rate can also be illustrative when considered in the contexts of other indicators and categories. As a piece of data, it is too important and too useful to omit from any indicator set.

    The poverty rate for all individuals in the measured population in Champaign County has hovered around roughly 20% since 2005. However, it reached its lowest rate in 2021 at 14.9%, and its second lowest rate in 2023 at 16.3%. Although the American Community Survey (ACS) data shows fluctuations between years, given their margins of error, none of the differences between consecutive years’ estimates are statistically significant, making it impossible to identify a trend.

    Poverty rate data was sourced from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

    As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

    Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

    For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Poverty Status in the Past 12 Months by Age.

    *According to the U.S. Census Bureau document “How Poverty is Calculated in the ACS," poverty status is calculated for everyone but those in the following groups: “people living in institutional group quarters (such as prisons or nursing homes), people in military barracks, people in college dormitories, living situations without conventional housing, and unrelated individuals under 15 years old."

    Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (16 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).

  7. P

    Philippines Incidence of Poor Families: Cagayan Valley

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Philippines Incidence of Poor Families: Cagayan Valley [Dataset]. https://www.ceicdata.com/en/philippines/family-income-and-expenditure-survey-poverty-statistics-and-proportion-of-poor-population-by-regions/incidence-of-poor-families-cagayan-valley
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1988 - Dec 1, 2015
    Area covered
    Philippines
    Variables measured
    Household Income and Expenditure Survey
    Description

    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.

  8. Poverty headcount ratio in Venezuela 2015

    • statista.com
    • ai-chatbox.pro
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    Statista, Poverty headcount ratio in Venezuela 2015 [Dataset]. https://www.statista.com/statistics/818416/poverty-headcount-ratio-in-venezuela/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005 - 2015
    Area covered
    Venezuela
    Description

    The poverty headcount ratio at national poverty lines in Venezuela increased by 3.6 percentage points (+12.2 percent) compared to the previous year. In total, the poverty headcount ratio amounted to 33.1 percent in 2015. The poverty headcount ratio at national poverty lines refers to the share of the population living in poverty, based on parameters set by local, regional, or national governments.

  9. P

    Philippines Incidence of Poor Population: Northern Mindanao

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Philippines Incidence of Poor Population: Northern Mindanao [Dataset]. https://www.ceicdata.com/en/philippines/family-income-and-expenditure-survey-poverty-statistics-and-proportion-of-poor-population-by-regions/incidence-of-poor-population-northern-mindanao
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1988 - Dec 1, 2015
    Area covered
    Philippines
    Variables measured
    Household Income and Expenditure Survey
    Description

    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.

  10. o

    Armenia - National Multidimensional Poverty Index 2010 - 2015 - Dataset -...

    • data.opendata.am
    Updated Jul 7, 2023
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    (2023). Armenia - National Multidimensional Poverty Index 2010 - 2015 - Dataset - Data Catalog Armenia [Dataset]. https://data.opendata.am/dataset/dcwb0047346
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    Dataset updated
    Jul 7, 2023
    Area covered
    Armenia
    Description

    The most recent estimate of monetary poverty in Armenia found that nearly 30 percent of the population lives below the national poverty threshold. However, because the Armenian social protection system provides some, though limited, basic support, monetary measures provide only a partial picture of the negative effects of poverty on well-being and the lack of positive capabilities.In 2013, the National Statistical Service of the Republic of Armenia and the World Bank began work on a national measure of multidimensional poverty to supplement the consumption poverty indicator. This measure, which was identified through consultations with many stakeholders in Armenia, reflects deprivations specific to Armenia in the areas of education, health, labor, housing conditions, and basic needs. The approach offers insights into the complexity, depth, and persistence of poverty in the country; tailoring it specifically to the country context enhances its relevance for policy.The national measure of multidimensional poverty for Armenia uses the Alkire-Foster approach.This tailored measure is not intended to be used in international comparisons; it is simply representative of the country and its specific development challenges. For every multidimensional measure, the dimensions, weights, and a method for aggregation must be selected.The first step in constructing the measure of multidimensional poverty is to select dimensions that reflect achievements or deprivations. These indicators complement the national monetary poverty measure with information that better captures nonmonetary aspects of well-being. The primary dimensions of the measure are basic needs, housing, education, labor, and health.The datasets documented here include 2010-2015 national multidimensional poverty indices, constructed using Armenia Integrated Living Conditions Survey (ILCS) data from 2010 to 2015.

