Source ID: FL313065035.Q For more information about the Flow of Funds tables, see the Financial Accounts Guide (https://www.federalreserve.gov/apps/fof/Default.aspx). With each quarterly release, the source may make major data and structural revisions to the series and tables. These changes are available in the Release Highlights (https://www.federalreserve.gov/apps/fof/FOFHighlight.aspx). In the Financial Accounts, the source identifies each series by a string of patterned letters and numbers. For a detailed description, including how this series is constructed, see the series analyzer (https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL313065035&t=) provided by the source.
Source ID: FL763065503.Q For more information about the Flow of Funds tables, see the Financial Accounts Guide (https://www.federalreserve.gov/apps/fof/Default.aspx). With each quarterly release, the source may make major data and structural revisions to the series and tables. These changes are available in the Release Highlights (https://www.federalreserve.gov/apps/fof/FOFHighlight.aspx). In the Financial Accounts, the source identifies each series by a string of patterned letters and numbers. For a detailed description, including how this series is constructed, see the series analyzer (https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL763065503&t=) provided by the source.
Source ID: FR413065035.Q For more information about the Flow of Funds tables, see the Financial Accounts Guide (https://www.federalreserve.gov/apps/fof/Default.aspx). With each quarterly release, the source may make major data and structural revisions to the series and tables. These changes are available in the Release Highlights (https://www.federalreserve.gov/apps/fof/FOFHighlight.aspx). In the Financial Accounts, the source identifies each series by a string of patterned letters and numbers. For a detailed description, including how this series is constructed, see the series analyzer (https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FR413065035&t=) provided by the source.
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records.
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records. A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation (https://www.census.gov/programs-surveys/saipe/guidance/confidence-intervals.html).
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
The homeownership rate is computed by dividing the estimated total population in owner-occupied units by the estimated total population (ACS 5-year variables B25008_002E and B25008_001E from table B25008, respectively). A housing unit is owner-occupied if the owner or co-owner lives in the unit, even if it is mortgaged or not fully paid for. A housing unit is classified as occupied if it is the current place of residence of the person or group of people living in it at the time of interview, or if the occupants are only temporarily absent from the residence for two months or less (e.g., on vacation or a business trip). If all the people staying in the unit at the time of the interview are staying there for two months or less, the unit is considered to be temporarily occupied and classified as "vacant." Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records. A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation (https://www.census.gov/programs-surveys/saipe/guidance/confidence-intervals.html).
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records.
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records. A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation (https://www.census.gov/programs-surveys/saipe/guidance/confidence-intervals.html).
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records. A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation (https://www.census.gov/programs-surveys/saipe/guidance/confidence-intervals.html).
The single-parent household rate is calculated as the sum of male and female single-parent households with their own children who are younger than 18-years of age divided by total households with their own children who are younger than 18-years of age (ACS 5-year variables S1101_C03_005E, S1101_C04_005E, and S1101_C01_005E respectively from table S1101). Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Burdened households are those households who pay 30 percent or more of their household income on housing (such as rent or mortgage expenses). This is calculated as the sum of households with a mortgage spending 30.0-34.9% of their income on selected monthly owner costs, households with a mortgage spending 35.0% or more of their income on selected monthly owner costs, households without a mortgage spending 30.0-34.9% of their income on selected monthly owner costs, households without a mortgage spending 35.0% or more of their income on selected monthly owner costs, households that rent spending 30.0-34.9% of their income on gross rent, and households that rent spending 35.0% or more of their income on gross rent (ACS 5-year variables DP04_0114E, DP04_0115E, DP04_0123E, DP04_0124E, DP04_0141E, and DP04_0142E respectively from table DP04) divided by the sum of the total number of households with a mortgage, the total number of households without a mortgage, and the total number of households that rent (ACS 5-year variables DP04_0110E, DP04_0117E, and DP04_0136E respectively from table DP04). Note that the calculation excludes households where selected monthly owner costs or gross rent cannot be calculated. Selected monthly owner costs are the sum of payments for mortgages, deeds of trust, contracts to purchase, or similar debts on the property (including payments for the first mortgage, second mortgages, home equity loans, and other junior mortgages); real estate taxes; fire, hazard, and flood insurance on the property; utilities (electricity, gas, and water and sewer); and fuels (oil, coal, kerosene, wood, etc.). It also includes, where appropriate, the monthly condominium fee for condominiums and mobile home costs (installment loan payments, personal property taxes, site rent, registration fees, and license fees). Gross rent provides information on the monthly housing cost expenses for renters. Gross rent is the contract rent plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter (or paid for the renter by someone else). Gross rent is intended to eliminate differentials that result from varying practices with respect to the inclusion of utilities and fuels as part of the rental payment. The estimated costs of water and sewer, and fuels are reported on a 12-month basis but are converted to monthly figures for the tabulations. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Mean commuting time is calculated by dividing the aggregate travel time to work for all workers (in minutes) by the total number of workers, 16-years old and older, who commute (ACS 5-year variables B08013_001E from table B08013 and B08012_001E from table B08012, respectively). Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010–2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011–2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
