This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.
This dataset represents the geospatial extent as polygons and the corresponding attribution for census block groups that meet the definition of low-income communities according to the Virginia 2020 Environmental Justice Act: “Low-income community” definition: “’Low-income community’ means any census block group in which 30 percent or more of the population is composed of people with low income.”
The referenced “low income” definition is also provided below: “Low income” definition: “’Low income’ means having an annual household income equal to or less than the greater of (i) an amount equal to 80 percent of the median income of the area in which the household is located, as reported by the Department of Housing and Urban Development, and (ii) 200 percent of the Federal Poverty Level.”
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents median household incomes for various household sizes in Thedford, NE, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/thedford-ne-median-household-income-by-household-size.jpeg" alt="Thedford, NE median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Thedford median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Lower Kalskag, AK, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/lower-kalskag-ak-median-household-income-by-household-size.jpeg" alt="Lower Kalskag, AK median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Lower Kalskag median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Lower Frederick Township, Pennsylvania, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/lower-frederick-township-pa-median-household-income-by-household-size.jpeg" alt="Lower Frederick Township, Pennsylvania median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Lower Frederick township median household income. You can refer the same here
Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Country Life Acres, MO, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/country-life-acres-mo-median-household-income-by-household-size.jpeg" alt="Country Life Acres, MO median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Country Life Acres median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
An investigation was carried out into the process involved in designing and building affordable community-driven vertical greening systems (VGS) prototypes in a low-income neighbourhood of Lagos, Nigeria. Prototypes are intended to improve indoor thermal comfort conditions and potentially provide substrate to grow edible and medicinal plants. Data, relating to 2 prototypes built in 2014 and their evaluation, comprises:the narrative / information about community participation in the design and construction of the 2 prototypes;the monitoring procedure used to collect thermal performance data;the analysis of the data collected on thermal performance;the community acceptability survey related to the prototypes.A summary is provided of a community-acceptability survey undertaken following a second round of 2 prototypes, built in the same neighbourhood in the year 2016. Research restults based upon these data are published at https://doi.org/10.1016/j.buildenv.2018.01.022
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Lower Alloways Creek Township, New Jersey, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/lower-alloways-creek-township-nj-median-household-income-by-household-size.jpeg" alt="Lower Alloways Creek Township, New Jersey median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Lower Alloways Creek township median household income. You can refer the same here
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the Census of Population.For more information on Aboriginal variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016 and the Aboriginal Peoples Technical Report, Census of Population, 2016.Return to footnote2referrerFootnote 3Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote3referrerFootnote 4The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote4referrerFootnote 5Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.Return to footnote5referrerFootnote 6Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the 2016 Census of Population. For more information on Aboriginal variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016 and the Aboriginal Peoples Technical Report, Census of Population, 2016.Return to footnote6referrerFootnote 7'Aboriginal identity' includes persons who are First Nations (North American Indian), Métis or Inuk (Inuit) and/or those who are Registered or Treaty Indians (that is, registered under the Indian Act of Canada) and/or those who have membership in a First Nation or Indian band. Aboriginal peoples of Canada are defined in the Constitution Act, 1982, section 35 (2) as including the Indian, Inuit and Métis peoples of Canada.Return to footnote7referrerFootnote 8'Single Aboriginal responses' includes persons who are in only one Aboriginal group, that is First Nations (North American Indian), Métis or Inuk (Inuit).Return to footnote8referrerFootnote 9Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the 2016 Census of Population. For additional information, refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016.Return to footnote9referrerFootnote 10'Multiple Aboriginal responses' includes persons who are any two or all three of the following: First Nations (North American Indian), Métis or Inuk (Inuit).Return to footnote10referrerFootnote 11'Aboriginal responses not included elsewhere' includes persons who are not First Nations (North American Indian), Métis or Inuk (Inuit), but who have Registered or Treaty Indian status and/or Membership in a First Nation or Indian band.
Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the Census of Population.For more information on Aboriginal variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016 and the Aboriginal Peoples Technical Report, Census of Population, 2016.Return to footnote2referrerFootnote 3Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote3referrerFootnote 4The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote4referrerFootnote 5Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.Return to footnote5referrerFootnote 6Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the 2016 Census of Population. For more information on Aboriginal variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016 and the Aboriginal Peoples Technical Report, Census of Population, 2016.Return to footnote6referrerFootnote 7'Aboriginal identity' includes persons who are First Nations (North American Indian), Métis or Inuk (Inuit) and/or those who are Registered or Treaty Indians (that is, registered under the Indian Act of Canada) and/or those who have membership in a First Nation or Indian band. Aboriginal peoples of Canada are defined in the Constitution Act, 1982, section 35 (2) as including the Indian, Inuit and Métis peoples of Canada.Return to footnote7referrerFootnote 8'Single Aboriginal responses' includes persons who are in only one Aboriginal group, that is First Nations (North American Indian), Métis or Inuk (Inuit).Return to footnote8referrerFootnote 9Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the 2016 Census of Population. For additional information, refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016.Return to footnote9referrerFootnote 10'Multiple Aboriginal responses' includes persons who are any two or all three of the following: First Nations (North American Indian), Métis or Inuk (Inuit).Return to footnote10referrerFootnote 11'Aboriginal responses not included elsewhere' includes persons who are not First Nations (North American Indian), Métis or Inuk (Inuit), but who have Registered or Treaty Indian status and/or Membership in a First Nation or Indian band.
The HOME Investment Partnerships Program (HOME) provides formula grants to states and localities that communities use - often in partnership with local nonprofit groups - to fund a wide range of activities including building, buying, and/or rehabilitating affordable housing for rent or homeownership or providing direct rental assistance to low-income people. HOME is the largest federal block grant to state and local governments designed exclusively to create affordable housing for low-income households.Authorized under Title II of the Cranston-Gonzalez National Affordable Housing Act, the HOME Investment Partnership Program (HOME) is designed exclusively to create affordable housing for low-income households. Each year the HOME Program allocates approximately $2 billion to fund the development, purchase, or rehabilitation of affordable housing, and to provide direct rental assistance. To learn more about the HOME program visit: https://www.hud.gov/program_offices/comm_planning/home, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_HOME Grantee Areas
Date of Coverage: Q1 FY 2025
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Korea HS: AS: 2 Quintile: Persons per Household data was reported at 3.040 Person in Mar 2018. This stayed constant from the previous number of 3.040 Person for Dec 2017. Korea HS: AS: 2 Quintile: Persons per Household data is updated quarterly, averaging 3.310 Person from Mar 2003 (Median) to Mar 2018, with 61 observations. The data reached an all-time high of 3.470 Person in Mar 2003 and a record low of 3.040 Person in Mar 2018. Korea HS: AS: 2 Quintile: Persons per Household data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s Korea – Table KR.H062: Household Income and Expenditure Survey (HS): by Income Quintile: All Salary and Wage Earner.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Comoros KM: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 19.200 % in 2014. This records an increase from the previous number of 17.300 % for 2004. Comoros KM: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 18.250 % from Dec 2004 (Median) to 2014, with 2 observations. The data reached an all-time high of 19.200 % in 2014 and a record low of 17.300 % in 2004. Comoros KM: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Comoros – Table KM.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Show Low, AZ, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/show-low-az-median-household-income-by-household-size.jpeg" alt="Show Low, AZ median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Show Low median household income. You can refer the same here
Low-Income Census tables used to gather data from the 2017-2021 American Community Survey 5-Year Estimates Using U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group. Census tables used to gather data from the 2017-2021 American Community Survey 5-Year Estimates. For more information and for methodology, visit DVRPC's website: https://www.dvrpc.org/GetInvolved/TitleVI/ For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipd Source of tract boundaries: US Census Bureau. The TIGER/Line Files Note: Tracts with null values should be symbolized as "Insufficient or No Data". Data Dictionary for Attributes: (Source = DVRPC indicates a calculated field) Field Alias Description Source geoid20 GEOID20 Census tract identifier (text) Census statefp20 State FIPS FIPS Code for State Census countyfp20 County FIPS FIPS Code for County Census name20 Tract Number Tract Number Census d_class Disabled Classification Classification