  11. w

    NYCgov Poverty Measure Data (2015)

    • data.wu.ac.at
    csv, json, rdf, xml
    Updated May 2, 2018
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    City of New York (2018). NYCgov Poverty Measure Data (2015) [Dataset]. https://data.wu.ac.at/schema/data_gov/ZDk2YmMxYmYtYmM1MS00NDZkLTg3MTAtN2ZjNTM0Mzk0YTMy
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    rdf, xml, csv, jsonAvailable download formats
    Dataset updated
    May 2, 2018
    Dataset provided by
    City of New York
    Description

    merican Community Survey Public Use Micro Sample, augmented by NYC Opportunity.

    This file contains poverty rates and related data from the NYCgov poverty measure data. The NYCgov poverty measure is generated annually by the poverty research unit of the Mayor's Office of Economic Opportunity (NYC Opportunity). The data is derived from the American Community Survey Public Use Microsample for NYC, augmented by NYC Opportunity to include imputed estimates for benefit participation and some household expenditures. For information on how the NYCgov poverty rate is constructed see http://www1.nyc.gov/site/opportunity/poverty-in-nyc/poverty-measure.page.

    DISCLAIMER: Do not use the visualization tool with this data set. This data set is unweighted. See “Read Me” page in data dictionary for correct use of person and household weights. Visualizations generated from this file will result in incorrect distributions of the data.

    For the list of all NYCgov Poverty Measure Data datasets available on the portal please use this link.

  12. Annual fuel poverty statistics report: 2015

    • gov.uk
    Updated May 28, 2015
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    Department of Energy & Climate Change (2015). Annual fuel poverty statistics report: 2015 [Dataset]. https://www.gov.uk/government/statistics/annual-fuel-poverty-statistics-report-2015
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    Dataset updated
    May 28, 2015
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department of Energy & Climate Change
    Description

    The fuel poverty statistics report for 2015 includes:

    • the latest statistics on the number of households living in fuel poverty, in England
    • analysis of the composition of the fuel poor group in 2013
    • projections of the number of households in fuel poverty in 2014 and 2015
    • estimates of sub-regional fuel poverty
  13. a

    2015 Population and Poverty at Split Tract

    • hub.arcgis.com
    Updated May 7, 2024
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    County of Los Angeles (2024). 2015 Population and Poverty at Split Tract [Dataset]. https://hub.arcgis.com/maps/lacounty::2015-population-and-poverty-at-split-tract/about
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    Dataset updated
    May 7, 2024
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2015 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP15: 2015 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2015) CT10FIP15: 2010 census tract with 2015 city FIPs for incorporated cities and unincorporated areas. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP15_AGE_0_4: 2015 population 0 to 4 years oldPOP15_AGE_5_9: 2015 population 5 to 9 years old POP15_AGE_10_14: 2015 population 10 to 14 years old POP15_AGE_15_17: 2015 population 15 to 17 years old POP15_AGE_18_19: 2015 population 18 to 19 years old POP15_AGE_20_44: 2015 population 20 to 24 years old POP15_AGE_25_29: 2015 population 25 to 29 years old POP15_AGE_30_34: 2015 population 30 to 34 years old POP15_AGE_35_44: 2015 population 35 to 44 years old POP15_AGE_45_54: 2015 population 45 to 54 years old POP15_AGE_55_64: 2015 population 55 to 64 years old POP15_AGE_65_74: 2015 population 65 to 74 years old POP15_AGE_75_84: 2015 population 75 to 84 years old POP15_AGE_85_100: 2015 population 85 years and older POP15_WHITE: 2015 Non-Hispanic White POP15_BLACK: 2015 Non-Hispanic African AmericanPOP15_AIAN: 2015 Non-Hispanic American Indian or Alaska NativePOP15_ASIAN: 2015 Non-Hispanic Asian POP15_HNPI: 2015 Non-Hispanic Hawaiian Native or Pacific IslanderPOP15_HISPANIC: 2015 HispanicPOP15_MALE: 2015 Male POP15_FEMALE: 2015 Female POV15_WHITE: 2015 Non-Hispanic White below 100% Federal Poverty Level POV15_BLACK: 2015 Non-Hispanic African American below 100% Federal Poverty Level POV15_AIAN: 2015 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV15_ASIAN: 2015 Non-Hispanic Asian below 100% Federal Poverty Level POV15_HNPI: 2015 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV15_HISPANIC: 2015 Hispanic below 100% Federal Poverty Level POV15_TOTAL: 2015 Total population below 100% Federal Poverty Level POP15_TOTAL: 2015 Total PopulationAREA_SQMIL: Area in square milePOP15_DENSITY: Population per square mile.POV15_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2015. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

