Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 American Community Survey 5-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..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2016-2020 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 delineation lists 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Chile CL: Coverage: Social Safety Net Programs: % of Population data was reported at 78.220 % in 2022. This records an increase from the previous number of 63.400 % for 2020. Chile CL: Coverage: Social Safety Net Programs: % of Population data is updated yearly, averaging 77.185 % from Dec 2006 (Median) to 2022, with 8 observations. The data reached an all-time high of 82.649 % in 2017 and a record low of 63.400 % in 2020. Chile CL: Coverage: Social Safety Net Programs: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Social Protection and Insurance. Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.;ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/);;

In 2020, around **** percent of the U.S. population had private health insurance coverage. This share slightly decreased to **** percent in 2024. Medicare and Medicaid together provided healthcare coverage to approximately ** percent of the population in the United States. U.S. population with and without health insurance In 2022, over half of the U.S. population had health insurance coverage through their place of employment, around 54.5 percent. Approximately 35 percent had coverage through some form of government plan in the same year. While still low, the U.S. population without health insurance has decreased slightly from the previous year. A large portion of those without health insurance are between 19 and 25 years of age. Approximately ** percent of adults in this age group did not have health insurance in 2021. Health expenditure The United States spent approximately ****** U.S. dollars per capita on health in 2022 while in comparison, the Canadian government expended some ***** U.S. dollars per capita in the same year. However, higher health spending did not equate to a better health system or outcomes and when ranked with other comparable high-income countries, the U.S. came in last on nearly all health performance categories from access of care to health outcomes.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 American Community Survey 5-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..Foreign born excludes people born outside the United States to a parent who is a U.S. citizen..Excludes householders, spouses, and unmarried partners..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..Public assistance includes receipt of Supplemental Security Income (SSI), cash public assistance income, or Food Stamps..The 2016-2020 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 delineation lists 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Bolivia BO: Coverage: Social Safety Net Programs: % of Population data was reported at 96.801 % in 2021. This records a decrease from the previous number of 97.854 % for 2020. Bolivia BO: Coverage: Social Safety Net Programs: % of Population data is updated yearly, averaging 77.112 % from Dec 2006 (Median) to 2021, with 14 observations. The data reached an all-time high of 97.854 % in 2020 and a record low of 11.666 % in 2006. Bolivia BO: Coverage: Social Safety Net Programs: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Social Protection and Insurance. Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.;ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/);;

About this dataset

Context

This list ranks the 51 states in the United States by Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each states over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Black Population: This column displays the rank of states in the United States by their Black or African American population, using the most recent ACS data available.
• states: The states for which the rank is shown in the previous column.
• Black Population: The Black population of the states is shown in this column.
• % of Total states Population: This shows what percentage of the total states population identifies as Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total U.S. Black Population: This tells us how much of the entire United States Black population lives in that states. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Series Name: [World Bank] Proportion of population covered by social insurance programs (percent)Series Code: SI_COV_SOCINSRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerableTarget 1.3: Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerableGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

The percentage of Americans covered by the Medicaid public health insurance plan decreased from **** percent in 2021 to around **** percent in 2024. However, the percentage of those insured through Medicaid remains lower than the peak of **** percent in 2015. The expansion of Medicaid The Affordable Care Act (ACA) provided the option for states to expand Medicaid eligibility to people whose income was below a particular threshold. The ACA’s major coverage expansion came into force in 2014, and the number of individuals estimated to be enrolled in Medicaid has since surpassed ** million. More than ** million children were enrolled in the program in 2018, representing ** percent of overall Medicaid enrollment. State Medicaid coverage Initially, the ACA mandated that all state Medicaid programs would have to be extended to provide medical coverage to nearly all low-income groups. However, the Supreme Court rejected that part of the act in 2012, leaving the door open for states to make their own decision on whether they expand their plans. As of September 2021, ** states plus the District of Columbia have adopted the Medicaid expansion.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 American Community Survey 5-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..The 2016-2020 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 delineation lists 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The median age in the United States reached 39.2 years in 2024. This was up from 28.1 in 1970, reflecting a significant aging of the population. Over the coming decades, the number of retirees is projected to rise by about 40 percent by 2050. This demographic shift will present new challenges to American society, reshaping patterns of consumption, work and public policy in the decades ahead. Can an older America balance the books? Social Security spending is set to rise as America grows older. The program, which is the government’s main pillar of support for retirees, already absorbs about five percent of GDP. This could reach six percent by 2035. That trajectory will keep pressure on policymakers to balance promises to pensioners with broader fiscal constraints. A world growing older The aging trend is not unique to the U.S. The global median age reached 30.9 in 2025, up from 20.3 in 1970. By 2050, China, Japan and South Korea are expected to rank among the countries with the largest shares of people aged 65 and over. The change will oblige policymakers to adapt long-standing arrangements to societies where a larger share of people are in later life.