of tract's disabled percentage as: well below average, below average, average, above average, or well above average DVRPC d_cntest Disabled Count Estimate Estimated count of disabled population Census d_cntmoe Disabled Count MOE Margin of error for estimated count of disabled population Census d_pctest Disabled Percentage Estimate Estimated percentage of disabled population DVRPC d_pctile Disabled Percentile Tract's regional percentile for percentage disabled DVRPC d_pctmoe Disabled Percentage MOE Margin of error for percentage of disabled population DVRPC d_score Disabled Score Corresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4 DVRPC em_class Ethnic Minority Classification Classification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above average DVRPC em_cntest Ethnic Minority Count Estimate Estimated count of Hispanic/Latino population Census em_cntmoe Ethnic Minority Count MOE Margin of error for estimated count of Hispanic/Latino population Census em_pctest Ethnic Minority Percentage Estimate Estimated percentage of Hispanic/Latino population DVRPC em_pctile Ethnic Minority Percentile Tract's regional percentile for percentage Hispanic/Latino DVRPC em_pctmoe Ethnic Minority Percentage MOE Margin of error for percentage of Hispanic/Latino population DVRPC em_score Ethnic Minority Score Corresponding numeric score for tract's Hispanic/Latino classification: 0, 1, 2, 3, 4 DVRPC f_class Female Classification Classification of tract's female percentage as: well below average, below average, average, above average, or well above average DVRPC f_cntest Female Count Estimate Estimated count of female population Census f_cntmoe Female Count MOE Margin of error for estimated count of female population Census f_pctest Female Percentage Estimate Estimated percentage of female population DVRPC f_pctile Female Percentile Tract's regional percentile for percentage female DVRPC f_pctmoe Female Percentage MOE Margin of error for percentage of female population DVRPC f_score Female Score Corresponding numeric score for tract's female classification: 0, 1, 2, 3, 4 DVRPC fb_class Foreign Born Classification Classification of tract's foreign born percentage as: well below average, below average, average, above average, or well above average DVRPC fb_cntest Foreign Born Count Estimate Estimated count of foreign born population Census fb_cntmoe Foreign Born Count MOE Margin of error for estimated count of foreign born population Census fb_pctest Foreign Born Percentage Estimate Estimated percentage of foreign born population DVRPC fb_pctile Foreign Born Percentile Tract's regional percentile for percentage foreign born DVRPC fb_pctmoe Foreign Born Percentage MOE Margin of error for percentage of foreign born population DVRPC fb_score Foreign Born Score Corresponding numeric score for tract's foreign born classification: 0, 1, 2, 3, 4 DVRPC lep_class Limited English Proficiency Count Estimate Estimated count of limited english proficiency population Census lep_cntest Limited English Proficiency Count MOE Margin of error for estimated count of limited english proficiency population Census lep_cntmoe Limited English Proficiency Percentage Estimate Estimated percentage of limited english proficiency population DVRPC lep_pctest Limited English Proficiency Percentage MOE Margin of error for percentage of limited english proficiency population DVRPC lep_pctile Limited English Proficiency Percentile Tract's regional percentile for percentage limited english proficiency DVRPC lep_pctmoe Limited English Proficiency Classification Classification of tract's limited english proficiency percentage as: well below average, below average, average, above average, or well above average DVRPC lep_score Limited English Proficiency Score Corresponding numeric score for tract's limited english proficiency classification: 0, 1, 2, 3, 4 DVRPC li_class Low Income Classification Classification of tract's low income percentage as: well below average, below average, average, above average, or well above average DVRPC li_cntest Low Income Count Estimate Estimated count of low income (below 200% of poverty level) population Census li_cntmoe Low Income Count MOE Margin of error for estimated count of low income population Census li_pctest Low Income Percentage Estimate Estimated percentage of low income (below 200% of poverty level) population DVRPC li_pctile Low Income Percentile Tract's regional percentile for percentage low income DVRPC li_pctmoe Low Income Percentage MOE Margin of error for percentage of low income population DVRPC li_score Low Income Score Corresponding numeric score for tract's low income classification: 0, 1, 2, 3, 4 DVRPC oa_class Older Adult Classification Classification of tract's older adult percentage as: well below average, below average, average, above average, or well above average DVRPC oa_cntest Older Adult Count Estimate Estimated count of older adult population (65 years or older) Census oa_cntmoe Older Adult Count MOE Margin of error for estimated count of older adult population Census oa_pctest Older Adult Percentage Estimate Estimated percentage of older adult population (65 years or older) DVRPC oa_pctile Older Adult Percentile Tract's regional percentile for percentage older adult DVRPC oa_pctmoe Older Adult Percentage MOE Margin of error for percentage of older adult population DVRPC oa_score Older Adult Score Corresponding numeric score for tract's older adult classification: 0, 1, 2, 3, 4 DVRPC rm_class Racial Minority Classification Classification of tract's non-white percentage as: well below average, below average, average, above average, or well above average