  14. A

    ‘Poverty rate - ACS 2015-2019 - Tempe Tracts’ analyzed by Analyst-2

    • analyst-2.ai
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com), ‘Poverty rate - ACS 2015-2019 - Tempe Tracts’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-poverty-rate-acs-2015-2019-tempe-tracts-b30d/9669fef9/?iid=001-957&v=presentation
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    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Poverty rate - ACS 2015-2019 - Tempe Tracts’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/65c43ceb-ca8c-49b7-a222-df271a777135 on 11 February 2022.

    --- Dataset description provided by original source is as follows ---

    Notice: The U.S. Census Bureau is delaying the release of the 2016-2020 ACS 5-year data until March 2022. For more information, please read the Census Bureau statement regarding this matter.

    -----------------------------------------

    This layer shows poverty status by age group. This layer is Census data from Esri's Living Atlas and is clipped to only show Tempe census tracts.


    This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online).


    Data is from US Census American Community Survey (ACS) 5-year estimates.


    Vintage: 2015-2019

    ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.)

    Data downloaded from: Census Bureau's API for American Community Survey

    Date of Census update: December 10, 2020

    National Figures: data.census.gov


    Additional Census data notes and data processing notes are available at the Esri Living Atlas Layer:

    https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)

    --- Original source retains full ownership of the source dataset ---

  15. a

    Persistent Poverty - County

    • usfs.hub.arcgis.com
    Updated Sep 30, 2022
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    U.S. Forest Service (2022). Persistent Poverty - County [Dataset]. https://usfs.hub.arcgis.com/maps/usfs::persistent-poverty-county
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    Dataset updated
    Sep 30, 2022
    Dataset authored and provided by
    U.S. Forest Service
    Area covered
    Description