Age-adjusted death rates are weighted averages of the age-specific death rates, where the weights represent a fixed population by age. They are used to compare relative mortality risk among groups and over time. An age-adjusted rate represents the rate that would have existed had the age-specific rates of the particular year prevailed in a population whose age distribution was the same as that of the fixed population. Age-adjusted rates should be viewed as relative indexes rather than as direct or actual measures of mortality risk. However, you can select other standard populations, or select specific population criteria to determine the age distribution ratios. Premature death rate includes all deaths where the deceased is younger than 75 years of age. 75 years of age is the standard consideration of a premature death according to the CDC's definition of Years of Potential Life Loss. Starting with the 2019 vintage, the CDC no longer calculates rates for a county when the death count is less than 20, marking them as "unreliable." FRED records these instances as missing observations in the series. For more information see the Frequently Asked Questions about Death Rates (https://wonder.cdc.gov/wonder/help/cmf.html#Frequently%20Asked%20Questions%20about%20Death%20Rates).
The crude death rate is the number of deaths reported each calendar year divided by the population, multiplied by 100,000. Premature death rate includes all deaths where the deceased is younger than 75 years of age. 75 years of age is the standard consideration of a premature death according to the CDC's definition of Years of Potential Life Loss. Starting with the 2019 vintage, the CDC no longer calculates rates for a county when the death count is less than 20, marking them as "unreliable." FRED records these instances as missing observations in the series. For more information see the Frequently Asked Questions about Death Rates (https://wonder.cdc.gov/wonder/help/cmf.html#Frequently%20Asked%20Questions%20about%20Death%20Rates).
For further information about this series go to https://www.census.gov/programs-surveys/saipe/about.html.
Estimate of educational attainment for population 18 years old and over whose highest degree was a bachelor’s, master’s, or professional or doctorate degree. (ACS variable S1501_C02_015E from table S1501.) For more information about the subject definitions, see: https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimates include data collected over a 60-month period. The date associated with the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, the value does not describe any specific day, month, or year within that time period. Multiyear estimates require some additional considerations. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see the ACS handbook (Section 3, "Understanding and Using ACS Single-Year and Multiyear Estimates," p. 13) for a comprehensive set of details and clarifications: https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf
Disconnected Youth represents the percentage of youth in a county who are between the ages of 16 and 19, who are not enrolled in school and who are unemployed or not in the labor force. (ACS 5 year variables from table DP02) Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook for a more thorough clarification. https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf The data is determined from the following calculation: (B14005_010E + B14005_011E + B14005_014E + B14005_015E + B14005_024E + B14005_025E + B14005_028E + B14005_029E) / B14005_001E
The Racial Dissimilarity Index measures the percentage of the non-hispanic white population in a county which would have to change Census tracts to equalize the racial distribution between white and non-white population groups across all tracts in the county. Starting with the 2016 observations, the calculation has been changed so that counties with only one census tract have missing data. Zero values represent counties where the proportions of non-white population and non-hispanic white population are the same. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010–2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011–2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
The American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) ask respondents age 1 year and over whether they lived in the same residence 1 year ago. For people who lived in a different residence, the location of their previous residence is collected. ACS uses a series of monthly samples to produce estimates. The 5-year dataset is used for the county-to-county migration flows since many counties have a population less than 20,000. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
This series has been discontinued in FRED. Because not all counties report crime data and the data that are reported are not uniform, user discretion is advised when using these data to make cross-county comparisons.The series represents the sum of violent crimes and property crimes as reported by county law enforcement agencies from the FBI Uniform Crime Reporting: Crime in the United States, Table 10: Offenses Known to Law Enforcement, by State by Metropolitan and Nonmetropolitan Counties. Note that these data do not represent county totals as they exclude crime counts for city agencies and other types of agencies that have jurisdiction within each county. The FBI's Uniform Crime Reporting (UCR) Program collects the number of offenses that come to the attention of law enforcement for violent crime and property crime, as well as data regarding clearances of these offenses. In addition, the FBI collects auxiliary information about these offenses (e.g., time of day of burglaries). Violent crime is composed of four offenses: murder and non-negligent manslaughter, rape, robbery, and aggravated assault. Violent crimes are defined in the UCR Program as those offenses that involve force or threat of force. Property crime includes the offenses of burglary, larceny-theft, motor vehicle theft, and arson. The object of the theft-type offenses is the taking of money or property, but there is no force or threat of force against the victims. See Table 10 Data Declaration (https://ucr.fbi.gov/crime-in-the-u.s/2018/crime-in-the-u.s.-2018/tables/table-10/table-10-data-declaration) for more information.