DVRPC rm_cntest Racial Minority Count Estimate Estimated count of non-white population DVRPC rm_cntmoe Racial Minority Count MOE Margin of error for estimated count of non-white population DVRPC rm_pctest Racial Minority Percentage Estimate Estimated percentage of non-white population DVRPC rm_pctile Racial Minority Percentile Tract's regional percentile for percentage non-white DVRPC rm_pctmoe Racial Minority Percentage MOE Margin of error for percentage of non-white population DVRPC rm_score Racial Minority Score Corresponding numeric score for tract's non-white classification: 0, 1, 2, 3, 4 DVRPC y_class Youth Classification Classification of tract's youth percentage as: well below average, below average, average, above average, or well above average DVRPC y_cntest Youth Count Estimate Estimated count of youth population (under 18 years) Census y_cntmoe Youth Count MOE Margin of error for estimated count of youth population Census y_pctest Youth Percentage Estimate Estimated percentage of youth population (under 18 years) DVRPC y_pctile Youth Percentile Tract's regional percentile for percentage youth DVRPC y_pctmoe Youth Percentage MOE Margin of error for percentage of youth population DVRPC y_score Youth Score Corresponding numeric score for tract's youth classification: 0, 1, 2, 3, 4 DVRPC ipd_score Composite Score Overall score adding the classification scores across all nine variables DVRPC u_tpopest Total Population Estimate Estimated total population of tract (universe [or denominator] for youth, older adult, female, racial minoriry, ethnic minority, & foreign born) Census u_tpopmoe Total Population MOE Margin of error for estimated total population of tract Census u_pop6est Population 6+ Estimated population over five years of age (universe [or
The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in FSM. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people. The 2005 FSM HIES asked income of all persons 15 years and over. It referred to income received during the calendar year 2004, and includes both cash and in-kind income. The survey has five primary objectives, namely to:
1) Rebase the FSM Consumer Price Index (CPI); 2) Provide data on the distribution of income and expenditures throughout the FSM; 3) Provide data for national accounts, particularly regarding income from home production activities and the consumption of goods and services derived form home production activities; 4) Provide nutritional information and food consumption patterns for the FSM families; and 5) Provide data for hardship study.
Entire Country
Four states of the FSM: Yap, Chuuk, Pohnpei, and Kosrae
The survey universe covered all persons living in their place of usual residence at the time of the survey. Income data were collected from persons aged 15 years and over while expenditure data were obtained from all household members at a household level. Persons living in institutions, such as school dormitories, hospital wards, hostels, prisons, as well as those whose usual residence were somewhere else were excluded from the survey.
Sample survey data [ssd]
The 2005 FSM Household Income and Expenditure Survey (HIES) used a sampling frame based on updated information on Enumeration Districts (ED) and household listing from the 2000 FSM Census. Based on this sampling frame, the four states of FSM were then classified as the domains of the survey. Each of the states was further divided into 3 strata, except for Kosrae which was not divided at all because it doesn't possess any outer islands and it has relatively good access to goods and services. The entire island was therefore classified under stratum 1. Each stratum was defined as follows:
1) State center and immediate surrounding areas:
- High 'living standard' and has immediate access to goods and services.
2) Areas surrounding state center (rest of main island):
- Medium 'living standard' and sometime limited access to goods and services
3) Outer islands:
- Low 'living standard' and rare access to goods and services.
Within each stratum, the HIES used a two-stage stratified sampling approach from which the sample was selected independently. First, enumeration districts (EDs) were drawn from each stratum using Proportion Probability to Size (PPS) sampling. Thus, the larger the ED size, the higher its probability of selection. About 69 EDs out of a total of 373 EDs were selected nationwide for the survey. Generally, one enumerator is assigned to each ED. Second, 20 households were systematically selected from an updated household listing for each of the selected EDs using a random start to come up with a total sample size of 1,380 households, or roughly 8.4 percent of all households in the state. Although it offered a fairly good representation of the total households in the nation, the final sample size showed a reduction of nearly 180 households from the 1,560 households, or 10 percent, initially selected for the survey.
Detailed information on the changes made to the sample size can be found in the next section under "Deviations from Sample Design."
The original plan to sample 1,560 households, or about 9.5 percent of all households in the nation was eventually reduced to 1,380 households, or about 8.4 percent of all households. The reduction of the sample size was due to fuel unavailability for transportation and uncertainty of field trip schedules to some of the selected outer islands. Dropping some of these islands from the sample was not expected to impact significantly on the accuracy of the survey results because independent weighting took place within each stratum, where islands were considered to be sufficiently homogenous.