    Unpublished data product not for circulation Persistent Poverty tracts*Persistent poverty area and enduring poverty area measures with reference year 2015-2019 are research measures only. The ERS offical measures are updated every ten years. The next updates will use 1960 through 2000 Decennial Census data and 2007-2011 and 2017-2021 5-year ACS estimates. The updates will take place following the Census Bureau release of the 2017-2021 estimates (anticipated December 2022).A reliability index is calculated for each poverty rate (PctPoor) derived using poverty count estimates and published margins of error from the 5-yr ACS. If the poverty rate estimate has low reliability (=3) AND the upper (PctPoor + derived MOE) or lower (PctPoor - derived MOE) bounds of the MOE adjusted poverty rate would change the poverty status of the estimate (high = 20.0% or more; extreme = 40.0% or more) then the county/tract type is coded as "N/A". If looking at metrics named "PerPov0711" and PerPov1519" ERS says: The official measure ending in 2007-11 included data from 1980. The research measure ending in 2015-19 drops 1980 and begins instead with 1990. There were huge differences in geographic coverage of census tracts and data quality between 1980 and 1990, namely "because tract geography wasn’t assigned to all areas of the country until the 1990 Decennial Census. Last date edited 9/1/2022Variable NamesVariable Labels and ValuesNotesGeographic VariablesGEO_ID_CTCensus download GEOID when downloading county and tract data togetherSTUSABState Postal AbbreviationfipsCounty FIPS code, in numericCountyNameArea Name (county, state)TractNameArea Name (tract, county, state)TractCensus Tract numberRegionCensus region numeric code 1 = Northeast 2 = Midwest 3 = South 4 = Westsubreg3ERS subregions 1 = Northeast and Great Lakes 2 = Eastern Metropolitan Belt 3 = Eastern and Interior Uplands 4 = Corn Belt 5 = Southeastern Coast 6 = Southern Coastal Plain 7 = Great Plains 8 = Rio Grande and Southwest 9 = West, Alaska and HawaiiMetNonmet2013Metro and nonmetro county code 0 = nonmetro county 1 = metro countyBeale2013ERS Rural-urban Continuum Code 2013 (counties) 1 = counties in metro area of 1 million population or more 2 = counties in metro area of 250,000 to 1 million population 3 = counties in metro area of fewer than 250,000 population 4 = urban population of 20,000 or more, adjacent to a metro area 5 = urban population of 20,000 or more, not adjacent to a metro area 6 = urban population of 2,500 to 19,999, adjacent to a metro area 7 = urban population of 2,500 to 19,999, not adjacent to a metro area 8 = completely rural or less than 2,500, adjacent to a metro area 9 = completely rural or less than 2,500, not adjacent to a metro areaRUCA_2010Rural Urban Commuting Areas, primary code (census tracts) 1 = Metropolitan area core: primary flow within an urbanized area (UA) 2 = Metropolitan area high commuting: primary flow 30% or more to a UA 3 = Metropolitan area low commuting: primary flow 10% to 30% to a UA 4 = Micropolitan area core: primary flow within an Urban Cluster of 10,000 to 49,999 (large UC) 5 = Micropolitan high commuting: primary flow 30% or more to a large UC 6 = Micropolitan low commuting: primary flow 10% to 30% to a large UC 7 = Small town core: primary flow within an Urban Cluster of 2,500 to 9,999 (small UC) 8 = Small town high commuting: primary flow 30% or more to a small UC 9 = Small town low commuting: primary flow 10% to 30% to a small UC 10 = Rural areas: primary flow to a tract outside a UA or UC 99 = Not coded: Census tract has zero population and no rural-urban identifier informationBNA01Census tract represents block numbering areas; BNAs are small statistical subdivisions of a county for numbering and grouping blocks in nonmetropolitan counties where local committees have not established tracts. 