According to a survey conducted in June 2023, in France, around 45 percent of the respondents had financial difficulties paying for their energy expenses. Moreover, around 34 percent of those surveyed declared they had financial problems paying their rent or mortgage.

According to a survey conducted in France in March 2024, a majority of the respondents declared they changed their eating habits due to inflation. For instance, approximately one respondent out of five declared they often had given up on buying some specific food products due to lack of money. And 13 percent of the respondents even said they often would skip a meal.

Inflation was the most worrying topic worldwide as of January 2025, with one third of the respondents choosing that option. Crime and violence as well as poverty and social inequality followed behind. Moreover, following Russia's invasion of Ukraine and the war in Gaza, nine percent of the respondents were worried about military conflict between nations. Only four percent were worried about the COVID-19 pandemic, which dominated the world after its outbreak in 2020. Global inflation and rising prices Inflation rates have spiked substantially since the beginning of the COVID-19 pandemic in 2020. From 2020 to 2021, the worldwide inflation rate increased from 3.5 percent to 4.7 percent, and from 2021 to 2022, the rate increased sharply from 4.7 percent to 8.7 percent. While rates are predicted to fall come 2025, many are continuing to struggle with price increases on basic necessities. Poverty and global development Poverty and social inequality was the third most worrying issue to respondents. While poverty and inequality are still prominent, global poverty rates have been on a steady decline over the years. In 1994, 64 percent of people in low-income countries and around one percent of people in high-income countries lived on less than 2.15 U.S. dollars per day. By 2018, this had fallen to almost 44 percent of people in low-income countries and 0.6 percent in high-income countries. Moreover, fewer people globally are dying of preventable diseases and people are living longer lives. Despite these aspects, issues such as wealth inequality have global prominence.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Abstract of associated article: Increasing the independence of a central bank from political influence, although ex-ante socially beneficial and initially successful in reducing inflation, would ultimately fail to lower inflation permanently. The smaller anticipated policy distortions implemented by a more independent central bank would induce the fiscal authority to decrease current distortions by increasing the deficit. Over time, inflation would increase to accommodate a higher public debt. By contrast, imposing a strict inflation target would lower inflation permanently and insulate the primary deficit from political distortions.

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Yangon, Rakhine, Shan (North), Kayin, Kachin, Shan (South), Mon, Tanintharyi, Mandalay, Kayah, Shan (East), Chin, Magway, Sagaing, Market Average

In February 2025, the average hourly earnings of all employees in the United States was at 11.24 U.S. dollars. The data have been seasonally adjusted. The deflators used for constant-dollar earnings shown here come from the Consumer Price Indexes Programs. The Consumer Price Index for All Urban Employees (CPI-U) is used to deflate the data for all employees. A comparison of the rate of wage growth versus the monthly inflation since 2020 rate can be accessed here. Real wages are wages that have been adjusted for inflation.

This measure answers the question of what number and percentage of residents are living below the federal poverty level, which means they meet certain threshold set by a set of parameters and computation performed by the Census Bureau. Following the Office of Management and Budget's (OMB) Statistical Policy Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family's total income is less than the family's threshold, then that family and every individual in it is considered in poverty. The official poverty thresholds do not vary geographically, but they are updated for inflation using the Consumer Price Index (CPI-U). The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). Data collected from the U.S. Census Bureau, American Communities Survey (1yr), Poverty Status in the Past 12 Months (Table S1701). American Communities Survey (ACS) is a survey with sampled statistics on the citywide level and is subject to a margin of error. ACS sample size and data quality measures can be found on the U.S. Census website in the Methodology section.

