A housing unit may be a house, an apartment, a mobile home, a group of rooms or a single room that is occupied (or, if vacant, intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other individuals in the building and which have direct access from outside the building or through a common hall. For vacant units, the criteria of separateness and direct access are applied to the intended occupants whenever possible. If that information cannot be obtained, the criteria are applied to the previous occupants.

Both occupied and vacant housing units are included in the housing unit inventory. Boats, recreational vehicles (RVs), vans, tents, railroad cars, and the like are included only if they are occupied as someone's current place of residence. Vacant mobile homes are included provided they are intended for occupancy on the site where they stand. Vacant mobile homes on dealers' sales lots, at the factory, or in storage yards are excluded from the housing inventory. Also excluded from the housing inventory are quarters being used entirely for nonresidential purposes, such as a store or an office, or quarters used for the storage of business supplies or inventory, machinery, or agricultural products.

Group Quarters (GQs) are places where people live or stay in a group living arrangement that is owned or managed by an entity or organization providing housing and/or services for the residents. These services may include custodial or medical care, as well as other types of assistance, and residency is commonly restricted to those receiving these services. People living in GQs usually are not related to each other. GQs include such places as college residence halls, residential treatment centers, skilled nursing facilities, group homes, military barracks, correctional facilities, workers' dormitories, and facilities for people experiencing homelessness. GQs are defined according to the housing and/or services provided to residents and are identified by Census GQ type codes.

In January 2006, the American Community Survey (ACS) was expanded to include the population living in GQ facilities. The ACS GQ sample encompasses 12 independent samples; like the housing unit (HU) sample, a new GQ sample is introduced each month.

The GQ data collection lasts only 6 weeks and does not include a formal nonresponse followup operation. The GQ data collection operation is conducted in two phases. First, U.S. Census Bureau Field Representatives (FRs) conduct interviews with the GQ facility contact person or administrator of the selected GQ (GQ level), and second, the FR conducts interviews with a sample of individuals from the facility (person level).

The GQ-level data collection instrument is an automated Group Quarters Facility Questionnaire (GQFQ). Information collected by the FR using the GQFQ during the GQlevel interview is used to determine or verify the type of facility, population size, and the sample of individuals to be interviewed. FRs conduct GQ-level data collection at approximately 20,000 individual GQ facilities each year.

A list of the GQ facilities (and their respective type codes) that are in scope for the 2019 ACS can be found in the 2019 Code List on the ACS website. Go to http://www.census.gov and enter “ACS Code Lists, Definitions, and Accuracy” in the search box.

The data on acreage were obtained from Housing Question 4 in the 2019 American Community Survey (ACS). This question was asked at occupied and vacant one-family houses and mobile homes. The data for vacant units were obtained by asking a neighbor, real estate agent, building manager, or anyone else who had knowledge of the vacant unit in question.

This question determines a range of acres (cuerdas) on which the house or mobile home is located. A major purpose for this question, in conjunction with Housing Question 5 on agricultural sales, is to identify farm units. In previous ACS questionnaires and in Census 2000, this question was used to determine single-family homes on 10 or more acres (cuerdas). The land may consist of more than one tract or plot. These tracts or plots are usually adjoining; however, they may be separated by a road, creek, another piece of land, etc.

In the ACS prior to 2004 and in Census 2000, acreage was one of the variables used to determine specified owner- and renter-occupied housing units.

Question/Concept History - The 1996-1998 question asked, "Is this house or mobile home on less than 1 acre, 1 to less than 10 acres, or 10 or more acres.” Since 1999, the question wording was changed to ask, "How many acres is this house or mobile home on?" and the second response category was modified to "1 to 9.9 acres." (In the Puerto Rico Community Survey, the question wording was changed to ask about cuerdas instead of acres.)

Comparability - Data on acreage in the 2019 ACS can be compared to previous ACS and Census 2000 acreage data.

Data on the sales of agricultural crops were obtained from Housing Question 5 in the 2019 American Community Survey. The question was asked at occupied one-family houses and mobile homes located on lots of 1 or more acres. Data for this question exclude units on lots of less than 1 acre, units located in structures containing two or more units, and all vacant units. This question refers to the total amount (before taxes and expenses) received in the 12 months prior to the interview, from the sale of crops, vegetables, fruits, nuts, livestock and livestock products, and nursery and forest products, produced on "this property." Respondents new to a unit were to estimate total agricultural sales from the 12 months prior to the interview even if some portion of the sales had been made by previous occupants of the unit.

This question is used mainly to classify housing units as farm or nonfarm residences, not to provide detailed information on the sale of agricultural products. Detailed information on the sale of agricultural products is provided by the Census of Agriculture, which is conducted by the U.S. Department of Agriculture/National Agricultural Statistics Service (see http://www.agcensus.usda.gov/).

Question/Concept History - On the 1996-1998 American Community Survey questionnaires, there were just two response categories to indicate whether or not the amount of sales was over $1,000. Since 1999, the question has included a series of response categories for the amount of the agricultural sales.

Comparability - Data on agricultural sales in the 2019 American Community Survey can be compared to previous ACS and Census 2000 agricultural sales data.

The data on bedrooms were obtained from Housing Question 6b in the 2019 American Community Survey. The question was asked at both occupied and vacant housing units. The number of bedrooms is the count of rooms designed to be used as bedrooms, that is, the number of rooms that would be listed as bedrooms if the house, apartment, or mobile home were on the market for sale or for rent. Included are all rooms intended to be used as bedrooms even if they currently are being used for some other purpose. A housing unit consisting of only one room is classified, by definition, as having no bedroom.

Bedrooms provide the basis for estimating the amount of living and sleeping spaces within a housing unit. These data allow officials to evaluate the adequacy of the housing stock to shelter the population, and to determine any housing deficiencies in neighborhoods. The data also allow officials to track the changing physical characteristics of the housing inventory over time.

Question/Concept History - The 1996-1998 American Community Survey question provided a response category for "None" and space for the respondent to enter a number of bedrooms. From 1999-2007, the question provided pre-coded response categories from "No bedroom" to "5 or more bedrooms." Starting in 2008, the question became the second part of a two-part question that linked the number of "rooms" and number of "bedrooms" questions together. In addition, the wording of the question was changed to ask, "How many of these rooms are bedrooms?" Additional changes introduced in 2008 included removing the pre- coded response categories and adding a write-in box for the respondent to enter the number of bedrooms, providing the rule to use for defining a "bedroom" as an instruction, and providing an additional instruction addressing efficiency and studio apartments - "If this is an efficiency/studio apartment, print '0'."

Limitation of the Data - The Census Bureau tested the changes introduced to the 2008 version of the bedrooms question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Rooms and Bedrooms" on the ACS website (http://www.census.gov/acs).

Comparability - Caution should be used when comparing American Community Survey data on bedrooms from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the bedrooms question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in "No bedroom" responses and as a decrease in "1 bedroom" to "3 bedrooms" responses.

The 2008 Broadband Improvement Act mandated the collection of data about computer and internet use. As a result, three questions were added to the 2013 American Community Survey (ACS) to measure these topics. Data about computer and internet use were derived from answers to Question 8, Question 9, and Question 10 on the 2019 ACS, and are asked of all occupied housing units.

The computer use question (Question 8) asked if anyone in the household owned or used a computer and included four response categories for a desktop or laptop, a smartphone, a tablet or other portable wireless computer, and some other type of computer. Respondents selected a checkbox for "Yes" or "No" for each response category. Respondents could select all categories that applied.

Respondents who checked "Yes" for the some other type of computer category are asked to write in descriptions of their other computer type(s). These are mostly used for internal purposes and to verify whether the household has some other type of computer, although some people may write in a type of computer that can be reclassified as a desktop or laptop, a smartphone, or a tablet or other portable wireless computer. Question 9 asked if any member of the household has access to the internet. "Access" refers to whether or not someone in the household uses or can connect to the internet, regardless of whether or not they pay for the service. Respondents were to select only ONE of the following choices:

Yes, by paying a cell phone company or Internet service provider- This category includes housing units where someone pays to access the internet through a service such as a data plan for a smartphone; a broadband internet service such as cable, fiber optic or DSL; satellite; dial-up; or other type of service. This will normally refer to a service that someone is billed for directly for internet alone or sometimes as part of a bundle. Yes, without paying a cell phone company or Internet service provider- Some respondents may live in a city or town that provides free internet service for their residents. In addition, some colleges or universities provide internet service. These are examples of cases where respondents may be able to access the internet without a subscription.

No access to the Internet at this house, apartment, or mobile home- This category includes housing units where no one can connect to or uses the internet using a paid service or any free service.

If a respondent answers "Yes, by paying a cell phone company or Internet service provider" to Question 9, they are asked to select the type of internet service in Question 10. Respondents select a checkbox for "Yes" or "No" for each of five types of service:

a.) cellular data plan for a smartphone or other mobile device,

b.) broadband (high speed) Internet service such as cable, fiber optic, or DSL,

c.) satellite,

d.) dial-up or

e.) some other service.

Respondents could select "Yes" for all categories that apply. If a respondent selected "Yes" to the "some other service" category, they are asked to write in a description of the type of internet service. These codes are primarily used internally and to verify whether the household has some other service, although some people may write in a type of internet service that can be reclassified into one of the other categories such as broadband or satellite service.

These data are used by a variety of government agencies, local communities, and other data users. The Federal Communications Commission (FCC) use these statistics to measure the nationwide development of broadband access, as well as the successful deployment of the next generation of broadband technology. These data also allow the FCC to develop measures to increase access to broadband technology and decrease barriers.

The National Telecommunications and Information Administration (NTIA) use these data to provide grants that help expand public access to broadband service and fund broadband education and support, particularly to groups that have traditionally underutilized broadband technology.

State and local governments can use these data to evaluate access to broadband in their communities, and institute policies and programs to increase access for areas with less connectivity. Businesses and non-profits can use these statistics to analyze computer and internet usage in their communities.

Question/Concept History - The computer and internet use questions were added to the ACS in 2013 and were mandated by the 2008 Broadband Improvement Act. In 2016, questions 8 (computer use) and 10 (type of internet service) were revised to improve the measurement of internet subscriptions and cellular data planes, as well as adjusting response categories for types of computers to account for changes in the types of computers available and the terminology used to describe them.

Limitation of the Data - These questions are not asked for the group quarters population, so do not include data about people living in housing such as dorms, prisons, nursing homes, etc.

Comparability - Data prior to 2013 are not available because 2013 was the first year that these questions were collected using the ACS. For more information, go to http://www.census.gov and enter "Comparing ACS Data" in the search box.

Caution should be used when comparing pre-2016 estimates due to question revisions. Observed changes may be due to the revised wording used in the questions and improved measurement rather than a change in use. For more information, go to http://www.census.gov and enter "Computer and Internet Use in the United States: 2016" in the search box.

The Current Population Survey (CPS) has periodically collected data about computer use since 1984 and about internet use since 1997. Both surveys exclude those living in group quarters. However, users should note CPS data are not necessarily comparable to ACS data in several important ways. First, unlike the ACS, some CPS questions are asked at the person level. In addition, the CPS questions and answer categories have changed multiple times over the years. Therefore, comparable data may not be available for certain questions during some years. In addition, some questions may appear to have similar wording as the ACS questions, but may not have been asked of the same type of people. Finally, weighting procedures differ between the two surveys.

The data on condominium housing units were obtained from Housing Question 15 in the 2019 American Community Survey (ACS). The question was asked at occupied housing units.

The data on contract rent (also referred to as "rent asked" for vacant units) were obtained from Housing Question 17a in the 2019 American Community Survey (ACS). The question was asked at renter-occupied housing units, and vacant housing units that were for rent, and vacant units rented but not occupied at the time of interview.

Housing units that are renter occupied without payment of rent are shown separately as "No rent paid." The unit may be owned by friends or relatives who live elsewhere and who allow occupancy without charge. Rent-free houses or apartments may be provided to compensate caretakers, ministers, tenant farmers, sharecroppers, or others.

Contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings, utilities, fees, meals, or services that may be included. For vacant units, it is the monthly rent asked for the rental unit at the time of interview.

If the contract rent includes rent for a business unit or for living quarters occupied by another household, only that part of the rent estimated to be for the respondent's unit was included. Excluded was any rent paid for additional units or for business premises.
If a renter pays rent to the owner of a condominium or cooperative, and the condominium fee or cooperative carrying charge also is paid by the renter to the owner, the condominium fee or carrying charge was included as rent.

If a renter receives payments from lodgers or roomers who are listed as members of the household, the rent without deduction for any payments received from the lodgers or roomers, was to be reported. The respondent was to report the rent agreed to or contracted for even if paid by someone else such as friends or relatives living elsewhere, a church or welfare agency, or the government through subsidies or vouchers.

Contract rent provides information on the monthly housing cost expenses for renters. When the data is used in conjunction with utility costs and income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance to agencies in determining policies on fair rent.

The data on Food Stamp benefits were obtained from Housing Question 14 in the 2019 American Community Survey (ACS). The Food Stamp Act of 1977 defines this federallyfunded program as one intended to "permit low-income households to obtain a more nutritious diet" (from Title XIII of Public Law 95-113, The Food Stamp Act of 1977, declaration of policy). Food purchasing power is increased by providing eligible households with coupons or cards that can be used to purchase food. The Food and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA) administers the Food Stamp Program through state and local welfare offices. The Food Stamp Program is the major national income support program to which all low-income and low-resource households, regardless of household characteristics, are eligible. In Puerto Rico, the program is named the Nutrition Assistance Program (NAP).

On October 1, 2008, the Federal Food Stamp program was renamed SNAP (Supplemental Nutrition Assistance Program).

Respondents were asked if one or more of the current members received food stamps or a food stamp benefit card during the past 12 months. Respondents were also asked to include benefits from the Supplemental Nutrition Assistance Program (SNAP) in order to incorporate the program name change.

Question/Concept History - The 1996-1998 American Community Survey asked for a 12- month amount for the value of the food stamps following the Yes response category. For the 1999-2002 ACS, the words "Food Stamps" were capitalized in the question following the Yes response category, and the instruction "Past 12 months' value - Dollars" was added. Since 2003, the words "received during the past 12 months" were added to the question following the Yes response category. Beginning in 2008, the value of food stamps received was no longer collected; the wording of the question was changed from "At anytime during the past 12 months" to "In the past 12 months," and the term '"food stamp benefit card' was added.
Adding the text "food stamps benefit card" to the question text and removing the dollar amount portion of the question resulted in a statistically significant increase in the recipiency rate for food stamps because of a decrease in item nonresponse rate.

Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Many types of GQ populations have food stamp distributions that are very different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the food stamp distribution. This is particularly true for areas with a substantial GQ population.

The Census Bureau tested the changes introduced to the 2008 version of the Food Stamp benefits question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008, see "2006 ACS Content Test Evaluation Report Covering Receipt Food Stamps" on the ACS website (http://www.census.gov).

Comparability - The Food Stamp/SNAP question is not asked in Census 2000. Because of the wording change on the 2008 ACS questionnaire, you cannot compare data before and after 2008.

The data on gross rent were obtained from answers to Housing Questions 13a-d and 17a in the 2019 American Community Survey (ACS). 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. Renter units occupied without payment of rent are shown separately as "No rent paid" in the tabulations.

Gross rent provides information on the monthly housing cost expenses for renters. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels and to provide assistance to agencies in determining policies on fair rent

Gross rent as a percentage of household income is a computed ratio of monthly gross rent to monthly household income (total household income divided by 12). The ratio is computed separately for each unit and is rounded to the nearest tenth. Units for which no rent is paid and units occupied by households that reported no income or a net loss comprise the category, "Not computed."

Gross rent as a percentage of household income provides information on the monthly housing cost expenses for renters. The information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance to agencies in determining policies on fair rent.

See Vacancy Status.

The data on house heating fuel were obtained from Housing Question 12 in the 2019 American Community Survey (ACS). The question was asked at occupied housing units. The data show the type of fuel used most to heat the house, apartment, or mobile home.

House heating fuel provides information on energy supply and consumption. These data are used by planners to identify the types of fuel used in certain areas and the consequences this usage may have on the area. The data also serve to aid in forecasting the need for future energy needs and power facilities such as generating plants, long distance pipelines for oil or natural gas, and long distance transmission lines for electricity.

House heating fuel is categorized on the ACS questionnaire as follows:

Utility Gas - This category includes gas piped through underground pipes from a central system to serve the neighborhood.

Bottled, Tank, or LP Gas - This category includes liquid propane gas stored in bottles or tanks that are refilled or exchanged when empty.

Electricity - This category includes electricity that is generally supplied by means of above or underground electric power lines.

Fuel Oil, Kerosene, etc. - This category includes fuel oil, kerosene, gasoline, alcohol, and other combustible liquids.

coal or coke - This category includes coal or coke that is usually distributed by truck.

Wood - This category includes purchased wood, wood cut by household members on their property or elsewhere, driftwood, sawmill or construction scraps, or the like.

Solar Energy - This category includes heat provided by sunlight that is collected, stored, and actively distributed to most of the rooms.

Other Fuel - This category includes all other fuels not specified elsewhere.

No Fuel used - This category includes units that do not use any fuel or that do not have heating equipment.

Question/Concept History - Since 1996, the American Community Survey questions have remained the same.

Comparability - Data on house heating fuel in the 2013 American Community Survey can be compared to previous ACS and Census 2000 house heating fuel data.

This question is based on the count of people in occupied housing units. All people occupying the housing unit are counted, including the householder, occupants related to the householder, and lodgers, roomers, boarders, and so forth.

See Living Quarters.

The data on fire, hazard, and flood insurance were obtained from Housing Question 20 in the 2019 American Community Survey (ACS). The question was asked of owner-occupied units. The statistics for this question refer to the annual premium for fire, hazard, and flood insurance on the property (land and buildings), that is, policies that protect the property and its contents against loss due to damage by fire, lightning, winds, hail, flood, explosion, and so on.

Liability policies are included only if they are paid with the fire, hazard, and flood insurance premiums and the amounts for fire, hazard, and flood cannot be separated. Premiums are reported even if they have not been paid or are paid by someone outside the household. When premiums are paid on other than a yearly basis, the premiums are converted to a yearly basis.

The payment for fire, hazard, and flood insurance is added to payments for real estate taxes, utilities, fuels, and mortgages (both first, second, home equity loans, and other junior mortgages) to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income." These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.

A separate question (21d in the 2019 American Community Survey) determines whether insurance premiums are included in the mortgage payment to the lender(s). This makes it possible to avoid counting these premiums twice in the computations.

See Computer and Internet Use.

Data on kitchen facilities were obtained from Housing Question 7c-e in the 2019 American Community Survey (ACS). The question was asked at both occupied and vacant housing units. A unit has complete kitchen facilities when it has all three of the following facilities:(c) a sink with a faucet, (d) a stove or range, and (e) a refrigerator. All kitchen facilities must be located in the house, apartment, or mobile home, but they need not be in the same room. A housing unit having only a microwave or portable heating equipment such as a hot plate or camping stove should not be considered as having complete kitchen facilities. An icebox is not considered to be a refrigerator.

Kitchen facilities provide an indication of living standards and assess the quality of household facilities within the housing inventory. These data provide assistance in determining areas that are eligible for programs and funding, such as Meals on Wheels. The data also serve to aid in the development of policies based on fair market rent, and to identify areas in need of rehabilitation loans or grants.

Question/Concept History

The 1996-1998 American Community Survey questions asked whether the house or apartment had complete kitchen facilities, requiring that the three facilities all be in the same unit. In 1999, "mobile home" was added to the question, along with the capitalization of the word "COMPLETE" for emphasis. Starting in 2008, the structure of the question changed and combined kitchen facilities with plumbing facilities and telephone service availability into one question to ask, "Does this house, apartment, or mobile home have-" and provided the respondent with a "Yes" or "No" checkbox for each component needed for complete facilities. Also in 2008, the component "sink with piped water" was changed to "sink with a faucet."

Comparability

Caution should be used when comparing American Community Survey data on kitchen facilities from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the kitchen facilities question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in housing units "lacking complete kitchen facilities."

The data on meals included in the rent were obtained from Housing Question 17b in the 2019 American Community Survey (ACS). The question was asked of occupied housing units that were rented and vacant housing units that were for rent or rented but not yet occupied at the time of enumeration. These data only include rental units, which meals are included in the rent, or if occupants contract for either their meals or a meal plan in order to live in the unit. Renters in continuing care or life facilities are included in this category if their contracts cover meal services.

The meals included in rent allows for a measurement on the amount of congregate housing within the housing inventory. Congregate housing is considered to be housing units where the rent includes meals and other services.

Question/Concept History

Since 1996, the American Community Survey questions have been the same. Starting in 2004, meals included in rent is shown for all renter-occupied housing units. In previous years (1996-2003), it was shown only for specified renter- occupied housing units.

Comparability

Data on meals included in rent in the 2019 ACS should not be compared to Census 2000 meals included in rent data. For Census 2000, tables were not released for total renter-occupied units. The universe in Census 2000 was "specified renter-occupied housing units" whereas the universe in the ACS is "renter occupied housing units," thus comparisons cannot be made between these two data sets.

The data on mobile home costs were obtained from Housing Question 23 in the 2019 American Community Survey (ACS). The question was asked at owner-occupied mobile homes.
These data include the total yearly costs for personal property taxes, land or site rent, registration fees, and license fees on all owner-occupied mobile homes. The instructions are to exclude real estate taxes already reported in Question 19. Additionally, the mobile home costs exclude installment loan payments on the purchase of the mobile home, as respondents are instructed to include these payments in Question 21b about the mortgage payment amount.

Costs are estimated as closely as possible when exact costs are not known. Amounts are the total for an entire 12-month billing period, even if they are paid by someone outside the household or remain unpaid.

The data from this question are added to payments for mortgages; real estate taxes; fire, hazard, and flood insurance payments; utilities; and fuels to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for mobile home owners. These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.

Question/Concept History

The 1996-1998 American Community Survey questions were the same. Between 1999 and 2002, the question had a lead-in question on whether the respondent had an installment loan or a contract on the mobile home. The question then asked for total costs including any installment loan.

Comparability

Data on mobile home costs in the 2019 ACS can be compared to previous ACS and Census 2000 mobile home costs data.

The data for monthly housing costs are developed from a distribution of "Selected Monthly Owner Costs" for owner-occupied units and "Gross Rent" for renter-occupied units. The owner-occupied categories are further separated into those with a mortgage and those without a mortgage. See the sections on "Selected Monthly Owner Costs" and "Gross Rent" for more details on what characteristics are included in each measure and how these data are comparable to previous ACS and Census 2000 data.

Monthly housing costs provide information on the cost of monthly housing expenses for owners and renters. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

The data for monthly housing costs as a percentage of household income are developed from a distribution of "Selected Monthly Owner Costs as a Percentage of Household Income" for owner-occupied and "Gross Rent as a Percentage of Household Income" for renter-occupied units. The owner-occupied categories are further separated into those with a mortgage and those without a mortgage. See sections on "Selected Monthly Owner Costs as a Percentage of Household Income" and "Gross Rent as a Percentage of Household Income" for more details on what characteristics are included in each measure and how these data are comparable to previous ACS and Census 2000 data.

Monthly housing costs as a percentage of household income provide information on the cost of monthly housing expenses for owners and renters. The information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

The data on mortgage payment were obtained from Housing Question 21b in the 2019 American Community Survey (ACS). The question was asked at owner-occupied units that have a mortgage, deed of trust, or similar debt; or contract to purchase. The question provides the regular monthly amount required to be paid to the lender for the first mortgage (deed of trust, contract to purchase, or similar debt) on the property. Amounts are included even if the payments are delinquent or paid by someone else. The amounts reported are included in the computation of "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for units with a mortgage.

The amounts reported include everything paid to the lender including principal and interest payments, real estate taxes, fire, hazard, and flood insurance payments, and mortgage insurance premiums. Separate questions determine whether real estate taxes and fire, hazard, and flood insurance payments are included in the mortgage payment to the lender. This makes it possible to avoid counting these components twice in the computation of "Selected Monthly Owner Costs."
Mortgage payment provides information on the monthly housing cost expenses for owners with a mortgage. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs aimed to meet the needs of people at different economic levels.

Question/Concept History

Since 1996, the American Community Survey questions have been the same.

Comparability

Data on mortgage payment in the 2019 ACS can be compared to previous ACS and Census 2000 mortgage payment data. For Census 2000, tables for both total owner-occupied housing units and specified owner-occupied housing units were released, thus comparisons can be made only when comparing the same universes between the two data sets.

The data on mortgage status were obtained from Housing Questions 21a and 22a in the 2019 American Community Survey (ACS). The questions were asked at owner-occupied units. "Mortgage" refers to all forms of debt where the property is pledged as security for repayment of the debt, including deeds of trust; trust deeds; contracts to purchase; land contracts; junior mortgages; and home equity loans.

A mortgage is considered a first mortgage if it has prior claim over any other mortgage or if it is the only mortgage on the property. All other mortgages (second, third, etc.) are considered junior mortgages. A home equity loan is generally a junior mortgage. If no first mortgage is reported, but a junior mortgage or home equity loan is reported, then the loan is considered a first mortgage.

In most data products, the tabulations for "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" usually are shown separately for units "with a mortgage" and for units "not mortgaged." The category "not mortgaged" is comprised of housing units owned free and clear of debt.

Mortgage status provides information on the cost of home ownership. When the data is used in conjunction with mortgage payment data, the information determines shelter costs for living quarters. These data can be used in the development of housing programs aimed to meet the needs of people at different economic levels.

Question/Concept History

Since 1996, the American Community Survey for mortgage status questions have been the same.

Comparability

Data on mortgage status in the 2019 ACS can be compared to previous ACS and Census 2000 mortgage status data. For Census 2000, tables for both total owneroccupied housing units and specified owner-occupied housing units were released, thus comparisons can be made only when comparing the same universes between the two data sets.

Occupants per room is obtained by dividing the reported number of current residents in each occupied housing unit by the number of rooms in the unit. The figures show the number of occupied units having the specified ratio of current residents per room. Occupants per room is rounded to the nearest hundredth.
This data is the basis for estimating the amount of living and sleeping spaces within a housing unit. The data also serve to aid in planning for future services and infrastructure, such as home energy assistance programs and the development of waste treatment facilities.

Comparability

Caution should be used when comparing American Community Survey data on occupants per room from the years 2008 and after with both pre-2008 data. Changes made to the rooms question between the 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable in a 2006 content test with the revised question showing an increase in "1 room" responses, decrease in "2 rooms" to "6 rooms" responses, and increases in "7 rooms" and "9 or more" room responses, with an overall increase in the median number of rooms reported using the revised question.

Data on occupants per room in the American Community Survey should be compared with great caution to Census 2000 data due to: 1) differences in residence rules and the absence of population controls used to adjust for undercoverage in the reported number of current residents in the ACS used in this measure and 2) differences in the reported number of rooms due to changes in the rooms question between the 2007 and 2008 ACS.

See Living Quarters.

See Tenure.

The data on plumbing facilities were obtained from Housing Question 7a and b in the 2019 American Community Survey (ACS). The question was asked at both occupied and vacant housing units. Complete plumbing facilities include: (a) hot and cold running water and (b) a bathtub or shower. Both facilities must be located inside the house, apartment, or mobile home, but not necessarily in the same room. Housing units are classified as lacking complete plumbing facilities when any of the two facilities is not present.

Plumbing facilities provide an indication of living standards and assess the quality of household facilities within the housing inventory. These data provide assistance in the assessment of water resources and to serve as an aid to identify possible areas of ground water contamination. The data also are used to forecast the need for additional water and sewage facilities, aid in the development of policies based on fair market rent, and to identify areas in need of rehabilitation loans or grants.

Question/Concept History

The 1996-2007 American Community Survey questions were stand-alone questions that asked the respondent to answer either "Yes, has all three facilities" or "No" to the question of whether the housing unit had complete plumbing facilities, requiring that the facilities all be in the same unit. Starting in 2008, the structure of the question changed and combined plumbing facilities with kitchen facilities and telephone service availability into one question to ask, "Does this house, apartment, or mobile home have -" and provided the respondent with a "Yes" or "No" checkbox for each component needed for complete facilities. An additional change introduced in 2008 included changing the description of the component "hot and cold piped water" to "hot and cold running water."

Comparability

Caution should be used when comparing ACS data on plumbing facilities from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the plumbing facilities question between 2007 and 2008 ACS involving the wording as well as the response option resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in housing units "lacking complete plumbing facilities." This increase in housing units "lacking complete plumbing" was most noticeable in Puerto Rico, when a component of complete plumbing was hot and cold running water. Due to the temperate climate there, hot water was not common there; thus many housing units that would have had complete plumbing under "Yes, has all three facilities" did not under the 2008 through 2012 questions. By 2013, the problem with the Puerto Rico complete plumbing had been fixed making 2013 plumbing for Puerto Rico comparable with pre-2008.