Other [oth]
Questionaires and forms used for the 2005 FSM HIES consisted of 1) HIES Questionnaire and 2) Weekly Diaries. The HIES Questionnaire were provided to enumerators and should be filled out during the first visit to the household. Its main objective was to collect housing information, basic demographic information about members of the household, and general household expenditures over the previous year. On the other hand, the weekly diaries, was an attempt to record household expenditure on a daily basis over the course of a 2 week period. Both the HIES questionnaire and the weekly diary were developed and modeled after similar forms from the 1998 FSM HIES Survey and the 2004 Palau HIES Survey. Dr. Micheal Levin from the US Census Bureau, International Program Center (IPC), Ms. Brihmer Johnson of the FSM Division of Statistics and Mr. Glenn McKinlay, statistics advisor to FSM Division of Statistics, provided crucial inputs to the overall design of these forms. All questionnaires and diaries used during the HIES were printed in English so it was extremely important that field interviewers understand the instuctions and questions contained within. Testing of the questionnaire were carried out by FSM Division of Statistics staffs who conducted "real" interviews with certain households in their neighborhood as well as having their own household be interviewed by a different office staff. Specific sections for both the HIES questionnaire and the weekly diaries are outlined below:
I. HIES Questionnaire
1) General Household characteristics 2 ) Individual Person Characteristics 3) General Expenditure Listings - 12 Months Recall Period
II. 2 Week Daily Diaries
1) Daily Expenditure Diary - Day1 (Mon) thru Day7 (Sun) 2) Home Produced Items 3) Gifts Given Away 4) Gifts Received 5) Unusual Expenses for Special Events
Data editing of the 2005 FSM HIES data occurred over several instances during the data processing phase of the project and afterwards prior to putting together the final report. After a two weeks office review and call backs right after the enumeration phase, the initial phase of data editing took place on July 18, 2005 when the data processing phase of the survey commenced. Training for editing and coding took place on the same day along with the signing of contracts for 10 office clerks recruited to carry out this phase of the survey. As part of their contract, these individuals were also hired to key in the data at a later time. One of their primary responsibily was to match geographic ids for questionnaire with corresponding diaries and ensure consistencies and valid entries accordingly. No computer consistency edit checks were run against the data during the keying/verification process since the programs for these processes were not available at the time. All data quality checks and edits were done at the US Bureau of Census. Further edits were applied to the data during the data analysis and report writing process.
There were five types of checks performed: Structural check, Verification check, Consistency check, Macro Editing check, Data Quality assessment. Edit lists were also produced for health module, income and expenditure questionnaire which needed to be checked against the questionnaires. On the edit list, corrections of errors were made by crossing out incorrect or missing values and entering the correct values in red. Missing amounts that were also missing on the questionnaire will need to be estimated using estimates from questionnaires in the same Enumeration District (ED) batch. For the diaries, the batch files were concatenated for each state and exported to tab delimited files. These files were imported into Excel and the unit price for each item was calculated using quantities and weights where possible. Records for each item were then filtered out and check for outlier unit price values (both large and small values as well as missing values). Values for missing amounts were imputed from estimated using average prices from the items within the same ED.
The office operations manual used for editing and coding the questionnaires and diaries is provided under "Technical Documents/Data Processing Documents/Office Editing & Coding."
Original Sample Size: 1,560 Households Original Sampling fraction 9.5%
Final Sample Size: 1,380 Households Final Sampling fraction 8.4%
The response rate for the final sample size of 1,380 households is 100 percent. The majority of households originally selected for the survey did respond to the survey. Households which have moved to other unselected areas or elsewhere and those who refused to respond were replaced with nearby households that were willing to participate in the survey.
No sampling error analysis of the survey was calculated.
The questionnaire design of the 2005 HIES vary from that of the 1998 HIES rendering comparison of the data to the 2005 HIES limited. However, when the data permits, comparisons were made.
EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.
There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.
Longitudinal data is limited to income information and a limited set of critical qualitative, non-monetary variables of deprivation, aimed at identifying the incidence and dynamic processes of persistence of poverty and social exclusion among subgroups in the population. The longitudinal component is also more limited in sample size compared to the primary, cross-sectional component. Furthermore, for any given set of individuals, microlevel changes are followed up only for a limited duration, such as a period of four years. For both the cross-sectional and longitudinal components, all household and personal data are linkable. Furthermore, modules providing updated information in the field of social exclusion is included starting from 2005.
Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.
This is the 3rd release of 2011 Longitudinal Dataset, as published by Eurostat in September 2014.
The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Croatia, Latvia, Lithuania, Luxembourg, Hungary, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.
Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.
The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.
Sample survey data [ssd]
On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.
For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.
Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.
The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.
At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.
According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:
Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.
Mixed
This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.