The Consumer Price Index gauges the price changes in a basket of goods and services in a defined time period. During August 2024, the product category with the highest Consumer Price Index (CPI) increase compared with the previous month in Argentina was household, water, electricity, gas and other fuels with a seven percent increase. Followed by education with a 6.6 percent increase. Nonetheless, when compared with the previous year, communications registered the highest price increase with over 320 percent year-over-year. The expectation of inflation Despite Argentina’s efforts to reduce inflation, the country ranks in the top three Latin American countries with the highest rate, only with a lower figure than Venezuela and Suriname. The situation is not a recent one, the inflation rate has been reaching double digits every year since 2012, reaching over 50 percent in 2019, making the constant rising prices nothing out of the ordinary for Argentinian families. The expectation of inflation is one of the main causes of inflation with low central bank interest-rates and increases in the money supply, which helps to explain the chronic inflation of the country. Both firms and people expect inflation in their lives, workers demand increasing wages to coop with inflation, while companies increase prices of goods and services because they expect production costs to grow, creating a vicious circle in the economy. Inflation and poverty Inflation negatively affects consumers and savers alike. For the latter, 100 Argentinian pesos in 2020 was worth just under 52 pesos in 2021, after adjusting for the 48.41 percent inflation rate. For the consumers, rising prices of the basic products increase the vulnerability of the population. In January 2023, the value of the basic food basket, which establishes the extreme poverty line, stood at 23,315 pesos, more than ten times higher than during the same month in 2018. Between the first half of 2018 and the first half of 2022, the share of households under the poverty line increased by over 8 percentage points reaching 27.7 percent.

Block Groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people, and are used to present data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number.This map is necessary for the CDBG team within DCA.About Poverty Data from the American Community Survey explained by SocialExplorer:Poverty statistics in American Community Survey products adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) vary by age (under 65 years or 65 years and older). The poverty thresholds for two-person families also vary by the age of the householder. If a family's total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual's total income is less than the appropriate threshold, then that individual is considered to be in poverty.In determining the poverty status of families and unrelated individuals, the Census Bureau uses thresholds (income cutoffs) arranged in a two-dimensional matrix. The matrix consists of family size (from one person to nine or more people) cross-classified by presence and number of family members under 18 years old (from no children present to eight or more children present). Unrelated individuals and two-person families are further differentiated by age of reference person (householder) (under 65 years old and 65 years old and over).

To determine a person's poverty status, one compares the person's total family income in the last 12 months with the poverty threshold appropriate for that person's family size and composition (see example below). If the total income of that person's family is less than the threshold appropriate for that family, then the person is considered "below the poverty level," together with every member of his or her family. If a person is not living with anyone related by birth, marriage, or adoption, then the person's own income is compared with his or her poverty threshold. The total number of people below the poverty level is the sum of people in families and the number of unrelated individuals with incomes in the last 12 months below the poverty threshold.

Since ACS is a continuous survey, people respond throughout the year. Because the income questions specify a period covering the last 12 months, the appropriate poverty thresholds are determined by multiplying the base-year poverty thresholds (1982) by the average of the monthly inflation factors for the 12 months preceding the data collection. See the table in Appendix A titled "Poverty Thresholds in 1982, by Size of Family and Number of Related Children Under 18 Years (Dollars)," for appropriate base thresholds. See the table "The 2012 Poverty Factors" in Appendix A for the appropriate adjustment based on interview month.

For example, consider a family of three with one child under 18 years of age, interviewed in July 2013 and reporting a total family income of $14,000 for the last 12 months (July 2012 to June 2013). The base year (1982) threshold for such a family is $7,765, while the average of the 12 inflation factors is 2.35795. Multiplying $7,765 by 2.35795 determines the appropriate poverty threshold for this family type, which is $18,309. Comparing the family's income of $14,000 with the poverty threshold shows that the family and all people in the family are considered to have been in poverty. The only difference for determining poverty status for unrelated individuals is that the person's individual total income is compared with the threshold rather than the family's income.Poverty status was determined for all people except institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years old. These groups were excluded from the numerator and denominator when calculating poverty rates.

In August 2024, the economic sector registering the most elevated inflation rate was communications, standing at 6.4 percent, trailed by housing at 4.3 percent, and home equipment at 3.3 percent when compared to the previous month.

Abstract

Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

        A dataset of monthly food price inflation estimates (aggregated for all food products available in the data) is also available for all countries covered by this modeling exercise.

Geographic coverage notes

The data cover the following sub-national areas: Kidal, Gao, Tombouctou, Bamako, Kayes, Koulikoro, Mopti, Segou, Sikasso, Market Average

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

Income, Expenditure and Consumption Surveys assume a prime importance among all household surveys undertaken by the national statistical offices all over the world. On the basis of such surveys, the standard of living of both households and individuals can be measured. Determining poverty line and setting up a basis for social welfare assistance depend on these surveys. In addition, weights for consumer price index which in turn is an important measure of inflation are derived from such surveys. Egypt has recognized the greatest importance of these surveys long time ago, the current HIECS 2004/2005 is the eighth Household Income, Expenditure and Consumption Survey that was carried out in 2004/2005, on a sample of 48000 households, among a long series of similar surveys that started back in 1955, and followed by several surveys.

