This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are geography-specific; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% income threshold of Nova Scotian tax filers. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are based on national threshold values, regardless of selected geography; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

Graph and download economic data for Minimum Wealth Cutoff for the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBLTP1311) from Q3 1989 to Q3 2022 about wealth, percentile, and USA.

In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

Graph and download economic data for Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBLTP1246) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.

While a household in the United States must earn greater than $380,000 to rank in the top 1% of all American households, a much higher income is required in most of California's coastal communities.

In March 2025, the top one percent of earners in the United Kingdom received an average pay of over 16,000 British pounds per month, compared with the bottom ten percent of earners who earned around 800 pounds a month.

The statistic displays the minimum threshold of wealth owned by the population in selected European countries in order to be selected into the richest one percent as of 2014. For instance, in Luxembourg, the top richest one percent of the population started at 2.7 million euros in 2014. In comparison, in Spain the cut-off point was at 227.7 thousand euros in the same year.

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are based on national threshold values, regardless of selected geography; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

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).

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

If you’re a senior with low income, you may qualify for monthly Guaranteed Annual Income System payments.

Maximum payment and allowable private income amounts for the period from July 1, 2025 to June 30, 2026 are:

• $90 monthly for single seniors (maximum monthly payment amount), your annual private income must be less than $4,320
• $180 monthly for senior couples (maximum monthly payment amount), your annual private income must be less than $8,640

The data is organized by private income levels. GAINS payments are provided on top of the Old Age Security (OAS) pension and the Guaranteed Income Supplement (GIS) payments you may receive from the federal government.

Learn more about the Ontario Guaranteed Annual Income System

This data is related to The Retirement Income System in Canada

Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

Advani, Hughson and Tarrant (2021) model the revenue that could be raised from an annual and a one-off wealth tax of the design recommended by Advani, Chamberlain and Summers in the Wealth Tax Commission’s Final Report (2020). This deposit contains the code required to replicate the revenue modelling and distributional analysis. The modelling draws on data from the Wealth and Assets Survey, supplemented with the Sunday Times Rich List, which we use to implement a Pareto correction for the under-coverage of wealth at the top.Around the world, the unprecedented public spending required to tackle COVID-19 will inevitably be followed by a debate about how to rebuild public finances. At the same time, politicians in many countries are already facing far-reaching questions from their electorates about the widening cracks in the social fabric that this pandemic has exposed, as prior inequalities become amplified and public services are stretched to their limits. These simultaneous shocks to national politics inevitably encourage people to 'think big' on tax policy. Even before the current crisis there were widespread calls for reforms to the taxation of wealth in the UK. These proposals have so far focused on reforming existing taxes. However, other countries have begun to raise the idea of introducing a 'wealth tax'-a new tax on ownership of wealth (net of debt). COVID-19 has rapidly pushed this idea higher up political agendas around the world, but existing studies fall a long way short of providing policymakers with a comprehensive blueprint for whether and how to introduce a wealth tax. Critics point to a number of legitimate issues that would need to be addressed. Would it be fair, and would the public support it? Is this type of tax justified from an economic perspective? How would you stop the wealthiest from hiding their assets? Will they all simply leave? How can you value some assets? What happens to people who own lots of wealth, but have little income with which to pay a wealth tax? And if wealth taxes are such a good idea, why have many countries abandoned them? These are important questions, without straightforward answers. The UK government last considered a wealth tax in the mid-1970s. This was also the last time that academics and policymakers in the UK thought seriously about how such a tax could be implemented. Over the past half century, much has changed in the mobility of people, the structure of our tax system, the availability of data, and the scope for digital solutions and coordination between tax authorities. Old plans therefore cannot be pulled 'off the shelf'. This project will evaluate whether a wealth tax for the UK would be desirable and deliverable. We will address the following three main research questions: (1) Is a wealth tax justified in principle, on economic or other grounds? (2) How should a wealth tax be designed, including definition of the tax base and solutions to administrative challenges such as valuation and liquidity? (3) What would be the revenue and distributional effects of a wealth tax in the UK, for a variety of design options and at specified rates/thresholds? To answer these questions, we will draw on a network of world-leading exports on tax policy from across academia, policy spheres, and legal practice. We will examine international experience, synthesising a large body of existing research originating in countries that already have (or have had) a wealth tax. We will add to these resources through novel research that draws on adjacent fields and disciplines to craft new solutions to the practical problems faced in delivering a wealth tax. We will also review common objections to a wealth tax. These new insights will be published in a series of 'evidence papers' made available directly to the public and policymakers. We will also publish a final report that states key recommendations for government and (if appropriate) delivers a 'ready to legislate' design for a wealth tax. We will not recommend specific rates or thresholds for the tax. Instead, we will create an online 'tax simulator' so that policymakers and members of the public can model the revenue and distributional effects of different options. We will also work with international partners to inform debates about wealth taxes in other countries. The modelling draws on data from the Wealth and Assets Survey, supplemented with the Sunday Times Rich List, which we use to implement a Pareto correction for the under-coverage of wealth at the top.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2015 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2015 American Community Survey 1-Year Estimates