The data shown for population in occupied units is the total population minus any people living in group quarters. All people occupying the housing unit are counted, including the householder, occupants related to the householder, and lodgers, roomers, boarders, and so forth.

Population in occupied housing units provides information on the population within the housing inventory. The data allow the identification of population patterns within areas to assist in developing housing programs. These data also serve to aid officials in tracking the changing population characteristics of the housing inventory over time.

Comparability

Data on the population in occupied housing units in the 2019 American Community Survey (ACS) can be compared to previous ACS data. The ACS estimates of occupied housing units differ from those obtained from the 2010 Census. For more information, see "Comparing 2010 American Community Survey 1-Year Estimates of Occupancy Status, Vacancy Status, and Household Size with the 2010 Census - Preliminary Results" on the Census website. Go to http://www.census.gov and enter the paper title in the search box.

The data on poverty status of households were derived from answers to the income questions. Since poverty is defined at the family level and not the household level, the poverty status of the household is determined by the poverty status of the householder. Households are classified as poor when the total income of the householder's family is below the appropriate poverty threshold. (For nonfamily householders, their own income is compared with the appropriate threshold.) The income of people living in the household who are unrelated to the householder is not considered when determining the poverty status of a household, nor does their presence affect the family size in determining the appropriate threshold. The poverty thresholds vary depending on three criteria: size of family, number of related children, and, for 1- and 2-person families, age of householder. See the table "The 2018 Poverty Factors" in Appendix A. (For more information, see "Poverty Status in the Past 12 Months" and "Income in the Past 12 Months" under "Population Variables.")

The data on real estate taxes were obtained from Housing Question 19 in the 2019 American Community Survey (ACS). The question was asked at owner-occupied units. The statistics from this question refer to the total amount of all real estate taxes on the entire property (land and buildings) payable to all taxing jurisdictions, including special assessments, school taxes, county taxes, and so forth.

Real estate taxes include state, local, and all other real estate taxes even if delinquent, unpaid, or paid by someone who is not a member of the household. However, taxes due from prior years are not included. If taxes are paid on other than a yearly basis, the payments are converted to a yearly basis.
The payment for real estate taxes is added to payments for fire, hazard, and flood insurance; utilities and fuels; and mortgages (both first and second mortgages, home equity loans, and other junior mortgages) to derive "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income." These data provide information on the cost of home ownership and offer an excellent measure of housing affordability and excessive shelter costs.
A separate question (Question 21c in the 2019 ACS) determines whether real estate taxes are included in the mortgage payment to the lender(s). This makes it possible to avoid counting taxes twice in the computations.

Question/Concept History

Since 1996, the American Community Survey questions have been the same.

Comparability

Data on real estate taxes in the 2019 ACS should not be compared to Census 2000 real estate taxes data. The universe in Census 2000 was "specified owner-occupied housing units" whereas the universe in the ACS is "owner occupied housing units," thus comparisons cannot be made between these two data sets.

See Contract Rent.

See Vacancy Status.

See Tenure.

The data on rooms were obtained from Housing Question 6a in the 2019 American Community Survey (ACS). The question was asked at both occupied and vacant housing units. The statistics on rooms are in terms of the number of housing units with a specified number of rooms. The intent of this question is to count the number of whole rooms used for living purposes.

For each unit, rooms include living rooms, dining rooms, kitchens, bedrooms, finished recreation rooms, enclosed porches suitable for year-round use, and lodger's rooms. Excluded are strip or pullman kitchens, bathrooms, open porches, balconies, halls or foyers, half-rooms, utility rooms, unfinished attics or basements, or other unfinished space used for storage. A partially divided room is a separate room only if there is a partition from floor to ceiling, but not if the partition consists solely of shelves or cabinets.

Rooms provide the basis for estimating the amount of living and sleeping spaces within a housing unit. These data allow officials to plan and allocate funding for additional housing to relieve crowded housing conditions. The data also serve to aid in planning for future services and infrastructure, such as home energy assistance programs and the development of waste treatment facilities.

The data on second mortgages or home equity loan payments were obtained from Housing Questions 22a and 22b in the 2019 American Community Survey (ACS). The questions were asked at owner-occupied units. Question 22a asks whether a second mortgage or a home equity loan exists on the property. Question 22b provides the regular monthly amount required to be paid to the lender on all second and junior mortgages and home equity loans. Amounts are included even if the payments are delinquent or paid by someone else. The amounts reported are included in the computation of "Selected Monthly Owner Costs" and "Selected Monthly Owner Costs as a Percentage of Household Income" for units with a mortgage.

All mortgages other than first mortgages (for example, second, third, etc.) are classified as "junior" mortgages. A second mortgage is a junior mortgage that gives the lender a claim against the property that is second to the claim of the holder of the first mortgage. Any other junior mortgage(s) would be subordinate to the second mortgage. A home equity loan is a line of credit available to the borrower that is secured by real estate. It may be placed on a property that already has a first or second mortgage, or it may be placed on a property that is owned free and clear.

If the respondents answered that no first mortgage existed, but a second mortgage or a home equity loan did, a computer edit assigned the unit a first mortgage and made the first mortgage monthly payment the amount reported in the second mortgage. The second mortgage/home equity loan data were then made "No" in Question 22a and blank in Question 22b.

Second mortgage or home equity loan data provide information on the monthly housing cost expenses for owners. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs aimed to meet the needs of people at different economic levels.

By listing the second mortgage or home equity loan question separately on the questionnaire from other housing cost questions, the data also serve to improving the accuracy of estimating monthly housing costs for mortgaged owners.

Question/Concept History

Since 1996, the American Community Survey questions remained the same.

Comparability

Data on second mortgages in the 2019 ACS should not be compared to Census 2000 second mortgage data. For Census 2000, while some tables were released for total owner-occupied units, second mortgage was not. The universe in Census 2000 was "specified owner-occupied housing units" whereas the universe in the ACS is "owneroccupied housing units," thus comparisons cannot be made between these two data sets.

The variable "Selected Conditions" is defined for owner- and renter-occupied housing units as having at least one of the following conditions:

1) lacking complete plumbing facilities,

2) lacking complete kitchen facilities,

3) with 1.01 or more occupants per room,

4) selected monthly owner costs as a percentage of household income greater than 30 percent, and

5) gross rent as a percentage of household income greater than 30 percent.

Selected conditions provide information in assessing the quality of the housing inventory and its occupants. The data is used to easily identify those homes in which the quality of living and housing can be considered substandard.

Comparability

Data on selected conditions in the 2019 American Community Survey (ACS) can be compared to previous ACS and Census 2000 selected conditions data.

The data on selected monthly owner costs were obtained from Housing Questions 13, 15, and Questions 19 through 23 in the 2019 American Community Survey (ACS). The data were obtained for owner-occupied units. 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 (Question 15) and mobile home costs (Question 23) (personal property taxes, site rent, registration fees, and license fees). Selected monthly owner costs were tabulated for all owner-occupied units, and usually are shown separately for units "with a mortgage" and for units "not mortgaged."

Selected monthly owner costs provide information on the monthly housing cost expenses for owners. When the data is used in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

The information on selected monthly owner costs as a percentage of household income is the computed ratio of selected monthly owner costs to monthly household income. The ratio was computed separately for each unit and rounded to the nearest whole percentage. The data are tabulated only for owner-occupied units.

Separate distributions are often shown for units "with a mortgage" and for units "not mortgaged." Units occupied by households reporting no income or a net loss are included in the "not computed" category. (For more information, see the discussion under "Selected Monthly Owner Costs.")

Selected monthly owner costs as a percentage of household income provide information on the monthly housing cost expenses for owners. The information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels.

Specified owner-occupied units include only 1-family houses on less than 10 acres (cuerdas) without a business or medical office on the property. The data for "specified units" exclude mobile homes, houses with a business or medical office, houses on 10 or more acres (cuerdas), and housing units in multiunit buildings.

Specified owner-occupied and vacant-for-sale housing unit information was used to maintain a comparable universe between the American Community Survey (ACS) and earlier census data. Owner costs, owner costs as a percentage of income, and value for owner-occupied and asking price for vacant-for-sale housing units in earlier census data were based on specified owner-occupied and vacant-for-sale housing units; however, beginning in 2004 the ACS no longer published information solely for this universe. Rather, the ACS began publishing information for all owner-occupied and vacant-for-sale and sold, not occupied housing units. The characteristics for a specified owner housing unit as well as a single variable that combines all the characteristics necessary to be a specified unit into one variable are maintained within the ACS Public Use Microdata Sample (PUMS) file. Through 2015 then, comparisons between the two data sets can be made by using the PUMS. In 2016, ACS stopped asking the business or medical office on property question, the lack of which was formerly a characteristic of specified. So, although there is still the single variable that combines all the characteristics for specified owner housing in 2016 on the PUMS, it is not comparable to preceding years which had the requirement of no business or medical office on property.

Question/Concept History

Prior to 1990, much of the owner-occupied housing inventory was comprised of single-family homes, either detached or attached. Therefore, earlier census data provided financial housing characteristics for the specified owner-occupied unit universe. However, the housing market began to change during the 1990's as an increasing number of units in multiunit structures were constructed and sold as condominiums, as well as the increase of mobile homes as an option for lower-income owners to purchase a home. As a result of these changes, the ACS abandoned the concept of the specified owner- occupied universe to ensure housing data was provided for all owner-occupied units.

Comparability

The ACS currently only publishes financial housing characteristics for all owner-occupied units. (ACS no longer publishes tables of the characteristics of vacant units other than the vacancy status and whether the units are temporarily occupied or not.) The 2016 ACS PUMS file will still provide the individual characteristics of a specified owner housing unit, except for business or medical office on property which is no longer asked. The 2016 PUMS will also provide a single variable that combines the characteristics necessary for specified owner housing. However, the absence of a business or medical office is no longer a characteristic for specified. So this single variable for specified owner housing is not comparable to the previous ACS single variable. Census 2000 data provide financial housing characteristics for both all owner-occupied and all vacant-for-sale units and the more restricted universe of specified owner-occupied and specified vacant-for-sale units. So caution must be exercised in comparing specified owner housing from ACS prior to 2016 to Census 2000 to ensure the same universes. Beginning in 2016, the ACS cannot be compared to either Census 2000 or to ACS in previous years due to the elimination of the business or medical office on property question.

Specified renter-occupied units are renter-occupied units that exclude 1-family houses on 10 or more acres (cuerdas).

Specified renter-occupied and vacant-for-rent housing unit information is used to maintain a comparable universe between the American Community Survey (ACS) and earlier census data. Contract rent, gross rent, and gross rent as a percentage of income in earlier census data were based on specified renter-occupied and vacant-for-rent units; however, beginning in 2004, the ACS no longer published information solely for this universe. Rather, the ACS began publishing information for all renter-occupied and vacant-for-rent and rented, not occupied housing units. The characteristics for a specified rental unit as well as a single variable that combines all the characteristics for specified into one variable are maintained within the PUMS file ensuring that comparisons between the two data sets can be made.

Comparability

The ACS currently only publishes financial housing characteristics for total renter-occupied units. The 2016 ACS PUMS file will still provide the individual characteristics of a specified rental unit. And the 2016 PUMS will also provide a single variable that combines the characteristics necessary for specified rental housing. For Census 2000, tables were only released for specified renter-occupied and vacant-for-rent units. Therefore, comparisons between these two data sets can only be made if the characteristics of a specified renter-occupied or vacant-for rent unit from the 2016 PUMS are used to construct the same universe as Census 2000 or the single variable on the 2016 PUMS that combines the characteristics necessary for specified rental housing is used to produce the comparable universe.

The data on telephones were obtained from Housing Question 8g in the 2013 American Community Survey. The question was asked at occupied housing units.

The question asked whether telephone service was available in the house, apartment, or mobile home. A telephone must be in working order and service available in the house, apartment, or mobile home that allows the respondent to both make and receive calls. Households whose service has been discontinued for nonpayment or other reasons are not counted as having telephone service available.

The availability of telephone service provides information on the isolation of households. These data help assess the level of communication access amongst elderly and low-income households. The data also serve to aid in the development of emergency telephone, medical, or crime prevention services.

Question/Concept History

For the 1996-1998 American Community Survey, the question asked whether there was a telephone in the house or apartment. A telephone must be inside the house or apartment for the unit to be classified as having a telephone. Units where the respondent used a telephone located inside the building, but not in the respondent's living quarters, were classified as having no telephone. In 1999, the words "or mobile home" were added question to be more inclusive of the structure type. In 2004, instructions that accompanied the ACS mail questionnaire advised respondents that if the household members used cell phones to answer that the house, apartment, or mobile home had telephone service. Starting in 2008, the structure of the question changed and combined telephone service availability with plumbing facilities and kitchen facilities into one question to ask, "Does this house, apartment, or mobile home have -" and provided the respondent with a "Yes" or "No" checkbox for each component needed for complete facilities. In 2008 the instruction "Include cell phones" was added.

Limitation of the Data

The Census Bureau tested the changes introduced to the 2008 version of the telephone service available question in the 2006 ACS Content Test. The results of this testing show that the changes may introduce an inconsistency in the data produced for this question as observed from the years 2007 to 2008; see "2006 ACS Content Test Evaluation Report Covering Facilities" on the ACS website (http://www.census.gov).

Comparability

Caution should be used when comparing American Community Survey data on telephone service availability from the years 2008 and after with both pre-2008 ACS and Census 2000 data. Changes made to the telephone service availability question between the 2007 and 2008 ACS involving the structure of the question as well as the introduction of an instruction to include cell phones resulted in an inconsistency in the ACS data. This inconsistency in the data was most noticeable as an increase in the number of respondents answering "Yes" to the question.

The data for tenure were obtained from Housing Question 17 in the 2013 American Community Survey. The question was asked at occupied housing units. Occupied housing units are classified as either owner-occupied or renter-occupied.

Tenure provides a measurement of home ownership, which has served as an indicator of the nation's economy for decades. These data are used to aid in the distribution of funds for programs such as those involving mortgage insurance, rental housing, and national defense housing. Data on tenure allows planners to evaluate the overall viability of housing markets and to assess the stability of neighborhoods. The data also serve in understanding the characteristics of owner-occupied and renter-occupied units to aid builders, mortgage lenders, planning officials, government agencies, etc., in the planning of housing programs and services.