0 = not a BNA tract 1 = BNA tractPoverty Areas MeasuresHiPov60Poverty Rate greater than or equal to 20.0% 1960 (counties only) -1 = N/A 0 = PctPoor60 < 20.0% 1 = PctPoor60 >= 20.0%HiPov70Poverty Rate greater than or equal to 20.0% 1970 -1 = N/A 0 = PctPoor70 < 20.0% 1 = PctPoor70 >= 20.0%HiPov80Poverty Rate greater than or equal to 20.0% 1980 -1 = N/A 0 = PctPoor80 < 20.0% 1 = PctPoor80 >= 20.0%HiPov90Poverty Rate greater than or equal to 20.0% 1990 -1 = N/A 0 = PctPoor90 < 20.0% 1 = PctPoor90 >= 20.0%HiPov00Poverty Rate greater than or equal to 20.0% 2000 -1 = N/A 0 = PctPoor00 < 20.0% 1 = PctPoor00 >= 20.0%HiPov0711Poverty Rate greater than or equal to 20.0% 2007-11 ACS -1 = N/A 0 = PctPoor0711 < 20.0% 1 = PctPoor0711 >= 20.0%HiPov1519Poverty Rate greater than or equal to 20.0% 2015-19 ACS -1 = N/A 0 = PctPoor1519 < 20.0% 1 = PctPoor1519 >= 20.0%ExtPov60Poverty Rate greater than or equal to 40.0% 1960 (counties only) -1 = N/A 0 = PctPoor60 < 40.0% 1 = PctPoor60 >= 40.0%ExtPov70Poverty Rate greater than or equal to 40.0% 1970 -1 = N/A 0 = PctPoor70 < 40.0% 1 = PctPoor70 >= 40.0%ExtPov80Poverty Rate greater than or equal to 40.0% 1980 -1 = N/A 0 = PctPoor80 < 40.0% 1 = PctPoor80 >= 40.0%ExtPov90Poverty Rate greater than or equal to 40.0% 1990 -1 = N/A 0 = PctPoor90 < 40.0% 1 = PctPoor90 >= 40.0%ExtPov00Poverty Rate greater than or equal to 40.0% 2000 -1 = N/A 0 = PctPoor00 < 40.0% 1 = PctPoor00 >= 40.0%ExtPov0711Poverty Rate greater than or equal to 40.0% 2007-11 ACS -1 = N/A 0 = PctPoor0711 < 40.0% 1 = PctPoor0711 >= 40.0%ExtPov1519Poverty Rate greater than or equal to 40.0% 2015-19 ACS -1 = N/A 0 = PctPoor1519 < 40.0% 1 = PctPoor1519 >= 40.0%PerPov90Official ERS Measure: Persistent Poverty 1990: poverty rate >= 20.0% in 1960, 1970, 1980, and 1990 (counties only) May not match previously published versions due to changes in geographic normalization procedures. -1 = N/A 0 = poverty rate not >= 20.0% in 1960, 1970, 1980, and 1990 1 = poverty rate >= 20.0% in 1960, 1970, 1980, and 1990PerPov00Official ERS Measure: Persistent Poverty 2000: poverty rate >= 20.0% in 1970, 1980, 1990, and 2000May not match previously published versions due to changes in geographic normalization procedures. -1 = N/A 0 = poverty rate not >= 20.0% in 1970, 1980, 1990, and 2000 1 = poverty rate >= 20.0% in 1970, 1980, 1990, and 2000PerPov0711Official ERS Measure: Persistent Poverty 2007-11: poverty rate >= 20.0% in 1980, 1990, 2000, and 2007-11May not match previously published versions due to changes in geographic normalization procedures and -1 = N/A application of reliability criteria. 0 = poverty rate not >= 20.0% in 1980, 1990, 2000, and 2007-11 1 = poverty rate >= 20.0% in 1980, 1990, 2000, and 2007-11PerPov1519Research Measure Only: Persistent Poverty 2015-19: poverty rate >= 20.0% in 1990, 2000, 2007-11, and 2015May not match previously published versions due to changes in geographic normalization procedures and -1 = N/A application of reliability criteria. 0 = poverty rate not >= 20.0% in 1990, 2000, 2007-11, and 2015-19 1 = poverty rate >= 20.0% in 1990, 2000, 2007-11, and 2015-19EndurePov0711Official ERS Measure: Enduring Poverty 2007-11: poverty rate >= 20.0% for at least 5 consecutive time periods up-to and including 2007-11 -1 = N/A 0 = Poverty Rate not >=20.0% in 1970, 1980, 1990, 2000, and 2007-11 1 = poverty rate >= 20.0% in 1970, 1980, 1990, 2000, and 2007-11 2 = poverty rate >=20.0% in 1960, 1970, 1980, 1990, 2000, and 2007-11 (counties only)EndurePov1519Research Measure Only: Enduring Poverty 2015-19: poverty rate >= 20.0% for at least 5 consecutive time periods, up-to and including 2015-19 -1 = N/A 0 = Poverty Rate not >=20.0% in 1980, 1990, 2000, 2007-11, and 2015-19 1 = poverty rate >= 20.0% in 1980, 1990, 2000, 2007-11, and 2015-19 2 = poverty rate >= 20.0% in 1970, 1980, 1990, 2000, 2007-11, and 2015-19 3 = poverty rate >=20.0% in 1960, 1970, 1980, 1990, 2000, 2007-11, and 2015-19 (counties only)Additional Notes: *In the combined data tab each variable ends with a 'C' for county and a 'T' for tractThe spreadsheet was joined to Esri's Living Atlas Social Vulnerability Tract Data (CDC) and therefore contains the following information as well: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) has created a tool to help emergency response planners and public health officials identify and map the communities that will most likely need support before, during, and after a hazardous event. The Social Vulnerability Index (SVI) uses U.S. Census data to determine the social vulnerability of every county and tract. CDC SVI ranks each county and tract on 15 social factors, including poverty, lack of vehicle access, and crowded housing, and groups them into four related themes:SocioeconomicHousing Composition and DisabilityMinority Status and LanguageHousing and TransportationThis feature layer visualizes the 2018 overall SVI for U.S. counties and tracts. Social Vulnerability Index (SVI) indicates the relative vulnerability of every U.S. county and tract.15 social factors grouped into four major themes | Index value calculated for each county for the 15 social factors, four major themes, and the overall rank