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..One person in each household is designated as the householder. In most cases, this is the person or one of the people in whose name the home is owned, being bought, or rented and who is listed on line one of the survey questionnaire. If there is no such person in the household, any adult household member 15 years old and over could be designated as the householder...Households are classified by type according to the presence of relatives. Two types of householders are distinguished: a family householder and a nonfamily householder. A family householder is a householder living with one or more individuals related to him or her by birth, marriage, or adoption. The householder and all people in the household related to him or her are family members. A nonfamily householder is a householder living alone or with non-relatives only...To determine poverty status of a householder in family households, one compares the total income in the past 12 months of all family members with the poverty threshold appropriate for that family size and composition. If the total family income is less than the threshold, then the householder together with every member of his or her family are considered as having income below the poverty level...In determining poverty status of a nonfamily householder, only the householder's own personal income is compared with the appropriate threshold for a single person. The poverty status of a nonfamily householder does not affect the poverty status of the other unrelated individuals living in the household and the incomes of people living in the household who are not related to the householder are not considered when determining the poverty status of a householder. The income of each unrelated individual is compared to the appropriate threshold for a single person..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the...

This map compares the number of people living above the poverty line to the number of people living below. Why do this?There are people living below the poverty line everywhere. Nearly every area of the country has a balance of people living above the poverty line and people living below it. There is not an "ideal" balance, so this map makes good use of the national ratio of 6 persons living above the poverty line for every 1 person living below it. Please consider that there is constant movement of people above and below the poverty threshold, as they gain better employment or lose a job; as they encounter a new family situation, natural disaster, health issue, major accident or other crisis. There are areas that suffer chronic poverty year after year. This map does not indicate how long people in the area have been below the poverty line. "The poverty rate is one of several socioeconomic indicators used by policy makers to evaluate economic conditions. It measures the percentage of people whose income fell below the poverty threshold. Federal and state governments use such estimates to allocate funds to local communities. Local communities use these estimates to identify the number of individuals or families eligible for various programs." Source: U.S. Census BureauIn the U.S. overall, there are 6 people living above the poverty line for every 1 household living below. Green areas on the map have a higher than normal number of people living above compared to below poverty. Orange areas on the map have a higher than normal number of people living below the poverty line compared to those above in that same area.The map shows the ratio for counties and census tracts, using these layers, created directly from the U.S. Census Bureau's American Community Survey (ACS)For comparison, an older layer using 2013 ACS data is also provided.The layers are updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Poverty status is based on income in past 12 months of survey. Current Vintage: 2014-2018ACS Table(s): B17020Data downloaded from: Census Bureau's API for American Community Survey National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

Abstract

The 2009 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

The 2003 Master Sample (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

Analysis unit

The unit of analysis was the Household

Universe

The 2009 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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2003 Master Sample (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.

Mode of data collection

Face-to-face [f2f]

Research instrument

Refer to the attached 2009 FIES questionnaire in pdf file (External Resources)

In 2022, 9.9 percent of all Canadians were living in low income. Between 2000 and 2022, the percentage of population with low income experienced a decrease, reaching the lowest value in 2020. The highest share of Canadians with low income was recorded in 2015, with 14.5 percent of the total population.

Low Income Measures

The low income measures (LIMs) were developed by Statistics Canada in the 1990s. They, along with the low income cut-offs (LICOs) and the market basket measure (MBM), were created in order to measure and track the low income population of Canada. With low income measures, individuals are classified as being in low income if their income falls below fifty percent of the median adjusted household income. The median income is adjusted in order to reflect the differing financial needs of households based on the number of its members. The low income measures are a useful tool to compare low income populations between countries as they do not rely on an arbitrary standard of what constitutes the threshold for poverty. Statistics Canada insists that the low income measures are not meant to be representative of a poverty rate. The department has no measure which they define as a measurement of poverty in Canada. Latest data and trends In 2022, around 2.1 million people were living in low income families in Canada. This figure has been fluctuating over the years, both in absolute numbers and in proportion over the total population. More women than men were living in low income families in 2022, though the number of men in low income has risen at twice the rate as that of women. One of the more drastic changes has been the rise in the number of single individuals living in low income, increasing by more than 60 percent since 2000.