As of October 2024, there were 133.89 million full-time employees in the United States. This is a slight decrease from the previous month, when there were 134.15 million full-time employees. The impact COVID-19 on employment In December 2019, the COVID-19 virus began its spread across the globe. Since being classified as a pandemic, the virus caused a global health crisis that has taken the lives of millions of people worldwide. The COVID-19 pandemic changed many facets of society, most significantly, the economy. In the first years, many businesses across all industries were forced to shut down, with large numbers of employees being laid off. The economy continued its recovery in 2022 with the nationwide unemployment rate returning to a more normal 3.4 percent as of April 2023. Unemployment benefits Because so many people in the United States lost their jobs, record numbers of individuals applied for unemployment insurance for the first time. As an early response to this nation-wide upheaval, the government issued relief checks and extended the benefits paid by unemployment insurance. In May 2020, the amount of unemployment insurance benefits paid rose to 23.73 billion U.S. dollars. As of December 2022, this value had declined to 2.24 billion U.S. dollars.

Mexico Coverage: Unemployment Benefits & Active Labour Market Programs: % of Population data was reported at 0.412 % in 2022. This records a decrease from the previous number of 0.780 % for 2020. Mexico Coverage: Unemployment Benefits & Active Labour Market Programs: % of Population data is updated yearly, averaging 0.596 % from Dec 2020 (Median) to 2022, with 2 observations. The data reached an all-time high of 0.780 % in 2020 and a record low of 0.412 % in 2022. Mexico Coverage: Unemployment Benefits & Active Labour Market Programs: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Social: Social Protection and Insurance. Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.;ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/);;

The number of retired workers receiving Social Security benefits increased from approximately ***** million in 2010 to ***** million in 2023. This figure has increased at the same rate year-on-year over the past decade and is likely to continue into the future. What is Social Security? Social Security benefits are payments, which are paid out by the U.S. government to qualified retirees and disabled people, as well as to their spouses, children and survivors. These payments are meant to provide them with partial replacement income. Social security expenditure is forecast to increase year-on-year over the next decade, as it has since the beginning of the 21st century. The impact of demographic change This is likely to the fact that the U.S. population is aging rapidly, which means that seniors will account for a greater proportion of the population in the future. This demographic change will put pressure on government resources, because the workforce whose tax dollars pay for social benefits will make up a smaller percentage of the population than now. Americans who are 65 years and older are the demographic group estimated to grow the most over the next 40 years, whereas the other groups will mostly remain the same.

Key Table Information.Table Title.Family Size by Cash Public Assistance Income or Households Receiving Food Stamps/SNAP Benefits in the Past 12 Months.Table ID.ACSDT1Y2024.B19123.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.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.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.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates...

Original census file name: tl_2020_

This table contains data on the percentage of the total population living below 200% of the Federal Poverty Level (FPL), and the percentage of children living below 200% FPL for California, its regions, counties, cities, towns, public use microdata areas, and census tracts. Data for time periods 2011-2015 (overall poverty) and 2012-2016 (child poverty) and with race/ethnicity stratification is included in the table. The poverty rate table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Poverty is an important social determinant of health (see http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=39) that can impact people’s access to basic necessities (housing, food, education, jobs, and transportation), and is associated with higher incidence and prevalence of illness, and with reduced access to quality health care. More information on the data table and a data dictionary can be found in the About/Attachments section.

Iran Coverage: Social Safety Net Programs: % of Population data was reported at 89.875 % in 2020. This records a decrease from the previous number of 90.660 % for 2019. Iran Coverage: Social Safety Net Programs: % of Population data is updated yearly, averaging 90.695 % from Dec 2017 (Median) to 2020, with 4 observations. The data reached an all-time high of 91.417 % in 2017 and a record low of 89.875 % in 2020. Iran Coverage: Social Safety Net Programs: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Iran – Table IR.World Bank.WDI: Social: Social Protection and Insurance. Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.;ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/);;

About this dataset

Context

The dataset tabulates the Philadelphia population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Philadelphia across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Philadelphia was 1.55 million, a 1.04% decrease year-by-year from 2022. Previously, in 2022, Philadelphia population was 1.57 million, a decline of 1.43% compared to a population of 1.59 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of Philadelphia increased by 36,868. In this period, the peak population was 1.6 million in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Philadelphia is shown in this column.
• Year on Year Change: This column displays the change in Philadelphia population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Philadelphia Population by Year. You can refer the same here

This layer contains a Vermont-only subset of county level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 American Community Survey 5-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..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2016-2020 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 delineation lists 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:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.