The data on units in structure (also referred to as "type of structure") were obtained from Housing Question 1 in the 2019 American Community Survey (ACS). The question was asked at occupied and vacant housing units. A structure is a separate building that either has open spaces on all sides or is separated from other structures by dividing walls that extend from ground to roof. In determining the number of units in a structure, all housing units, both occupied and vacant, are counted. Stores and office space are excluded. The data are presented for the number of housing units in structures of specified type and size, not for the number of residential buildings.

The units in structure provides information on the housing inventory by subdividing the inventory into one-family homes, apartments, and mobile homes. When the data is used in conjunction with tenure, year structure built, and income, units in structure serves as the basic identifier of housing used in many federal programs. The data also serve to aid in the planning of roads, hospitals, utility lines, schools, playgrounds, shopping centers, emergency preparedness plans, and energy consumption and supplies.

The data on utility costs were obtained from Housing Questions 13a through 13d in the 2019 American Community Survey (ACS). The questions were asked of occupied housing units. The questions about electricity and gas asked for the monthly costs, and the questions about water/sewer and other fuels (oil, coal, wood, kerosene, etc.) asked for the yearly costs.

Costs are recorded if paid by or billed to occupants, a welfare agency, relatives, or friends. Costs that are paid by landlords, included in the rent payment, or included in condominium or cooperative fees are excluded.

The cost of utilities provides information on the cost of either home ownership or renting. When the data is used as part of monthly housing costs and in conjunction with income data, the information offers an excellent measure of housing affordability and excessive shelter costs. The data also serve to aid in the development of housing programs to meet the needs of people at different economic levels, and to provide assistance in forecasting future utility services and energy supplies.

Question/Concept History

The American Community Survey questions ask for monthly costs for electricity and gas, and yearly costs for water/sewer and other fuels. Since 1999, the words "or mobile home" were added to each question, and Question 13b, which asked "Last month, what was the cost of gas for this house, apartment, or mobile home?" had an additional response category, "included in electricity payment entered above."

Limitation of the Data

Research has shown that respondents tended to overstate their expenses for electricity and gas when compared to utility company records. There is some evidence that this overstatement is reduced when yearly costs are asked rather than monthly costs. Caution should be exercised in using these data for direct analysis because costs are not reported for certain kinds of units such as renter-occupied units with all utilities included in the rent and owner-occupied condominium units with utilities included in the condominium fee.

Comparability

Data on utility costs in the 2019 American Community Survey can be compared to previous ACS and Census 2000 utility costs data.

Before 2013, the data on vacancy status were obtained only for a sample of cases in the computer-assisted personal interview (known as "CAPI") follow-up by field representatives. Data on vacancy status were obtained at the time of the personal visit. Vacancy status and other characteristics of vacant units were determined by field representatives obtaining information from landlords, owners, neighbors, rental agents, and others. Beginning in 2013, vacancy status and other characteristics of vacant units were obtained in the Internet selfresponse instrument as well as the CAPI.

Vacancy status has long been used as a basic indicator of the housing market and provides information on the stability and quality of housing for certain areas. The data is used to assess the demand for housing, to identify housing turnover within areas, and to better understand the population within the housing market over time. These data also serve to aid in the development of housing programs to meet the needs of persons at different economic levels.

Vacant units are subdivided according to their housing market classification as follows:

For Rent - These are vacant units offered "for rent," and vacant units offered either "for rent" or "for sale."

Rented, Not Occupied - These are vacant units rented but not yet occupied, including units where money has been paid or agreed upon, but the renter has not yet moved in.

For Sale Only - These are vacant units being offered "for sale only," including units in cooperatives and condominium projects if the individual units are offered "for sale only." If units are offered either "for rent" or "for sale" they are included in the "for rent" classification.

Sold, Not Occupied - These are vacant units sold but not yet occupied, including units that have been sold recently, but the new owner has not yet moved in.

For Seasonal, Recreational, or Occasional Use - These are vacant units used or intended for use only in certain seasons or for weekends or other occasional use throughout the year. Seasonal units include those used for summer or winter sports or recreation, such as beach cottages and hunting cabins. Seasonal units also may include quarters for such workers as herders and loggers. Interval ownership units, sometimes called shared-ownership or timesharing condominiums, also are included here.

For Migrant Workers - These include vacant units intended for occupancy by migratory workers employed in farm work during the crop season. (Work in a cannery, a freezer plant, or a food-processing plant is not farm work.)

Other Vacant - If a vacant unit does not fall into any of the categories specified above, it is classified as "Other vacant." For example, this category includes units held for occupancy by a caretaker or janitor, and units held for personal reasons of the owner.

Homeowner Vacancy Rate - The homeowner vacancy rate is the proportion of the homeowner inventory that is vacant "for sale." It is computed by dividing the number of vacant units "for sale only" by the sum of the owner-occupied units, vacant units that are "for sale only," and vacant units that have been sold but not yet occupied, and then multiplying by 100. This measure is rounded to the nearest tenth.

Rental Vacancy Rate - The rental vacancy rate is the proportion of the rental inventory that is vacant "for rent." It is computed by dividing the number of vacant units "for rent" by the sum of the renter-occupied units, vacant units that are "for rent," and vacant units that have been rented but not yet occupied, and then multiplying by 100. This measure is rounded to the nearest tenth.

Available Housing Vacancy Rate - The proportion of the housing inventory that is vacant- for-sale only and vacant-for-rent. It is computed by dividing the sum of vacant-for-sale only housing units and vacant-for-rent housing units, by the sum of occupied units, vacant-for-sale only housing units, vacant-sold-not occupied housing units, vacant-for-rent housing units, and vacant-rented-not-occupied housing units, and then multiplying by 100. This measure is rounded to the nearest tenth.

Question/Concept History - The 1996-2004 American Community Survey and Census 2000 used a single vacancy status category for units that were either "Rented or sold, not occupied." Since the 2005 ACS, there have been two separate categories, "Rented, not occupied" and "Sold, not occupied." This change created consistency among the ACS, the Housing Vacancy Survey, and the 2010 Census vacancy status response options. The revised categories were incorporated in the calculations of the rental vacancy rate and the homeowner vacancy rate.

Comparability - Do not compare because differences in the design and data collection methods between the ACS and the Decennial Census may materially affect estimates of vacancy rates. For more information on differences in vacancy rates between the ACS and Census, see Comparing 2010 American Community Survey 1-Year Estimates of Occupancy Status, Vacancy Status, and Household Size with the 2010 Census - Preliminary Results on the Census website. Go to http://www.census.gov/acs and enter the paper title in the search box

A housing unit occupied at the time of interview entirely by people who will be there for 2 months or less.In Computer-Assisted Telephone Interviews (CATI) and Computer-Assisted Personal Interviews (CAPI), the data for current residence elsewhere were obtained after creating the roster of people staying at the sample unit and after asking the current residence questions. Temporarily occupied units are sample units occupied at the time of interview entirely by people who will be there for 2 months or less. At sample units where all the people are staying less than 2 months, the respondent is asked a subset of the questions from the housing section, including the question on vacancy status.

In Computer-Assisted Telephone Interviews (CATI) and Computer-Assisted Personal Interviews (CAPI), the data for current residence elsewhere were obtained after creating the roster of people staying at the sample unit and after asking the current residence questions. Beginning in 2013, in the Internet self-response instrument, the roster of people is not created. Rather, if no one is living or staying there for more than 2 months, it is established that the home is not the current residence of any household members and the instrument begins the battery of vacant housing questions.

The current residence concept is unique to the American Community Survey. By using the current residence to decide for whom to collect survey information, the ACS can provide a more accurate description of an area's social and economic characteristics. Most surveys, as well as the decennial census, use the concept of usual residence. Usual residence is defined as the place where a person lives and sleeps most of the time. The census defines everyone as having only one usual residence.

Comparability

Do not compare because differences in the design and data collection methods between the ACS and the Decennial Census may materially affect estimates of vacancy rates. For more information on differences in vacancy rates between the ACS and Census, see Comparing 2010 American Community Survey 1-Year Estimates of Occupancy Status, Vacancy Status, and Household Size with the 2010 Census - Preliminary Results on the Census website. Go to http://www.census.gov/acs and enter the paper title in the search box

See Living Quarters.

The data on value (also referred to as "price asked" for vacant units) were obtained from Housing Question 18 in the 2019 American Community Survey (ACS). The question was asked at housing units that were owned, being bought, vacant for sale, or sold but not occupied at the time of the survey. Value is the respondent's estimate of how much the property (house and lot, mobile home and lot (if lot owned), or condominium unit) would sell for if it were for sale. If the house was owned or being bought, but the land on which it sits was not, the respondent was asked to estimate the combined value of the house and the land. Owners of noncondominium multi-unit buildings who live in one of the building's units, like duplexes and small apartment buildings, should report the value of the building, the land, and any additional buildings on the same plot of land. For vacant units, value was the price asked for the property. Value was tabulated separately for all owner-occupied and vacant-for-sale and sold, not occupied housing units, as well as owner-occupied mobile homes.

The value of a home provides information on neighborhood quality, housing affordability, and wealth. These data provide socioeconomic information not captured by household income and comparative information on the state of local housing markets. The data also serve to aid in the development of housing programs designed to meet the housing needs of persons at different economic levels.

The data on vehicles available were obtained from Housing Question 11 in the 2019 American Community Survey (ACS). The question was asked at occupied housing units. These data show the number of passenger cars, vans, and pickup or panel trucks of one-ton (2,000 pounds) capacity or less kept at home and available for the use of household members. Vehicles rented or leased for one month or more, company vehicles, and police and government vehicles are included if kept at home and used for non-business purposes. Motorcycles or other recreational vehicles are excluded. Dismantled or immobile vehicles are excluded. Vehicles kept at home but used only for business purposes also are excluded.

The availability of vehicles provides information for numerous transportation programs. When the data is used in conjunction with place-of-work and journey-to-work data, the information can provide insight into vehicle travel and aid in forecasting future travel and its effect on transportation systems. The data also serve to aid in the development of emergency and evacuation planning, special transportation services, and forecasting future energy consumption and needs.

Question/Concept History

The 1996-1998 American Community Survey question provided a space for the respondent to enter the number of vehicles. Since 1999, the American Community Survey question provided seven pre-coded response categories ranging from "None" to "6 or more."

Comparability

Data on vehicle availability in the 2019 ACS can be compared to previous ACS and Census 2000 vehicle availability data.

The data on year householder moved into unit were obtained from answers to Housing Question 3 in the 2019 American Community Survey (ACS), which was asked at occupied housing units. These data refer to the year of the latest move by the householder. If the householder moved back into a housing unit he or she previously occupied, the year of the latest move was reported. If the householder moved from one apartment to another within the same building, the year the householder moved into the present apartment was reported. The intent is to establish the year the present occupancy by the householder began. The year that the householder moved in is not necessarily the same year other members of the household moved in, although in the great majority of cases an entire household moves at the same time.

The year the householder moved into the unit provides information on the specific period of time when mobility occurs, especially for recent movers. These data help to measure neighborhood stability and to identify transient communities. The data also is used to assess the amount of displacement caused by floods and other natural disasters, and as an aid to evaluate the changes in service requirements.

The data on year structure built were obtained from Housing Question 2 in the 2019 American Community Survey (ACS). The question was asked at both occupied and vacant housing units. Year structure built refers to when the building was first constructed, not when it was remodeled, added to, or converted. Housing units under construction are included as vacant housing if they meet the housing unit definition, that is, all exterior windows, doors, and final usable floors are in place. For mobile homes, houseboats, RVs, etc., the manufacturer's model year was assumed to be the year built. The data relate to the number of units built during the specified periods that were still in existence at the time of interview.

The year the structure was built provides information on the age of housing units. These data help identify new housing construction and measures the disappearance of old housing from the inventory, when used in combination with data from previous years. The data also serve to aid in the development of formulas to determine substandard housing and provide assistance in forecasting future services, such as energy consumption and fire protection.

The data on age were derived from answers to Question 4 in the 2019 American Community Survey (ACS). The age classification is based on the age of the person in complete years at the time of interview. Both age and date of birth are used in combination to calculate the most accurate age at the time of the interview. Respondents are asked to give an age in whole, completed years as of interview date as well as the month, day and year of birth. People are not to round an age up if the person is close to having a birthday, and to estimate an age if the exact age is not known. An additional instruction on babies also asks respondents to print "0" for babies less than one year old. Inconsistently reported and missing values are assigned or imputed based on the values of other variables for that person, from other people in the household, or from people in other households ("hot deck" imputation).

Age is asked for all persons in a household or group quarters. On the mailout/mailback paper questionnaire for households, both age and date of birth are asked for persons listed as person numbers 1-5 on the form. Only age (in years) is initially asked for persons listed as 6-12 on the mailout/mailback paper questionnaire. If a respondent indicates that there are more than 5 people living in the household, then the household is eligible for Failed Edit Follow-up (FEFU). During FEFU operations, telephone center staffers call respondents to obtain missing data. This includes asking date of birth for any person in the household missing date of birth information. In Computer Assisted Telephone Interviews (CATI) and Computer Assisted Personal Interview (CAPI) instruments both age and date of birth is asked for all persons. In 2006, the ACS began collecting data in group quarters (GQs). This included asking both age and date of birth for persons living in a group quarters. For additional data collection methodology, please see https://www.census.gov/programssurveys/acs/.

Data on age are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. Age data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. Age is central for any number of federal programs that target funds or services to children, working-age adults, women of childbearing age, or the older population. The U.S. Department of Education uses census age data in its formula for allotment to states. The U.S. Department of Veterans Affairs uses age to develop its mandated state projections on the need for hospitals, nursing homes, cemeteries, domiciliary services, and other benefits for veterans. For more information on the use of age data in Federal programs, please go to "ACS Handbook of Questions and Current Federal Uses".

Ancestry refers to a person's ethnic origin, heritage, descent, or "roots," which may reflect their place of birth or that of previous generations of their family. Some ethnic identities, such as "Egyptian" or "Polish" can be traced to geographic areas outside the United States, while other ethnicities such as "Pennsylvania German" or "Cajun" evolved in the United States.

The intent of the ancestry question was not to measure the degree of attachment the respondent had to a particular ethnicity, but simply to establish that the respondent had a connection to and self-identified with a particular ethnic group. For example, a response of "Irish" might reflect total involvement in an Irish community or only a memory of ancestors several generations removed from the individual.

The data on ancestry were derived from answers to Question 13 in the 2019 American Community Survey (ACS). The question was based on self-identification; the data on ancestry represent self-classification by people according to the ancestry group(s) with which they most closely identify.