For further information about this series go to https://www.census.gov/programs-surveys/saipe/about.html.
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records.
For further information about this series go to https://www.census.gov/programs-surveys/saipe/about.html.
Data obtained from ACS Demographic and Housing Estimates, table DP05. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010-2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011-2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf) for a more thorough clarification.
This data represents the ratio of the mean income for the highest quintile (top 20 percent) of earners divided by the mean income of the lowest quintile (bottom 20 percent) of earners in a particular county. Multiyear estimates from the American Community Survey (ACS) are "period" estimates derived from a data sample collected over a period of time, as opposed to "point-in-time" estimates such as those from past decennial censuses. ACS 5-year estimate includes data collected over a 60-month period. The date of the data is the end of the 5-year period. For example, a value dated 2014 represents data from 2010 to 2014. However, they do not describe any specific day, month, or year within that time period. Multiyear estimates require some considerations that single-year estimates do not. For example, multiyear estimates released in consecutive years consist mostly of overlapping years and shared data. The 2010–2014 ACS 5-year estimates share sample data from 2011 through 2014 with the 2011–2015 ACS 5-year estimates. Because of this overlap, users should use extreme caution in making comparisons with consecutive years of multiyear estimates. Please see "Section 3: Understanding and Using ACS Single-Year and Multiyear Estimates" on publication page 13 (file page 19) of the 2018 ACS General Handbook for a more thorough clarification. https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018.pdf
For further information about this series go to https://www.census.gov/programs-surveys/saipe/about.html.
GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.
The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Poverty universe is one of the data sources used in producing SAIPE program estimates, it is made up of persons for whom the Census Bureau can determine poverty status (either "in poverty" or "not in poverty"). The definition of poverty universe for SAIPE estimates is the same for 2006 and beyond and conceptually matches the poverty universe of the American Community Survey (ACS). The poverty universe estimates are not the same as the population estimates from the Census Bureau's Population Estimates Program. Instead, they are derived estimates that differ from population estimates in the following ways: 1. The poverty universe does not include children under the age of 15 who are not related to a reference person within the household by way of birth, marriage or adoption (for example, foster children). The reason is that Census Bureau surveys typically ask income questions only of persons age 15 or older and those under 15 related to a reference person within the household. 2. Beginning with 2006, the poverty universe includes group quarters populations only for noninstitutionalized group quarters, not elsewhere classified. Residents of college dormitories, military housing, and all institutional group quarters populations are excluded. The 2005 poverty universe estimates excluded all group quarters' residents, matching the definition of the 2005 ACS. Prior to the estimates for 2005, the poverty universe data were derived from the Annual Social and Economic Supplement of the Current Population Survey. This marks a break in the data series due to a methodology change. See more details about SAIPE Model Input Data (https://www.census.gov/data/datasets/time-series/demo/saipe/model-tables.html).
For further information about this series go to https://www.census.gov/programs-surveys/saipe/about.html.
GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.