  16. Poverty incidence among individuals Philippines 2015-2023

    • statista.com
    • ai-chatbox.pro
    Updated May 20, 2025
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    Statista (2025). Poverty incidence among individuals Philippines 2015-2023 [Dataset]. https://www.statista.com/statistics/1321274/philippines-poverty-incidence-of-individuals/
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    Dataset updated
    May 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    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.

  17. Poverty and Living Conditions Survey 2014-2015 - Myanmar

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Oct 14, 2021
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    World Bank (2021). Poverty and Living Conditions Survey 2014-2015 - Myanmar [Dataset]. https://datacatalog.ihsn.org/catalog/9739
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    Dataset updated
    Oct 14, 2021
    Dataset authored and provided by
    World Bankhttp://worldbank.org/
    Time period covered
    2015
    Area covered
    Myanmar (Burma)
    Description

    Abstract

    The MPLCS 2015 is a comprehensive study of how people in Myanmar live. It is a joint analysis conducted by a technical team from the Ministry of Planning and Finance, Government of Myanmar, and the Poverty and Equity Global Practice of the World Bank. It collects data on the occupations of people, how much income they earn, and how they use this to meet the food, housing, health, education, and other needs of their families.

    The Myanmar Poverty and Living Conditions Survey has the following objectives: - Put forward trends in poverty between 2004/05, 2009/10 and 2015 - Present a measure of poverty that reflects the situation of poverty in Myanmar in 2015 at the national, urban/rural and agro-zone - Conduct analysis about the situation and nature of poverty in Myanmar that informs policy choices and strategies.

    Geographic coverage

    National coverage. The survey is a representative of the Union Territory, four agro-zones, and urban/rural areas.

    Analysis unit

    • Households
    • Individuals
    • Agricultural parcel and crops
    • Consumption items

    Universe

    The survey covered only the usual household residents, excluding people living in hotels/motels/guesthouses, military camps, police camps, orphanages/homes for the aged, religious centers, boarding schools/colleges/universities, correctional facilities/prisons, hospitals, camps/hostels for workers, and homeless/other collective quarters.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The MPLCS sample design was developed based on the sampling frame from the April 2014 Census pre-enumeration listing data. In addition to providing statistically representative estimates at the national level, the sample was designed so that representative estimates were derived for each of four agro-ecological zones (Hills and Mountains, Dry Zone, Coastal and Delta), for the urban/rural levels overall, and specifically Yangon and surrounding area. The data are not representative at the state or region level.

    The sample primary sampling units (PSUs) for this sample are the enumeration areas (EAs) defined for the 2014 Myanmar Population and Housing Census. There are 304 EAs and 3648 sample households.

    A stratified multi-stage sample design is used for the MLPCS 2015. The stratum are agro--ecological zone and rural/urban. The classification of the EAs in the 2014 Myanmar Census of Population and Housing frame by urban and rural stratum was based on the administrative structure of the hierarchical geographic areas in Myanmar; all EAs in administrative areas defined as wards are considered urban, and all EAs in village tracks are classified as rural. The distribution of the households in the 2014 Myanmar Census of Population and Housing frame by region, urban and rural stratum, based on the preliminary Census data.

    Sampling deviation

    A total of 14 sample EAs selected for the MPLCS could not be enumerated, mostly because of security problems.

    Refer to MPLCS 2014/15 Survey Conduct and Quality Control Report.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The MPLCS questionnaire builds from earlier household expenditure and living conditions surveys conducted in Myanmar, in particular, the Integrated Household Living Conditions Assessment (IHCLA-I, 2005 and IHLCA-II, 2010) and the Household Income and Expenditure Survey (between 1989 and 2012) and WORLD BANK's LIVING STANDARD surveys. The MPLCS brings all these previous household surveys together into a single survey and provides one comprehensive source of living conditions information.