The Census Bureau coded the responses into a numeric representation of over 1,000 categories. To do so, responses initially were processed through an automated coding system; then, those that were not automatically assigned a code were coded by individuals trained in coding ancestry responses. The code list reflects the results of the Census Bureau's own research and consultations with many ethnic experts. Many decisions were made to determine the classification of responses. These decisions affected the grouping of the tabulated data. For example, the "Indonesian" category includes the responses of "Indonesian," "Celebesian," "Moluccan," and a number of other responses.

The ancestry question allowed respondents to report one or more ancestry groups. Generally, only the first two responses reported were coded. If a response was in terms of a dual ancestry, for example, "Irish English," the person was assigned two codes, in this case one for Irish and another for English. However, in certain cases, multiple responses such as "French Canadian," "Scotch-Irish," "Greek Cypriot," and "Black Dutch" were assigned a single code reflecting their status as unique groups. If a person reported one of these unique groups in addition to another group, for example, "Scotch-Irish English," resulting in three terms, that person received one code for the unique group (Scotch-Irish) and another one for the remaining group (English). If a person reported "English Irish French," only English and Irish were coded. If there were more than two ancestries listed and one of the ancestries was a part of another, such as "German Bavarian Hawaiian," the responses were coded using the more detailed groups (Bavarian and Hawaiian).

The Census Bureau accepted "American" as a unique ethnicity if it was given alone or with one other ancestry. There were some groups such as "American Indian," "Mexican American," and "African American" that were coded and identified separately.

The ancestry question is asked for every person in the American Community Survey, regardless of age, place of birth, Hispanic origin, or race.

Ancestry identifies the ethnic origins of the population, and Federal agencies regard this information as essential for fulfilling many important needs. Ancestry is required to enforce provisions under the Civil Rights Act, which prohibits discrimination based upon race, sex, religion, and national origin. More generally, these data are needed to measure the social and economic characteristics of ethnic groups and to tailor services to accommodate cultural differences. The Department of Labor draws samples for surveys that provide employment statistics and other related information for ethnic groups using ancestry.

The ACS data on ancestry are released annually on the American FactFinder (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml). Beginning in 2019, these tables are available through data.census.gov/. The Detailed Tables (B04001-B04006) contain estimates of over 100 different ancestry groups for the nation, states, and many other geographic areas, while the Special Population Profiles contain characteristics of different ancestry groups.

Special Population Profiles contain characteristics of different ancestry groups. Go to https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml and select "Advanced Search" to enter the table number.

In all tabulations, when respondents provided an unclassifiable ethnic identity (for example, "multi-national," "adopted," or "I have no idea"), the answer was included in "Unclassified or not reported."

The tabulations on ancestry show two types of data- one where estimates represent the number of people, and the other where estimates represent the number of responses. If you want to know how many people reported an ancestry, use the estimates based on people. If you want to know how many reports there were of a certain ancestry, use the estimates based on reports. The difference between the two types of data presentations represents the fact that people can provide more than one ancestry, and therefore can be counted twice in the same ancestry category. Examples are provided below.

The following are the types of estimates shown:

People Reporting Single Ancestry - Includes all people who reported only one ethnic group such as "German." Also included in this category are people with only a multipleterm response such as "Scotch-Irish" who are assigned a single code because they represent one distinct group. For example, in this type of table, the count for German would be interpreted as "The number of people who reported only German as their ancestry."

People Reporting Multiple Ancestries - Includes all people who reported more than one group, such as "German" and "Irish" and were assigned two ancestry codes. The German line on this table would be interpreted as "The number of people who responded that German was part of their multiple ancestry."

People Reporting Ancestry - Includes all people who reported each ancestry, regardless of whether it was their first or second ancestry, or part of a single or multiple response. This estimate is the sum of the two estimates above (for Single and Multiple ancestry). People can be listed twice in this table. For example, if someone reports their ancestry as "German and Danish," they will be listed once in German and once in Danish, and therefore the sum of the rows would not equal the total population. Interpret the German line of this table as "The total number of people who reported they had German ancestry."

Note that three other tables were available prior to 2014:

B04001 - First Ancestry Reported

B04002 - Second Ancestry Reported

B04003 -Total Ancestries Reported

These tables were removed in 2014 because they were less user-friendly than B04004-B04006. The tables were tallies of the number of people reporting each ancestry first, second, and in total, which resulted in double-counting within many ancestry groups. For example, if a respondent reported two different types of German ancestry, they would be tallied twice under German in B04003. Or, if a respondent had two different types of Arab ancestry, they would be tallied twice under Arab. Thus, table B04006 is a better table to use if a data user is interested in knowing the total number of people who responded that they had German or Arab ancestry, for example.

Question/Concept History - The question on ancestry has been asked on the ACS since 1996. The question wording has never changed, although placement of the question changed slightly. Also, the examples listed below the write-in lines changed in 1999, but have remained the same since then.

The question on ancestry was first asked in the 1980 Census. It replaced the question on parental place of birth, in order to include ancestral heritage for people whose families have been in the U.S. for more than two generations. The question also was asked in the 1990 Census and Census 2000.

The ACS editing system uses answers to the race and place of birth questions to clarify ancestry responses of "Indian," where possible. It also aids in the interpretation of two-word ancestries, such as "Black Irish."

Limitation of the Data - Although some experts consider religious affiliation a component of ethnic identity, the ancestry question was not designed to collect any information concerning religion. The Census Bureau is prohibited from collecting information on religion. Thus, if a religion was given as an answer to the ancestry question, it was coded as an "Other" response.

Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations may have ancestry distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the ancestry distribution. This is particularly true for areas with a substantial GQ population.

Comparability - The data are comparable to Census 2000, as long as some caution is used. Response rates to the ancestry question are generally higher for the ACS than for the Census, and data are never generated for missing ancestry responses; therefore, some ancestry groups are reported more heavily in the ACS than in Census 2000.

In 2010, there were two major changes to the coding rules. If up to two ancestries were listed, both were coded, even if one was the specific of the other or if one was American. Also, race groups and Hispanic groups were coded with the same priority as non-race and non-Hispanic groups. For example, "Haitian Black French" would previously have been coded Haitian and French, but now would be coded Haitian and Black. For more information, see the Ancestry Code List found within the 2019 ACS Code List. Go to http://www.census.gov and enter "ACS Code Lists, Definitions, and Accuracy" in the search box.

For the 1996-1998 American Community Survey, the data on fertility (also referred to as "children ever born") was asked of all women 15 years old and over regardless of marital status. Stillbirths, stepchildren, and adopted children were excluded from the number of children ever born. Ever-married women were instructed to include all children born to them before and during their most recent marriage, children no longer living, and children living away from home, as well as children who were still living in the home. Never-married women were instructed to include all children born to them. The question on children ever born was asked to measure lifetime fertility experience of women up to the survey date.

Data were most frequently presented in terms of the aggregate number of children ever born to women in the specified category and in terms of the rate per 1,000 women.

Beginning in 1999, American Community Survey data on fertility were derived from questions that asked if the person had given birth in the past 12 months (Question 24 in the 2019 ACS). See the section on "Fertility" for more information.

Question/Concept History

The 1996-1998 American Community Survey used a write-in space for the number and a response category for "None." No question addressed "children ever born" after 1998.

Limitation of the Data

The data available for 1996-1998 are only available for a limited number of geographies.

Comparability

The data on children ever born are comparable to data from the 1990 Census and prior censuses. The data are also comparable to the June supplement to the Current Population Survey.

The data on citizenship status were derived from answers to Question 8 in the 2019 American Community Survey (ACS). This question was asked about Persons 1 through 5 in the ACS.

Respondents were asked to select one of five categories:

(1) born in the United States,

(2) born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas,

(3) born abroad of U.S. citizen parent or parents,

(4) U.S. citizen by naturalization, or

(5) not a U.S citizen. Respondents indicating they are a U.S. citizen by naturalization are also asked to print their year of naturalization.

People born in American Samoa, although not explicitly listed, are included in the second response category.

For the Puerto Rico Community Survey, respondents were asked to select one of five categories: (1) born in Puerto Rico, (2) born in a U.S. state, District of Columbia, Guam, the U.S. Virgin Islands, or Northern Marianas, (3) born abroad of U.S. citizen parent or parents, (4) U.S. citizen by naturalization, or (5) not a U.S. citizen. Respondents indicating they are a U.S. citizen by naturalization are also asked to print their year of naturalization. People born in American Samoa, although not explicitly listed, are included in the second response category.


When no information on citizenship status was reported for a person, information for other household members, if available, was used to assign a citizenship status to the respondent. All cases of nonresponse that were not assigned a citizenship status based on information from other household members were allocated the citizenship status of another person with similar characteristics who provided complete information. In cases of conflicting responses, place of birth information is used to edit citizenship status. For example, if a respondent states he or she was born in Puerto Rico but was not a U.S. citizen, the edits use the response to the place of birth question to change the respondent's status to "U.S. citizen at birth."

Class of worker categorizes people according to the type of ownership of the employing organization. Class of worker data were derived from answers to question 41 in the 2019 American Community Survey. Question 41 provides respondents with 8 class of worker categories from which they are to select one. These categories are:

1. An employee of a private, for-profit company or business, or of an individual, for wages, salary, or commissions.
2. An employee of a private, not-for-profit, tax-exempt, or charitable organization.
3. A local government employee (city, county, etc.).
4. A state government employee.
5. A Federal government employee.
6. Self-employed in own not incorporated business, professional practice, or farm.
7. Self-employed in own incorporated business, professional practice, or farm.
8. Working without pay in a family business or farm.

These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person's job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.

The class of worker categories are defined as follows:

Under the conceptual framework of disability described by the Institute of Medicine (IOM) and the International Classification of Functioning, Disability, and Health (ICF), disability is defined as the product of interactions among individuals' bodies; their physical, emotional, and mental health; and the physical and social environment in which they live, work, or play. Disability exists where this interaction results in limitations of activities and restrictions to full participation at school, at work, at home, or in the community. For example, disability may exist where a person is limited in their ability to work due to job discrimination against persons with specific health conditions; or, disability may exist where a child has difficulty learning because the school cannot accommodate the child's deafness.

Furthermore, disability is a dynamic concept that changes over time as one's health improves or declines, as technology advances, and as social structures adapt. As such, disability is a continuum in which the degree of difficulty may also increase or decrease. Because disability exists along a continuum, various cut-offs are used to allow for a simpler understanding of the concept, the most common of which is the dichotomous "With a disability"/"no disability" differential.

Measuring this complex concept of disability with a short set of six questions is difficult. Because of the multitude of possible functional limitations that may present as disabilities, and in the absence of information on external factors that influence disability, surveys like the ACS are limited to capturing difficulty with only selected activities. As such, people identified by the ACS as having a disability are, in fact, those who exhibit difficulty with specific functions and may, in the absence of accommodation, have a disability. While this definition is different from the one described by the IOM and ICF conceptual frameworks, it relates to the programmatic definitions used in most Federal and state legislation.

In an attempt to capture a variety of characteristics that encompass the definition of disability, the ACS identifies serious difficulty with four basic areas of functioning - hearing, vision, cognition, and ambulation. These functional limitations are supplemented by questions about difficulties with selected activities from the Katz Activities of Daily Living (ADL) and Lawton Instrumental Activities of Daily Living (IADL) scales, namely difficulty bathing and dressing, and difficulty performing errands such as shopping. Overall, the ACS attempts to capture six aspects of disability, which can be used together to create an overall disability measure, or independently to identify populations with specific disability types.

Information on disability is used by a number of federal agencies to distribute funds and develop programs for people with disabilities. For example, data about the size, distribution, and needs of the population with a disability are essential for developing disability employment policy. For the Americans with Disabilities Act, data about functional limitations are important to ensure that comparable public transportation services are available for all segments of the population. Federal grants are awarded, under the Older Americans Act, based on the number of elderly people with physical and mental disabilities.

Question/Concept History

In the 2019 American Community Survey, disability concepts were asked in questions 17 through 19. Question 17 had two subparts and was asked of all persons regardless of age. Question 18 had three subparts and was asked of people age 5 years and older. Question 19 was asked of people age 15 years and older.

Educational attainment data are needed for use in assessing the socioeconomic condition of the U.S. population. Government agencies also require these data for funding allocations and program planning and implementation. These data are needed to determine the extent of illiteracy rates of citizens in language minorities in order to meet statutory requirements under the Voting Rights Act. Based on data about educational attainment, school districts are allocated funds to provide classes in basic skills to adults who have not completed high school.

Data on educational attainment were derived from answers to Question 11 on the 2019 American Community Survey, which was asked of all respondents. Educational attainment data are tabulated for people 18 years old and over. Respondents are classified according to the highest degree or the highest level of school completed. The question included instructions for persons currently enrolled in school to report the level of the previous grade attended or the highest degree received.

The educational attainment question included a response category that allowed people to report completing the 12th grade without receiving a high school diploma. Respondents who received a regular high school diploma and did not attend college were instructed to report "Regular high school diploma." Respondents who received the equivalent of a high school diploma (for example, passed the test of General Educational Development (G.E.D.)), and did not attend college, were instructed to report "GED or alternative credential." "Some college" is in two categories: "Some college credit, but less than 1 year of college credit" and "1 or more years of college credit, no degree." The category "Associate's degree" included people whose highest degree is an associate's degree, which generally requires 2 years of college level work and is either in an occupational program that prepares them for a specific occupation, or an academic program primarily in the arts and sciences. The course work may or may not be transferable to a bachelor's degree. Master's degrees include the traditional MA and MS degrees and field-specific degrees, such as MSW, MEd, MBA, MLS, and MEng. Instructions included in the respondent instruction guide for mailout/mailback respondents only provided the following examples of professional school degrees: medicine, dentistry, chiropractic, optometry, osteopathic medicine, pharmacy, podiatry, veterinary medicine, law, and theology. The order in which degrees were listed suggested that doctorate degrees were "higher" than professional school degrees, which were "higher" than master's degrees. If more than one box was filled, the response was edited to the highest level or degree reported.

Help text available to people responding by Internet and through personal interviews were instructed that schooling completed in foreign or ungraded school systems should be reportedas the equivalent level of schooling in the regular American system. The instructions specified that certificates or diplomas for training in specific trades or from vocational, technical or business schools were not to be reported. Honorary degrees awarded for a respondent's accomplishments were not to be reported.