The survey main objectives are: To identify expenditure levels and patterns of population as well as socio-economic and demographic differentials. To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is an important input for national planning. Current and past demand estimates are utilized to predict future demands. To measure mean household and per-capita expenditure for various expenditure items along with socio-economic correlates. To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. To define mean household and per-capita income from different sources. To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. To study the relationships between demographic, geographical, housing characteristics of households and their income and expenditure for commodities and services. To provide data necessary for national accounts especially in compiling inputs and outputs tables. To identify consumers behavior changes among socio-economic groups in urban and rural areas. To identify per capita food consumption and its main components of calories, proteins and fats according to its sources and the levels of expenditure in both urban and rural areas. To identify the value of expenditure for food according to sources, either from household production or not, in addition to household expenditure for non food commodities and services. To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ...) in urban and rural areas. To identify the percentage distribution of income recipients according to some background variables such as housing conditions, size of household and characteristics of head of household.

It is the first time that the Household Income, Expenditure and Consumption Survey implies the following issues: 1- The use of the classification of individual consumption according to purpose (COICOP) in designing the expenditure and consumption questionnaire. 2- The inclusion of the main sales outlets of food and beverages. 3- The addition of school enrollment (6+ years) to the household schedule. 4- The inclusion of expenditure for used commodities (durables and semi durables). 5- The addition of data related to change in assets owned by the household during the reference year.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of the Household Income, Expenditure and Consumption Survey (HIECS) of 2004/2005 is a multi-stage stratified cluster sample and self-weighted to the practical extent. Its designed size is 48000 households allocated among governorates and their urban/rural components in proportion to size. The sample was selected in three stages (the second stage is considered dummy), the first two stages is related to the Master Sample which has been drawn directly before the fieldwork of HIECS started. The third sampling stage concerns with the selection of a sample of 40 households from each Master Sample Areas (1200 areas with approximately 700 households in each).

The Master Sample (1200 areas) has been allocated among the governorates of Egypt, with its urban/rural components, in proportion with the estimated size of households of every stratum (governorate) and substratum (urban/rural populations). At the first sampling stage, the shiakha in urban and village in rural are considered the smallest administrative divisions for which census data are available. Therefore such divisions were considered Primary Sampling Units (PSUs) for urban and rural samples of all governorates respectively. Small towns which are not further subdivided into smaller administrative units are dealt with as urban PSUs. While the larger shiakhas or towns were subdivided into several PSUs using the 1996 census data. At the contrary, a village with less than 600 households in 1996 (700 households at present) was joined to the adjacent village so as to make certain that all PSUs are greater than 600 households in 1996. Subsequently, the sampling frames of the first stage sample of urban/rural substrata for all governorates were formed. Implicit stratification was introduced to both urban and rural frames. At the second stage of sampling, a single area segment was selected following the equal probability selection method. A field operation has been carried out for the purpose of creating a household list for each selected second stage sample segment. In the third sampling stage representing the final stage, 40 households were selected from each area segment selected in the second sampling stage of the master sample. With the aim of reducing the field efforts it was deemed efficient to limit the spread of the household sample over the entire area segments by sampling clusters of 5 households each instead of sampling individual households directly. It is worth mentioning that the method of systematic selection will jeopardize the property of equal probability selection as each household in the list still has 40 chances of being selected in the sample.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among the documentation materials published in both Arabic and English.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1- Expenditure and consumption questionnaire. 2- Diary questionnaire for expenditure and consumption. 3- Income questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of Labor Statisticians held in Geneva, 2003. - Using the recent Classification of Individual Consumption according to Purpose (COICOP). - Using more than one approach of expenditure measurement to serve many purposes of the survey.

A brief description of each questionnaire is given next:

1- Expenditure and Consumption Questionnaire

This questionnaire comprises 14 tables in addition to identification and geographic data of household on the cover page. The questionnaire is divided into two main sections.