Estimate of the percentage of the population with a credit score below 660. Counties with fewer than 20 people in the sample are not reported for privacy reasons. The estimate is based on the representative primary sample of the New York Fed Consumer Credit Panel, which includes only the primary sample member per household (about 5% of the U.S. credit report population, defined as all U.S. residents with a credit history). For more details about the data and sample, see "An Introduction to the Consumer Credit Panel" (https://www.newyorkfed.org/research/staff_reports/sr479.html). Source: Federal Reserve Bank of New York/Equifax Consumer Credit Panel Reprinted with permission. Copyright © 2016, Equifax. All rights reserved. Reproduction of median credit score per county in any form is prohibited except with the prior written permission of Equifax.
Utility patents are patents for invention. Patent origin is determined by the residence of the first-named inventor. See Explanation of Data (https://www.uspto.gov/web/offices/ac/ido/oeip/taf/countyall/explan_countyall.htm) and Types of Patent Applications and Proceedings (https://www.uspto.gov/patents/basics/types-patent-applications/design-patent-application-guide) for more information.
An establishment is an economic unit, such as a factory, mine, store, or office that produces goods or services. It generally is at a single location and is engaged predominantly in one type of economic activity. Where a single location encompasses two or more distinct activities, these are treated as separate establishments, if separate payroll records are available, and the various activities are classified under different industry codes.
As stated by the source, these annual county indexes should be considered developmental. As with the standard FHFA HPIs, revisions to these indexes may reflect the impact of new data or technical adjustments. Indexes are calibrated using appraisal values and sales prices for mortgages bought or guaranteed by Fannie Mae and Freddie Mac. As discussed in the Working Paper 16-01, in cases where sample sizes are small for the county area, an index is either not reported if recording has not started or a missing value is reported with a period (.). Index values always reflect the native county index, i.e. they are not made with data from another area or year. For tracking and feedback purposes, please cite Working Paper 16-01 when using these data. A suggested form is: Bogin, A., Doerner, W. and Larson, W. (2016). Local House Price Dynamics: New Indices and Stylized Facts. Federal Housing Finance Agency, Working Paper 16-01. The working paper is accessible at http://www.fhfa.gov/papers/wp1601.aspx.
GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.
Data for "Resident Population" are estimates as of July 1. Data for 1970, 1980, 1990, and 2000 are annual census. Population estimates are updated annually using current data on births, deaths, and migration to calculate population change since the most recent decennial census. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. Each vintage of estimates includes all years since the most recent decennial census.
These data come from the Current Population Survey (CPS), also known as the household survey. Civilian Labor Force includes all persons in the civilian noninstitutional population ages 16 and older classified as either employed or unemployed. Employed persons are all persons who, during the reference week (the week including the 12th day of the month), (a) did any work as paid employees, worked in their own business or profession or on their own farm, or worked 15 hours or more as unpaid workers in an enterprise operated by a member of their family, or (b) were not working but who had jobs from which they were temporarily absent because of vacation, illness, bad weather, childcare problems, maternity or paternity leave, labor-management dispute, job training, or other family or personal reasons, whether or not they were paid for the time off or were seeking other jobs. Each employed person is counted only once, even if he or she holds more than one job. Unemployed persons are all persons who had no employment during the reference week, were available for work, except for temporary illness, and had made specific efforts to find employment some time during the 4 week-period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed. For more details, see the release's <a href=https://www.bls.gov/lau/laufaq.htm>frequently asked questions</a>.
This series represents the total number of building permits for all structure types. Structure types include 1-unit, 2-unit, 3-unit, 4-unit, and 5-unit or more.
For each time period represented in the tables, complete income reporters are ranked in ascending order, according to the level of total before-tax income reported by the consumer unit. The ranking is then divided into five equal groups. Incomplete income reporters are not ranked and are shown separately. For more details about the data or the survey, visit the FAQs (https://www.bls.gov/cex/csxfaqs.htm).
Source ID: FL645080073.Q For more information about the Flow of Funds tables, see the Financial Accounts Guide (https://www.federalreserve.gov/apps/fof/Default.aspx). With each quarterly release, the source may make major data and structural revisions to the series and tables. These changes are available in the Release Highlights (https://www.federalreserve.gov/apps/fof/FOFHighlight.aspx). In the Financial Accounts, the source identifies each series by a string of patterned letters and numbers. For a detailed description, including how this series is constructed, see the series analyzer (https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL645080073&t=) provided by the source.