The data on employment status were derived from Questions 29 and 35 to 37 in the 2019 American Community Survey. (In the 1999-2002 American Community Survey, data were derived from Questions 22 and 28 to 30; in the 1996-1998 American Community Survey, data were derived from Questions 21 and 28 to 30.) The questions were asked of all people 15 years old and over. The series of questions on employment status was designed to identify, in this sequence: (1) people who worked at any time during the reference week; (2) people on temporary layoff who were available for work; (3) people who did not work during the reference week but who had jobs or businesses from which they were temporarily absent (excluding layoff); (4) people who did not work during the reference week, but who were looking for work during the last four weeks and were available for work during the reference week; and (5) people not in the labor force. (For more information, see the discussion under "Reference Week.")

The employment status data shown in American Community Survey tabulations relate to people 16 years old and over.

Employment status is key to understanding work and unemployment patterns and the availability of workers. Based on labor market areas and unemployment levels, the U.S. Department of Labor identifies service delivery areas and determines amounts to be allocated to each for job training. The impact of immigration on the economy and job markets is determined partially by labor force data, and this information is included in required reports to Congress. The Office of Management and Budget, under the Paperwork Reduction Act, uses data about employed workers as part of the criteria for defining metropolitan areas. The Bureau of Economic Analysis uses this information, in conjunction with other data, to develop its state per capita income estimates used in the allocation formulas and eligibility criteria for many federal programs such as Medicaid.

See Household Type and Relationship.

The data on fertility were derived from Question 17 in 1999-2002, Question 18 in 2003-2007, question 23 in 2008, and question 24 since 2009 in the American Community Survey. The question asked if the person had given birth in the past 12 months, and was asked of all women 15 to 50 years old regardless of marital status. From this question, we are able to determine geographies with high numbers of women with births and the characteristics of these women, such as age and marital status. When fertility was not reported, it was imputed according to the woman's age and marital status and the possibility there was an infant in the household.

Data are most frequently presented in terms of the aggregate number of women who had a birth in the past 12 months in the specified category, and in terms of the rate per 1,000 women.

Field of degree data are used by the National Science Foundation to study the characteristics of the population with science and engineering degrees and occupations.

Data on field of bachelor's degree were derived from answers to Question 12 in the 2019 American Community Survey. This question was asked only to person with a bachelor's degree or higher. Eligible respondents were asked to list the specific major(s) of any bachelor's degree received. This question does not ask for the field of any other type of degree earned (such as master's or doctorate).

An automated computer system coded write-in responses to Question 12 into 192 areas. Clerical coding categorized any write-in responses that could not be autocoded by the computer. Respondents listing multiple fields were assigned a code for each field, with a maximum of 10 fields per respondent.
The majors were further classified into a category scheme detailed in Field of Degree Classification table in Appendix A.

Question/Concept History

The field of degree question first appeared in the 2009 ACS. The inclusion of a field of degree question on the ACS was proposed to provide field of degree data annually for small levels of geography and to assist in building a sampling frame for the National Science Foundation's (NSF) National Survey of College Graduates (NSCG).

Comparability

Tables based on 2010-2019 ACS data are not completely comparable to tables based on 2009 ACS data due to slight changes in the field of degree coding and classifications. More information can be found at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/educational-attainment-user-notes/acs-2010-field-of-degree-changes.html.

This data may be roughly comparable to the National Survey of College Graduates and the National Survey of Recent College Graduates, although the sampling frame and survey instruments differ between the surveys. Field of degree data was also collected in the Survey of Income and Program Participation (SIPP) from1984 to 2004. However, these data would not be comparable to ACS due to differences in data collection period, methodology and collection methods. For example, the SIPP only collects data for respondents who are 15 years and older and does not include group quarters.

The foreign-born population includes anyone who was not a U.S. citizen or a U.S. national at birth. This includes respondents who indicated they were a U.S. citizen by naturalization or not a U.S. citizen. See Citizenship Status.

See Household Type and Relationship.

See School Enrollment and Type of School.

Data on grandparents as caregivers were derived from Questions 25a through 25c in the 2019 American Community Survey. Data are collected on whether a grandchild lives with a grandparent in the household, whether the grandparent has responsibility for the basic needs of the grandchild, and the duration of that responsibility.

See Living Quarters.

In 2017, data on health insurance coverage were derived from answers to Question 16 in the American Community Survey, which was asked of all respondents. Respondents were instructed to report their current coverage and to mark "yes" or "no" for each of the eight types listed (labeled as parts 16a to 16h).

1. Insurance through a current or former employer or union (of this person or another family member)
2. Insurance purchased directly from an insurance company (by this person or another family member)
3. Medicare, for people 65 and older, or people with certain disabilities
4. Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability
5. TRICARE or other military health care
6. VA (including those who have ever used or enrolled for VA health care)
7. Indian Health Service
8. Any other type of health insurance or health coverage plan

Respondents who answered "yes" to question 16h were asked to provide their other type of coverage type in a write-in field.

Health insurance coverage in the ACS and other Census Bureau surveys define coverage to include plans and programs that provide comprehensive health coverage. Plans that provide insurance for specific conditions or situations such as cancer and long-term care policies are not considered coverage. Likewise, other types of insurance like dental, vision, life, and disability insurance are not considered health insurance coverage.

In defining types of coverage, write-in responses were reclassified into one of the first seven types of coverage or determined not to be a coverage type. Write-in responses that referenced the coverage of a family member were edited to assign coverage based on responses from other family members. As a result, only the first seven types of health coverage are included in the microdata file.

An eligibility edit was applied to give Medicaid, Medicare, and TRICARE coverage to individuals based on program eligibility rules. TRICARE or other military health care was given to active-duty military personnel and their spouses and children. Medicaid or other means-tested public coverage was given to foster children, certain individuals receiving Supplementary Security Income or Public Assistance, and the spouses and children of certain Medicaid beneficiaries. Medicare coverage was given to people 65 and older who received Social Security or Medicaid benefits.

People were considered insured if they reported at least one "yes" to Questions 16a to 16f. People who had no reported health coverage, or those whose only health coverage was Indian Health Service, were considered uninsured. For reporting purposes, the Census Bureau broadly classifies health insurance coverage as private health insurance or public coverage. Private health insurance is a plan provided through an employer or union, a plan purchased by an individual from a private company, or TRICARE or other military health care. Respondents reporting a "yes" to the types listed in parts a, b, or e were considered to have private health insurance. Public health coverage includes the federal programs Medicare, Medicaid, and VA Health Care (provided through the Department of Veterans Affairs); the Children's Health Insurance Program (CHIP); and individual state health plans. Respondents reporting a "yes" to the types listed in c, d, or f were considered to have public coverage. The types of health insurance are not mutually exclusive; people may be covered by more than one at the same time.

The U.S. Department of Health and Human Services, as well as other federal agencies, use data on health insurance coverage to more accurately distribute resources and better understand state and local health insurance needs.

Question/Concept History

The ACS began asking questions about health insurance coverage in 2008. Because 2008 was the first year of collection, the Census Bureau limited the number and type of data products to simple age breakdowns of overall, private, and public coverage status. The evaluation of the 2008 data suggested that the data were of good quality, so the Census Bureau expanded the data products to include estimates of the specific types of coverage along with estimates about social, economic, and demographic details for people with and without health insurance.

For the 2008 data released September 2009, there was no eligibility edit applied. The eligibility edit that was developed for the 2009 was applied to the 2008 data during spring 2010. New estimates of health insurance coverage with this data are available (http://www.census.gov/hhes/www/hlthins/hlthins.html).

Limitation of the Data

The universe for most health insurance coverage estimates is the civilian noninstitutionalized population, which excludes active-duty military personnel and the population living in correctional facilities and nursing homes. Some noninstitutionalized GQ populations have health insurance coverage distributions that are different from the household population (e.g., the prevalence of private health insurance among residents of college dormitories is higher than the household population). The proportion of the universe that is in the noninstitutionalized GQ populations could therefore have a noticeable impact on estimates of the health insurance coverage. Institutionalized GQ populations may also have health insurance coverage distributions that are different from the civilian noninstitutionalized population, the distributions in the published tables may differ slightly from how they would look if the total population were represented.

Comparability

Health insurance coverage was added to the 2008 ACS and so no equivalent measure is available from previous ACS surveys or Census 2000. Because of the addition of the eligibility edit to 2009 ACS health insurance, data users should be careful as to which 2008 ACS estimates they use to make comparisons. National, state, county and place-level 2008 1-year data incorporating the eligibility edit are available
(https://www.census.gov/topics/health/health-insurance/guidance/acs-2008-1-year-re-run.html); they are comparable to the 2009 estimates in American Fact Finder (factfinder.census.gov). Please see
"Applying and Evaluating Logical Coverage Edits to Health Insurance Coverage in the American Community Survey" for more information on the logical coverage (eligibility) edits.

Because coverage in the ACS references an individual's current status, caution should be taken when making comparisons to other surveys which may define coverage as "at any time in the last year" or "throughout the past year." A discussion of how the ACS health insurance estimates relate to other survey health insurance estimates can be found in A Preliminary Evaluation of Health Insurance Coverage in the 2008 American Community Survey (https://www.census.gov/library/working-papers/2009/acs/2009_Turner_01.html).

The data on the Hispanic or Latino population were derived from answers to a question that was asked of all people (Question 5 in the 2019 American Community Survey (ACS)) . The terms "Hispanic," "Latino," and "Spanish" are used interchangeably. Some respondents identify with all three terms while others may identify with only one of these three specific terms. Hispanics or Latinos who identify with the terms "Hispanic," "Latino," or "Spanish" are those who classify themselves in one of the specific Hispanic, Latino, or Spanish categories listed on the questionnaire ("Mexican," "Puerto Rican," or "Cuban") as well as those who indicate that they are "another Hispanic, Latino, or Spanish origin." People who do not identify with one of the specific origins listed on the questionnaire but indicate that they are "another Hispanic, Latino, or Spanish origin" are those whose origins are from Spain, the Spanish-speaking countries of Central or South America, or the Dominican Republic. Up to two write-in responses to the "another Hispanic, Latino, or Spanish origin" category are coded.

Origin can be viewed as the heritage, nationality group, lineage, or country of birth of the person or the person's parents or ancestors before their arrival in the United States. People who identify their origin as Hispanic, Latino, or Spanish may be of any race.

Hispanic origin is used in numerous programs and is vital in making policy decisions. These data are needed to determine compliance with provisions of antidiscrimination in employment and minority recruitment legislation. Under the Voting Rights Act, data about Hispanic origin are essential to ensure enforcement of bilingual election rules. Hispanic origin classifications used by the Census Bureau and other federal agencies meet the requirements of standards issued by the Office of Management and Budget in 1997 (Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity). These standards set forth guidance for statistical collection and reporting on race and ethnicity used by all federal agencies.

Some tabulations are shown by the origin of the householder. In all cases where the origin of households, families, or occupied housing units is classified as Hispanic, Latino, or Spanish, the origin of the householder is used. (For more information, see the discussion of householder under "Household Type and Relationship.")

See Household Type and Relationship.

The data on relationship to householder were derived from answers to Question 2 in the 2019 American Community Survey, relationship to the householder, which was asked of all people in housing units. The question on relationship is essential for classifying the population information on families and other groups. Information about changes in the composition of the American family, from the number of people living alone to the number of children living with only one parent, is essential for planning and carrying out a number of federal programs, such as families in poverty.

The responses to this question were used to determine the relationships of all persons to the householder, as well as household type (married couple family, nonfamily, etc.). From responses to this question, we were able to determine numbers of related children, own children, unmarried partner households, and multigenerational households. We calculated average household and family size. When relationship was not reported, it was imputed using the age difference between the householder and the person, sex, and marital status.

See Household Type and Relationship.

See Household Type and Relationship.

See Foreign-Born Population.

The data on income were derived from answers to Questions 47 and 48 in the 2019 American Community Survey, which were asked of the population 15 years old and over. "Total income" is the sum of the amounts reported separately for wage or salary income; net self- employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income.

Receipts from the following sources are not included as income: capital gains, money received from the sale of property (unless the recipient was engaged in the business of selling such property); the value of income "in kind" from food stamps, public housing subsidies, medical care, employer contributions for individuals, etc.; withdrawal of bank deposits; money borrowed; tax refunds; exchange of money between relatives living in the same household; gifts and lump-sum inheritances, insurance payments, and other types of lump- sum receipts.

Income is a vital measure of general economic circumstances. Income data are used to determine poverty status, to measure economic well-being, and to assess the need for assistance. These data are included in federal allocation formulas for many government programs. For instance:

Social Services: Under the Older Americans Act, funds for food, health care, and legal services are distributed to local agencies based on data about elderly people with low incomes. Data about income at the state and county levels are used to allocate funds for food, health care, and classes in meal planning to low-income women with children.

Employment: Income data are used to identify local areas eligible for grants to stimulate economic recovery, run job-training programs, and define areas such as empowerment or enterprise zones.

Housing: Under the Low-Income Home Energy Assistance Program, income data are used to allocate funds to areas for home energy aid. Under the Community Development Block Grant Program, funding for housing assistance and other community development is based on income and other census data.

Education: Data about poor children are used to allocate funds to counties and school districts. These funds provide resources and services to improve the education of economically disadvantaged children.

In household surveys, respondents tend to underreport income. Asking the list of specific sources of income helps respondents remember all income amounts that have been received, and asking total income increases the overall response rate and thus, the accuracy of the answers to the income questions. The eight specific sources of income also provide needed detail about items such as earnings, retirement income, and public assistance.

The eight types of income reported in the American Community Survey are defined as follows:

1. Wage or salary income: Wage or salary income includes total money earnings received for work performed as an employee during the past 12 months. It includes wages, salary, Armed Forces pay, commissions, tips, piece-rate payments, and cash bonuses earned before deductions were made for taxes, bonds, pensions, union dues, etc.
2. Self-employment income: Self-employment income includes both farm and non-farm self-employment income.
   
   Farm self-employment income includes net money income (gross receipts minus operating expenses) from the operation of a farm by a person on his or her own account, as an owner, renter, or sharecropper. Gross receipts include the value of all products sold, government farm programs, money received from the rental of farm equipment to others, and incidental receipts from the sale of wood, sand, gravel, etc. Operating expenses include cost of feed, fertilizer, seed, and other farming supplies, cash wages paid to farmhands, depreciation charges, rent, interest on farm mortgages, farm building repairs, farm taxes (not state and federal personal income taxes), etc. The value of fuel, food, or other farm products used for family living is not included as part of net income.
   
   Non-farm self-employment income includes net money income (gross receipts minus expenses) from one's own business, professional enterprise, or partnership. Gross receipts include the value of all goods sold and services rendered. Expenses include costs of goods purchased, rent, heat, light, power, depreciation charges, wages and salaries paid, business taxes (not personal income taxes), etc.
   