Section one: Household schedule and other information. It includes: - Demographic characteristics and basic data for all household individuals consisting of 16 questions for every person. - Members of household who are currently working abroad. - The household ration card. - The main outlets that provide food and beverage. - Domestic and foreign tourism. - The housing conditions including 15 questions. - Means of transportation used to go to work or school. - The household possession of appliances and means

Census Tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity that are updated by local participants prior to each decennial census as part of the Census Bureau's Participant Statistical Areas Program. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. To determine a person's poverty status, one compares the person's total family income in the last 12 months with the poverty threshold appropriate for that person's family size and composition (see example below). If the total income of that person's family is less than the threshold appropriate for that family, then the person is considered "below the poverty level," together with every member of his or her family. If a person is not living with anyone related by birth, marriage, or adoption, then the person's own income is compared with his or her poverty threshold. The total number of people below the poverty level is the sum of people in families and the number of unrelated individuals with incomes in the last 12 months below the poverty threshold.Since ACS is a continuous survey, people respond throughout the year. Because the income questions specify a period covering the last 12 months, the appropriate poverty thresholds are determined by multiplying the base-year poverty thresholds (1982) by the average of the monthly inflation factors for the 12 months preceding the data collection. See the table in Appendix A titled "Poverty Thresholds in 1982, by Size of Family and Number of Related Children Under 18 Years (Dollars)," for appropriate base thresholds. See the table "The 2012 Poverty Factors" in Appendix A for the appropriate adjustment based on interview month.Poverty status was determined for all people except institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years old. These groups were excluded from the numerator and denominator when calculating poverty rates.

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled at the Place level. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

The American Community Survey (ACS) 5 Year 2016-2020 socioeconomic estimate data is a subset of information derived from the following census tables:B08013 - Aggregate Travel Time To Work Of Workers By Sex;B08303 - Travel Time To Work;B17019 - Poverty Status In The Past 12 Months Of Families By Household Type By Tenure;B17021 - Poverty Status Of Individuals In The Past 12 Months By Living Arrangement;B19001 - Household Income In The Past 12 Months;B19013 - Median Household Income In The Past 12 Months;B19025 - Aggregate Household Income In The Past 12 Months;B19113 - Median Family Income In The Past 12 Months;B19202 - Median Non-family Household Income In The Past 12 Months;B23001 - Sex By Age By Employment Status For The Population 16 Years And Over;B25014 - Tenure By Occupants Per Room;B25026 - Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit;B25106 - Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months;C24010 - Sex By Occupation For The Civilian Employed Population 16 Years And Over;B20004 - Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over;B23006 - Educational Attainment by Employment Status for the Population 25 to 64 Years, and;B24021 - Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_ACS 5-Year Socioeconomic Estimate Data by CountyDate of Coverage: 2016-2020

The indicator is defined as the percentage of the population whose equivalised disposable income is below the ‘at-risk-of-poverty threshold’ calculated in the standard way for the base year, currently 2005, and then adjusted for inflation.

This feature layer represents Sustainable Development Goal indicator 1.2.1 'Proportion of Population Living Below the National Poverty Line' for Palestine in 2011. In 2010-2011, PCBS invested substantially in reviewing its original (1998) poverty measurement and trends methodology to meet international best practice standards, which primarily involve the following: (a) adjusting for spatial price differences; (b) calculating poverty headcount at individual rather than household level; and (c) ensuring that poverty lines over time reflect the same purchasing power, which necessitates that the poverty line is adjusted for price inflation using official CPI.

The table presents data from 10 out of 11 CEEAC countries gathered from the WDI database. It features the following series of variables: - the income share of the lowest 20%, - the total natural resources rents (% GDP), - agriculture, value added (annual % growth), - GDP growth (annual %), - Industry, value added (annual % growth), - the total population growth (annual % growth), - Rural population growth (annual %), - Urban population growth (annual %), - Services, value added (annual % growth) , - Domestic credit to private sector by banks (% of GDP), - Employment in agriculture (% of total employment) (modeled ILO estimate), - Employment in industry (% of total employment) (modeled ILO estimate), - Employment in service (% of total employment) (modeled ILO estimate), - Inflation, GDP deflator (annual %), - GINI index (World Bank estimate), - Gini (%), - Vast majority income (annual % growth). Data are then treated in E-views to regress pro poor growth (measured by the income share held by the lowest 20% and by the vast majority income growth) with the value added of the primary (agriculture), the secondary (industry) and the tertiary (service) sectors; employment the both sectors, the natural resources rents and other control variables like GDP growth, inflation and inequality.