The 10th percentile credit score among outstanding first liens. The current credit score is the most recently determined commercially available credit score of the primary borrower on the mortgage loan. The credit score provider may vary by FR Y-14M reporting firm and even within the firm's reporting. Only mortgage accounts with credit scores between 150 and 950 are included in the original credit score percentile calculations. For more detail see: methodology (https://www.philadelphiafed.org/-/media/frbp/assets/surveys-and-data/y14/y-14-data-methodology).
The 50th percentile first lien loan size originated in the observed quarter. These data include total bank loans originated and held in portfolio in a given quarter, including those that will later be sold or securitized. For more detail see: methodology (https://www.philadelphiafed.org/-/media/frbp/assets/surveys-and-data/y14/y-14-data-methodology).
Housing tenure refers to the family's principal place of residence during the survey. "Owner" includes families living in their own homes, cooperatives or condominium apartments, or townhouses. "Renter" includes families paying rent, as well as families living rent-free in lieu of wages. For more details about the data or the survey, visit the FAQs (https://www.bls.gov/cex/csxfaqs.htm).
Housing tenure refers to the family's principal place of residence during the survey. "Owner" includes families living in their own homes, cooperatives or condominium apartments, or townhouses. "Renter" includes families paying rent, as well as families living rent-free in lieu of wages. A consumer unit comprises either: (1) all members of a particular household who are related by blood, marriage, adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more persons living together who use their income to make joint expenditure decisions. Financial independence is determined by the three major expense categories: Housing, food, and other living expenses. To be considered financially independent, at least two of the three major expense categories have to be provided entirely, or in part, by the respondent. For more details about the data or the survey, visit the FAQs (https://www.bls.gov/cex/csxfaqs.htm).
The Mortgage Debt Outstanding table is no longer being updated as of March 2020. Many of the series that were published in this table can be found in the Z1 Financial Accounts of the United States release. The Z1 equivalent of this series is found at ASCMA. (https://fred.stlouisfed.org/series/ASCMA) For further information, please refer to the Board of Governors of the Federal Reserve System's Mortgage Debt Outstanding (http://www.federalreserve.gov/econresdata/releases/mortoutstand/current.htm).
Housing tenure refers to the family's principal place of residence during the survey. "Owner" includes families living in their own homes, cooperatives or condominium apartments, or townhouses. "Renter" includes families paying rent, as well as families living rent-free in lieu of wages. For more details about the data or the survey, visit the FAQs (https://www.bls.gov/cex/csxfaqs.htm).
The 75th percentile original loan-to-value (LTV) ratio. The original LTV ratio is the original loan amount divided by the lesser of the selling price or the appraised value of the property securing the mortgage at origination. Only mortgage accounts with LTV values greater than 0 percent and less than 125 percent are included in the original LTV percentile calculations.For more detail see: methodology (https://www.philadelphiafed.org/-/media/frbp/assets/surveys-and-data/y14/y-14-data-methodology).
This series has been discontinued and will no longer be updated. It was a duplicate of the following series, which will continue to be updated: https://fred.stlouisfed.org/series/AGSEBMPTCMAHDFS The FRED series Total Credit Market Debt Owed by Domestic Financial Sectors - Agency- and GSE-backed Mortgage Pools is now known as Agency-and GSE-Backed Mortgage Pools; Total Mortgages; Liability. The source series id is FL413065005.Q. This series appears in Table L.208. For further information see the assistance provided in the guide to the Financial Accounts at https://www.federalreserve.gov/apps/fof/.
For further information, please refer to the US Census Bureau's Annual Services release, online at http://www.census.gov/services/.
Source ID: FL413065505.Q For more information about the Flow of Funds tables, see the Financial Accounts Guide (https://www.federalreserve.gov/apps/fof/Default.aspx). With each quarterly release, the source may make major data and structural revisions to the series and tables. These changes are available in the Release Highlights (https://www.federalreserve.gov/apps/fof/FOFHighlight.aspx). In the Financial Accounts, the source identifies each series by a string of patterned letters and numbers. For a detailed description, including how this series is constructed, see the series analyzer (https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL413065505&t=) provided by the source.