   
3. Interest, dividends, net rental income, royalty income, or income from estates and trusts: Interest, dividends, or net rental income includes interest on savings or bonds, dividends from stockholdings or membership in associations, net income from rental of property to others and receipts from boarders or lodgers, net royalties, and periodic payments from an estate or trust fund.
4. Social Security income: Social Security income includes Social Security pensions and survivor benefits, permanent disability insurance payments made by the Social Security Administration prior to deductions for medical insurance, and railroad retirement insurance checks from the U.S. government. Medicare reimbursements are not included.
5. Supplemental Security Income (SSI): Supplemental Security Income (SSI) is a nationwide U.S. assistance program administered by the Social Security Administration that guarantees a minimum level of income for needy aged, blind, or disabled individuals. The Puerto Rico Community Survey questionnaire asks about the receipt of SSI; however, SSI is not a federally-administered program in Puerto Rico. Therefore, it is probably not being interpreted by most respondents in the same manner as SSI in the United States. The only way a resident of Puerto Rico could have appropriately reported SSI would have been if they lived in the United States at any time during the past 12-month reference period and received SSI.
6. Public assistance income: Public assistance income includes general assistance and Temporary Assistance to Needy Families (TANF). Separate payments received for hospital or other medical care (vendor payments) are excluded. This does not include Supplemental Security Income (SSI) or noncash benefits such as Food Stamps. The terms "public assistance income" and "cash public assistance" are used interchangeably in the 2019 ACS data products.
7. Retirement, survivor, or disability income: Retirement, survivor, or disability income includes (1) regular income from a company pension, union pension, Federal government pension, state government pension, local government pension, U.S. military pension, KEOGH retirement plan, SEP (Simplified Employee Pension) or any other type of pension, retirement account or annuity such as IRA, ROTH IRA, 401(k) or 403(b); (2) survivor income which is paid to spouses or children of a deceased person; (3) regular income from a disability pension paid to those who are unable to work due to a disability from companies or unions; federal, state, or local government; and the U.S. military.
   
   Do not include Social Security or income that is "rolled over" or reinvested in another retirement account.
8. All other income: All other income includes unemployment compensation, worker's compensation, Department of Veterans Affairs (VA) payments, alimony and child support, contributions received periodically from people not living in the household, military family allotments, and other kinds of periodic income other than earnings.

Industry data describe the kind of business conducted by a person's employing organization. Industry data were derived from answers to questions 42 through 44 in the 2019 American Community Survey. Question 42 asks: "For whom did this person work?" Question 43 asks: "What kind of business or industry was this?" Question 44 provides four checkboxes from which respondents are to select one to indicate whether the business was primarily manufacturing, wholesale trade, retail trade, or other (agriculture, construction, service, government, etc.).

These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person's job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.

Coding Procedures - Written responses to the industry questions are coded using the industry classification system developed for Census 2000 and modified in 2002, 2007, 2012 and again in 2017. This system consists of 269 categories for employed people, including military, classified into 20 sectors, plus an additional Census code for the unemployed, with no work experience in the last 5 years or earlier or never worked for a total of 270 Census industry codes. The modified 2017 Census industry classification was developed from the 2017 North American Industry Classification System (NAICS) (http://www.census.gov/eos/www/naics/) published by the Executive Office of the President, Office of Management and Budget. The NAICS was developed to increase comparability in industry definitions between the United States, Mexico, and Canada. It provides industry classifications that group establishments into industries based on the activities in which they are primarily engaged. The NAICS was created for establishment designations and provides detail about the smallest operating establishment, while the ACS data are collected from households and differ in detail and nature from those obtained from establishment surveys. Because of potential disclosure issues, the Census industry classification system, while defined in NAICS terms, cannot reflect the full detail for all categories that the NAICS provides.

Respondents provided the data for the tabulations by writing on the questionnaires descriptions of their kind of business or industry. These write-ins are converted to a code category through automated coding. Cases not autocoded on both industry and occupation are sent to the clerical staff in the National Processing Center in Jeffersonville, Indiana who assign codes by comparing these descriptions to entries in the most current Alphabetical Index of Industries and Occupations (https://www.census.gov/topics/employment/industryoccupation/guidance/indexes.html).

The industry category, "Public administration," is limited to regular government functions such as legislative, judicial, administrative, and regulatory activities. Other government organizations such as public schools, public hospitals, and bus lines are classified by industry according to the activity in which they are engaged.

Some occupation groups are related closely to certain industries. Operators of transportation equipment, farm operators and workers, and healthcare providers account for major portions of their respective industries of transportation, agriculture, and health care. However, the industry categories include people in other occupations. For example, people employed in agriculture include truck drivers and bookkeepers; people employed in the transportation industry include mechanics, freight handlers, and payroll clerks; and people employed in the health care industry include janitors, security guards, and secretaries.

Editing Procedures - Following the coding operation, a computer edit and allocation process excludes all responses that should not be included in the universe, and evaluates the consistency of the remaining responses. The codes for industry are checked for consistency with the occupation and class of worker data provided for that respondent. Occasionally respondents supply industry descriptions that are not sufficiently specific for precise classification, or they do not report on these questions at all. Certain types of incomplete entries are corrected using the Alphabetical Index of Industries and Occupations. If one or more of the three codes (industry, occupation, or class of worker) is blank after the edit, a code is assigned from a donor respondent who is a "similar" person based on questions such as age, sex, educational attainment, income, employment status, and weeks worked. If all of the labor force and income data are blank, all of these economic questions are assigned from a "similar" person who had provided all the necessary data.

These questions describe the industrial composition of the American labor force. Data are used to formulate policy and programs for employment, career development and training, and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

Question/Concept History - Industry data have been collected during decennial censuses intermittently since 1820 and on a continuous basis since 1910. Starting with the 2010 Census, industry data will no longer be collected during the decennial census. Long form data collection has transitioned to the ACS. The ACS began collecting data on industry in 1996. The questions on industry were designed to be consistent with the 1990 Census questions on industry. In the 1990 Census and starting with the 1999 ACS, a check box was added to the employer name questionnaire item that was to be marked by anyone "now on active duty in the Armed Forces..." This information is used by the industry and occupation coders to assist in assigning proper industry codes for active duty military. Prior to 1999, the 1996-1998 ACS class of worker question had an additional response category for "Active duty U.S. Armed Forces member." Other than this exception, ACS questions on industry have remained consistent between 1996 and 2019.

Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations have industry distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the industry distribution in some geographic areas with a substantial GQ population.

Data on occupation, industry, and class of worker are collected for the respondent's current primary job or the most recent job for those who are not employed but have worked in the last 5 years. Other labor force questions, such as questions on earnings or work hours, may have different reference periods and may not limit the response to the primary job. Although the prevalence of multiple jobs is low, data on some labor force items may not exactly correspond to the reported occupation, industry, or class of worker of a respondent.

Comparability - Comparability of industry data was affected by a number of factors, primarily the system used to classify the questionnaire responses. Changes in the industry classification system limit comparability of the data from one year to another. These changes are needed to recognize the "birth" of new industries, the "death" of others, the growth and decline in existing industries, and the desire of analysts and other users for more detail in the presentation of the data. Probably the greatest cause of noncomparability is the movement of a segment from one category to another. Changes in the nature of jobs, respondent terminology, and refinement of category composition made these movements necessary.

ACS data from 1996 to 1999 used the same industry classification systems used for the 1990 Census; therefore, the data are comparable. Since 1990, the industry classification has had major revisions to reflect the shift from the Standard Industrial Classification (SIC) to the North American Industry Classification System (NAICS). These changes were reflected in the Census 2000 industry codes. For more information on industry comparability across classification systems, please see technical paper #65: The Relationship Between the 1990 Census and Census 2000 Industry and Occupation Classification Systems
(http://www.census.gov/people/io/files/techpaper2000.pdf). The 2000-2002 ACS data used the same industry and occupation classification systems used for the Census 2000; therefore, the data are comparable. In 2002, NAICS underwent another change and the industry codes were changed accordingly. Because of the possibility of new industries being added to the list of codes, the Census Bureau needed to have more flexibility in adding codes. Consequently, in 2002, industry census codes were expanded from three-digit codes to four-digit codes. The changes to these code classifications mean that the ACS data from 2003-2007 are not completely comparable to the data from earlier surveys. In 2007, NAICS was updated again. This resulted in a minor change in the industry data that will cause it to not be completely comparable to previous years. The changes were concentrated in the Information Sector where one census code was added (6672) and two were deleted (6675, 6692). The ACS followed the 2007 code list through 2012, making the ACS 2007-2012 industry codes comparable. NAICS was updated again in 2012. The changes were used to create the 2012 Census industry code list, which was first applied to the 2013 ACS. The revision included 9 new codes (3095, 3365, 3875, 3895, 4195, 4265, 4795, 5275, 5295), 9 deletions (3090, 3360, 3870, 3890, 4190, 4260, 4790, 5270, 5290) and 19 title changes. These changes make the 2012 Census industry codes only partially comparable with previous years. The ACS followed the 2012 code list through 2017. In 2017, the NAICS was updated again. The 2017 NAICS updated were used to create the 2017 Census industry code list, which was first applied to the 2019 ACS, The revision included 19 new codes ('1691', '3291', '4971', '4972', '5381', '5391', '5393', '6991', '6992', '7071', '7072', '7181', '8191', '8192', '8561', '8562', '8563', '8564', '8891'), 17 deletions ('1680', '1690', '3190', '3290', '4970', '5380', '5590', '5591', '5592', '6990', '7070', '7170', '7180', '8190', '8560', '8880', '8890') and 18 title changes. These changes make the 2017 Census industry codes only partially comparable with previous years.

For more information, see the 2017 Census Industry Code List within the 2019 ACS Code List. Go to (http://www.census.gov) and enter "“ACS Code Lists, Definitions, and Accuracy" in the search box.

See also Occupation and Class of Worker.

See Employment Status.

The data on marital status and marital history were derived from answers to Questions 20 through 23 in the 2019 American Community Survey. The marital status question is asked to determine the status of the person at the time of interview. Many government programs need accurate information on marital status, such as the number of married women in the labor force, elderly widowed individuals, or young single people who may establish homes of their own. The marital history data enables multiple agencies to more accurately measure the effects of federal and state policies and programs that focus on the well-being of families. Marital history data can provide estimates of marriage and divorce rates and duration, as well as flows into and out of marriage. This information is critical for more refined analyses of eligibility for program services and benefits, and of changes resulting from federal policies and programs.

Before 2008, the marital status question was asked of all people. Beginning in 2008, the question on marital status was asked only for people 15 years old and over. People 15 and over were asked whether they were "now married," "widowed," "divorced," "separated," or "never married." People in common-law marriages were allowed to report the marital status they considered the most appropriate. When marital status was not reported, it was imputed according to the person's relationship to the householder, sex, and age.

Differences in the number of married males and females occur because there is no step in the weighting process to equalize the weighted estimates of husbands and wives.

See Journey to Work.

See Residence 1 Year Ago.

The native population includes anyone who was a U.S. citizen or a U.S. national at birth. This includes respondents who indicated they were born in the United States, Puerto Rico, a U.S. Island Area (such as Guam), or abroad of American (U.S. citizen) parent or parents. See Citizenship Status.

See Place of Birth.

Nativity of parent indicates the nativity (native or foreign born) of the parent(s) of children living in a family or subfamily with one or more parents present in the household. It applies to "own children," that is, never married children under 18 years of age living with one or more of their parents. (See also "Own Child.") The nativity of the child's parent(s) is determined by the citizenship status of the parent(s). A person is considered native if he/she is a native United States citizen at birth, and foreign born if he/she is not a United States citizen at birth. (See also "Place of Birth.")

Limitation of the Data - Nativity of parent does not provide information about children over the age of 18 who may live in the same household as their parents, or children of any age who live apart from their parents.

Comparability - No comparable data were published prior to 2006. However, prior years do include the nativity and relationship data from which "nativity of parent" was created.

Occupation describes the kind of work a person does on the job. Occupation data were derived from answers to questions 45 and 46 in the 2013 American Community Survey. Question 45 asks: "What kind of work was this person doing?" Question 46 asks: "What were this person's most important activities or duties?"

These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person's job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.

These questions describe the work activity and occupational experience of the American labor force. Data are used to formulate policy and programs for employment, career development and training; to provide information on the occupational skills of the labor force in a given area to analyze career trends; and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

Coding Procedures - Occupation statistics are compiled from data that are coded based on the Standard Occupational Classification (SOC) Manual: 2019 (http://www.bls.gov/soc), published by the Executive Office of the President, Office of Management and Budget. Census occupation codes, based on the 2019 SOC, provide 569 specific occupational categories, for employed people, including military, arranged into 23 major occupational groups, plus an additional Census code for the unemployed, with no work experience in the last 5 years or earlier or never worked for a total of 570 Census occupation codes.

Respondents provided the data for the tabulations by writing on the questionnaires descriptions of the kind of work and activities they are doing. These write-ins are converted to a code category through automated coding. Cases not autocoded on both industry and occupation are sent to the clerical staff in the National Processing Center (NPC) in Jeffersonville, Indiana, who assign codes by comparing these descriptions to entries in the Alphabetical Index of Industries and Occupations (https://www.census.gov/topics/employment/industry-occupation/guidance/indexes.html).

Some occupation groups are related closely to certain industries. Operators of transportation equipment, farm operators and workers, and healthcare providers account for major portions of their respective industries of transportation, agriculture, and health care. However, the industry categories include people in other occupations. For example, people employed in agriculture include truck drivers and bookkeepers; people employed in the transportation industry include mechanics, freight handlers, and payroll clerks; and people employed in the health care industry include janitors, security guards, and secretaries.

Editing Procedures - Following the coding operation, a computer edit and allocation process excludes all responses that should not be included in the universe, and evaluates the consistency of the remaining responses. The codes for occupation are checked for consistency with the industry and class of worker data provided for that respondent. Occasionally respondents supply occupation descriptions that are not sufficiently specific for precise classification, or they do not report on these questions at all. Certain types of incomplete entries are corrected using the Alphabetical Index of Industries and Occupations. If one or more of the three codes (occupation, industry, or class of worker) is blank after the edit, a code is assigned from a donor respondent who is a "similar" person based on questions such as age, sex, educational attainment, income, employment status, and weeks worked. If all of the labor force and income data are blank, all of these economic questions are assigned from a "similar" person who had provided all the necessary data.