    The MPLCS 2014/2015 household questionnaire consists of 13 modules. 1. Roster 2. Education and literacy 3a. Health status 3b. Health care 4. Labor and employment 5a. International migration (current household members) 5b. Remittances (former household members and others) 6. Housing 7. Household assets/durables 8a. Household consumption in the last 7 days 8b. Non-food consumption expenditure in the last 30 days 8c. Non-food consumption expenditure in 6 and 12 months 9. Non-farm enterprises 10a. Parcel roster 10b. Inputs 10c. Labor 10d. Harvest and crop disposition 10e. Livestock 10f. Agricultural machinery and equipment 10g. Aquaculture and fisheries 11a. Loans/credit 11b. Financial inclusion 12. Food security/subjective assessment of well-being 13. Shocks and coping strategies

    Sampling error estimates

    Tables with calculated sampling errors and confidence intervals for the most important survey estimates, the different sources of non-sampling error presented in MPLCS 2015 Survey Conduct and Quality Control Report section 5.

    Data appraisal

    For detail of data quality control and measurement, see in MPLCS 2015 Survey Conduct and Quality Control Report section 3.5.

  18. P

    Philippines Incidence of Poor Families: CALABARZON

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Philippines Incidence of Poor Families: CALABARZON [Dataset]. https://www.ceicdata.com/en/philippines/family-income-and-expenditure-survey-poverty-statistics-and-proportion-of-poor-population-by-regions/incidence-of-poor-families-calabarzon
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1991 - Dec 1, 2015
    Area covered
    Philippines
    Variables measured
    Household Income and Expenditure Survey
    Description

    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.

  19. T

    Germany - At Risk of Poverty rate

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Aug 25, 2020
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    TRADING ECONOMICS (2020). Germany - At Risk of Poverty rate [Dataset]. https://tradingeconomics.com/germany/at-risk-of-poverty-rate-eurostat-data.html
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    xml, csv, json, excelAvailable download formats
    Dataset updated
    Aug 25, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Germany
    Description

    Germany - At Risk of Poverty rate was 15.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Germany - At Risk of Poverty rate - last updated from the EUROSTAT on July of 2025. Historically, Germany - At Risk of Poverty rate reached a record high of 16.70% in December of 2015 and a record low of 12.20% in December of 2005.

  20. T

    Estimate of Related Children Age 5-17 in Families in Poverty for Calcasieu...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Dec 3, 2020
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    TRADING ECONOMICS (2020). Estimate of Related Children Age 5-17 in Families in Poverty for Calcasieu Parish, LA [Dataset]. https://tradingeconomics.com/united-states/estimate-of-related-children-age-5-17-in-families-in-poverty-for-calcasieu-parish-la-fed-data.html
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Dec 3, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Calcasieu Parish, Louisiana
    Description

    Estimate of Related Children Age 5-17 in Families in Poverty for Calcasieu Parish, LA was 8196.00000 Persons in January of 2023, according to the United States Federal Reserve. Historically, Estimate of Related Children Age 5-17 in Families in Poverty for Calcasieu Parish, LA reached a record high of 9135.00000 in January of 2015 and a record low of 6272.00000 in January of 2008. Trading Economics provides the current actual value, an historical data chart and related indicators for Estimate of Related Children Age 5-17 in Families in Poverty for Calcasieu Parish, LA - last updated from the United States Federal Reserve on July of 2025.

Share
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Statista (2025). Poverty incidence among families Philippines 2015-2023 [Dataset]. https://www.statista.com/statistics/1321266/philippines-poverty-incidence-of-families/
Organization logo

Poverty incidence among families Philippines 2015-2023

Explore at:
Dataset updated
Jun 26, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Philippines
Description

Based on preliminary results in 2023, the proportion of families in the Philippines with income below the poverty threshold was estimated at **** percent, lower than the estimate for 2018. In that year, the average per capita food threshold reached ****** Philippine pesos.

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