Question/Concept History - OOccupation data have been collected during decennial censuses since 1850. Starting with the 2010 Census, occupation data was no longer collected during the decennial census. Long form data collection has transitioned to the ACS. The ACS began collecting data on occupation in 1996. The questions on occupation were designed to be consistent with the 1990 Census questions on occupation. ACS questions on occupation have remained consistent between 1996 and 2019.

Limitation of the Data - Beginning in 2006, the population in group quarters (GQ) was included in the ACS. Some types of GQ populations have occupational distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the occupational distribution in some geographic areas with a substantial GQ population.

Data on occupation, industry, and class of worker are collected for the respondent's current primary job or the most recent job for those who are not employed but have worked in the last 5 years. Other labor force questions, such as questions on earnings or work hours, may have different reference periods and may not limit the response to the primary job. Although the prevalence of multiple jobs is low, data on some labor force items may not exactly correspond to the reported occupation, industry, or class of worker of a respondent.

Comparability - Comparability of occupation data was affected by a number of factors, primarily the system used to classify the questionnaire responses. Changes in the occupational classification system limit comparability of the data from one year to another. These changes are needed to recognize the "birth" of new occupations, the "death" of others, the growth and decline in existing occupations, and the desire of analysts and other users for more detail in the presentation of the data. Probably the greatest cause of noncomparability is the movement of a segment from one category to another. Changes in the nature of jobs, respondent terminology, and refinement of category composition made these movements necessary.

ACS data from 1996 to 1999 used the same occupation classification systems used for the 1990 Census; therefore, the data are comparable. Since 1990, the occupation classification has been revised to reflect changes within the Standard Occupational Classification (SOC). The SOC was updated in 2000 and these changes were reflected in the Census 2000 occupation codes. For more information on occupational comparability across classification systems, please see technical paper #65: The Relationship Between the 1990 Census and Census 2000 Industry and Occupation Classification Systems (https://www.census.gov/content/dam/Census/library/workingpapers/2003/demo/techpaper2000.pdf). The 2000-2002 ACS data used the same occupation classification systems used for Census 2000; therefore, the data are comparable. Because of the possibility of new occupations being added to the list of codes, the Census Bureau needed to have more flexibility in adding codes. Consequently, in 2002, Census occupation codes were expanded from three-digit codes to four-digit codes. For occupation, this entailed adding a "0" to the end of each occupation code. The SOC was revised once more in 2010. Based on the 2010 SOC changes, Census codes were revised resulting in a net gain of 30 Census occupation codes (from 510 occupations to 540 occupations). Most of these changes were concentrated in information technology, healthcare, printing, and human resources occupations. The SOC was revised once again in 2019. Based on the 2019 SOC changes, the Census codes were revised resulting in a net gain of 30 Census occupation codes (from 540 occupations to 570 occupations). The 2019 Census occupation codes were first applied to the 2019 ACS. The 2019 Census occupation codes changes These substantive changes across multiple occupation groups make the 2019 Census occupation codes non-comparable with previous years without the use of the occupation crosswalk and conversion rates. For information on the 2019 SOC and Census occupation codes, please see the 2019 Census Occupation Codes with Crosswalk document, which includes the summary of 2019 changes and the Census 2010 to 2019 occupation codes crosswalk on the Industry and Occupation Code Lists & Crosswalks page (https://www.census.gov/topics/employment/industryoccupation/guidance/code-lists.html).

For more information, see the Census Occupation Code List found within the 2019 ACS Code List. Go to https://data.census.gov. and enter "ACS Code Lists, Definitions, and Accuracy" in the search box.

See also, Industry and Class of Worker.

See Household Type and Relationship.

See Veteran Status.

See Household Type and Relationship.

See Household Type and Relationship.

The data on place of birth were derived from answers to Question 7 in the 2019 American Community Survey. Respondents were asked to select one of two categories: (1) in the United States, or (2) outside the United States. In the American Community Survey, respondents selecting category (1) were then asked to report the name of the state while respondents selecting category (2) were then asked to report the name of the foreign country, or Puerto Rico, Guam, etc. In the Puerto Rico Community Survey, respondents selecting category (1) were also asked to report the name of the state, while respondents selecting category (2) were then asked to print Puerto Rico or the name of the foreign country, or U.S. Virgin Islands, Guam, etc. People not reporting a place of birth were assigned the state or country of birth of another family member, or were allocated the response of another individual with similar characteristics. People born outside the United States were asked to report their place of birth according to current international boundaries. Since numerous changes in boundaries of foreign countries have occurred in the last century, some people may have reported their place of birth in terms of boundaries that existed at the time of their birth or emigration, or in accordance with their own national preference.

The place of birth questions along with the citizenship status question provide essential data for setting and evaluating immigration policies and laws. Knowing the characteristics of immigrants helps legislators and others understand how different immigrant groups are assimilated. Federal agencies require these data to develop programs for refugees and other foreign-born individuals. Vital information on lifetime migration among states also comes from the place of birth question.

See Journey to Work.

Poverty statistics in American Community Survey products adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) vary by age (under 65 years or 65 years and older). The poverty thresholds for two-person families also vary by the age of the householder. If a family's total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual's total income is less than the appropriate threshold, then that individual is considered to be in poverty.

See Journey to Work.

The data on race were derived from answers to the question on race that was asked of all people (Question 6 in the 2019 American Community Survey (ACS)). The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race item include racial and national origin or sociocultural groups. People may choose to report more than one race to indicate their racial mixture, such as "American Indian" and "White." People who identify their origin as Hispanic, Latino, or Spanish may be of any race.

The racial classifications used by the Census Bureau adhere to the October 30, 1997, Federal Register notice entitled, "Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity" issued by OMB. These standards govern the categories used to collect and present federal data on race and ethnicity. OMB requires five minimum categories (White, Black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander) for race. The race categories are described below with a sixth category, "Some Other Race," added with OMB approval. In addition to the five race groups, OMB also states that respondents should be offered the option of selecting one or more races.

If an individual did not provide a race response, the race or races of the householder or other household members were imputed using specific rules of precedence of household relationship. For example, if race was missing for a natural-born child in the household, then either the race or races of the householder, another natural-born child, or spouse of the householder were imputed.

If race was not reported for anyone in the household, then the race or races of a householder in a previously processed household were imputed.
Definitions from OMB guide the Census Bureau in classifying written responses to the race question:

The data on employment status and journey to work relate to the reference week, that is, the calendar week preceding the date on which the respondents completed their questionnaires or were interviewed. This week is not the same for all respondents since the interviewing was conducted over a 12-month period. The occurrence of holidays during the relative reference week could affect the data on actual hours worked during the reference week, but probably had no effect on overall measurement of employment status.

See Household Type and Relationship.

The data on residence 1 year ago were derived from answers to Question 15 in the 2019 American Community Survey, which were asked of the population 1 year and older. For the American Community Survey, people who had moved from another residence in the United States or Puerto Rico 1 year earlier were asked to report the exact address (number and street name); the name of the city, town, or post office; the name of the U.S. county or municipio in Puerto Rico; state or Puerto Rico; and the ZIP Code where they lived 1 year ago. People living outside the United States and Puerto Rico were asked to report the name of the foreign country or U.S. Island Area where they were living 1 year ago.

For the Puerto Rico Community Survey, people who moved from another residence in Puerto Rico or the United States 1 year ago were asked to report the exact address, including the development or condominium name; the name of the city, town, or post office; the municipio in Puerto Rico (county equivalent) or county in the U.S.; and the ZIP Code where they lived. People living outside Puerto Rico and the United States were asked to report the name of the foreign country or U.S. Island Area where they were living 1 year ago.

Residence 1 year ago is used in conjunction with location of current residence to determine the extent of residential mobility of the population and the resulting redistribution of the population across the various states, metropolitan areas, and regions of the country.

When no information on previous residence was reported for a person, information for other family members, if available, was used to assign a location of residence 1 year ago. All cases of nonresponse or incomplete response that were not assigned a previous residence based on information from other family members were allocated the previous residence of another person with similar characteristics who provided complete information.

The tabulation category, "Same house," includes all people 1 year and over who did not move during the 1 year as well as those who had moved and returned to their residence 1 year ago. The category, "Different house in the United States" includes people who lived in the United States 1 year ago but in a different house or apartment from the one they occupied at the time of interview. These movers are then further subdivided according to the type of move.

In most tabulations, movers within the U.S. are divided into three groups according to their previous residence: "Different house, same county," "Different county, same state," and "Different state." The last group may be further subdivided into region of residence 1 year ago. An additional category, "Abroad," includes those whose previous residence was in a foreign country, Puerto Rico, American Samoa, Guam, the Northern Marianas, or the U.S. Virgin Islands, including members of the Armed Forces and their dependents. Some tabulations show movers who were residing in Puerto Rico or one of the U.S. Island Areas 1 year ago separately from those residing in foreign countries.

In most tabulations, movers within Puerto Rico are divided into two groups according to their residence 1 year ago: "Same municipio" and "Different municipio." Other tabulations show movers within or between metropolitan areas similar to the stateside tabulations.

School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.

Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2019 American Community Survey. People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to "include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree." Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in "vocational, technical, or business school" such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.

The data on sex were derived from answers to Question 3 in the 2019 American Community Survey. Individuals were asked to mark either "male" or "female" to indicate their biological sex. For most cases in which sex was invalid, the appropriate entry was determined from other information provided for that person, such as the person's given (i.e., first) name and household relationship. Otherwise, sex was allocated from a hot deck.

Sex is asked for all persons in a household or group quarters. On the mailout/mailback paper questionnaire for households, sex is asked for all persons listed on the form. This form accommodates asking sex for up to 12 people listed as living or residing in the household for at least 2 months. If a respondent indicates that more people are listed as part of the total persons living in the household than the form can accommodate, or if any person included on the form is missing sex, then the household is eligible for Failed Edit Follow-up (FEFU). During FEFU operations, telephone center staffers call respondents to obtain missing data. This includes asking sex for any person in the household missing sex information. In Computer Assisted Telephone Interviews (CATI) and Computer Assisted Personal Interview (CAPI) instruments sex is asked for all persons. In 2006, the ACS began collecting data in group quarters (GQs). This included asking sex for persons living in a group quarters. For additional data collection methodology, please see https://www.census.gov/programs-surveys/acs/.

Data on sex are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. The sex data collected on the forms are aggregated and provide the number of males and females in the population. These data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. Data about sex are critical because so many federal programs must differentiate between males and females. The U.S. Departments of Education and Health and Human Services are required by statute to use these data to fund, implement, and evaluate various social and welfare programs, such as the Special Supplemental Food Program for Women, Infants, and Children (WIC) or the Low-Income Home Energy Assistance Program (LIHEAP). Laws to promote equal employment opportunity for women also require census data on sex. The U.S. Department of Veterans Affairs must use census data to develop its state projections of veterans' facilities and benefits. For more information on the use of sex data in Federal programs, please see "ACS Handbook of Questions and Current Federal Uses."

See Income in the Past 12 Months.

See Household Type and Relationship.

See Journey to Work.

See Journey to Work.

See School Enrollment.

See Work Experience.

Data on veteran status and period of military service were derived from answers to Questions 26 and 27 in the 2019 American Community Survey.

See Work Experience.

The data on work experience were derived from answers to Questions 38, 39, and 40 in the 2019 American Community Survey. This term relates to work status in the past 12 months, weeks worked in the past 12 months, and usual hours worked per week worked in the past 12 months.

To comply with provisions of the Civil Rights Act, the U.S. Department of Justice uses these data to determine the availability of individuals for work. Government agencies, in considering the programmatic and policy aspects of providing federal assistance to areas, have emphasized the requirements for reliable data to determine the employment resources available. Data about the number of weeks and hours worked last year are essential because these data allow the characterization of workers by full-time/part-time and full-year/part-year status. Data about working last year are also necessary for collecting accurate income data by defining the universe of persons who should have earnings as part of their total income.

See Work Experience.

The data on year of entry were derived from answers to Question 9 in the 2019 American Community Survey. This question was asked about Persons 1 through 5 in the ACS, and was restricted to those persons who on Question 8 answered that they were in citizenship categories (2) born in Puerto Rico, Guam, the U.S. Virgin Islands, or Northern Marianas, (3) born abroad of U.S. citizen parent or parents, (4) U.S. citizen by naturalization, or (5) not a U.S citizen.

All respondents born outside the United States were asked for the year in which they came to live in the United States. This includes people born in Puerto Rico and U.S. Island Areas; people born abroad of an U.S. citizen parent or parents; and the foreign born. (See "Citizenship Status.") For the Puerto Rico Community Survey, respondents were asked for the year in which they came to live in Puerto Rico.

The responses to this question indicate when persons born outside of the U.S. came to live in the United States.

Question/Concept History

Since 1996, the year of entry questions for the American Community Survey and for the Puerto Rico Survey were identical. An instruction was added beginning in 1999 to "Print numbers in boxes."

Limitation of the Data

Respondents were directed to indicate the year they entered the U.S. "to live" (or "to live" in Puerto Rico, for the Puerto Community Survey). For respondents who entered the U.S. (or entered Puerto Rico for the Puerto Rico Community Survey) multiple times, the interviewers were instructed to request the most recent year of entry. For respondents who entered multiple times and did not ask the interviewer for clarification or who mailed back the questionnaire without being interviewed in person, it is unclear which year of entry was provided (i.e. first or most recent).

Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations may have year of entry distributions that are different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the year of entry distribution. This is particularly true for areas with substantial GQ populations.

Comparability

Year of entry was comparable across ACS years. A note of caution when comparing ACS and Census 2000 year of entry data: Census 2000 represents data collected as of April 1, 2000 and thus the "2000" year of entry category accounts only for the first quarter (Jan-Mar) in 2000. In comparison, the ACS represents data collected throughout the entire year and thus the "2000" year of entry category accounts for the entire year of 2000. For more information, go to https://data.census.gov and enter "Comparing ACS Data" in the search box.

See "Mean."

See "Mean."

The Gini is a measure of how much a distribution varies from a proportionate distribution. A purely proportionate distribution would have every value in the distribution being equal (that is 20% of the values would equal 20% of the aggregate total of all the values). This is also known as "perfect equality" - all households have an equal share of income. An example of a distribution that deviates the most from perfect equality would be have every value except one equal to zero, and one value that would be equal to the nonzero aggregate total for all the values. This is also known as "perfect inequality" - one household has all income.

The Gini ranges from zero (perfect equality) to one (perfect inequality), and it is calculated by measuring the difference between a diagonal line (the purely proportionate distribution) and the distribution of actual values (a Lorenz curve). This measure is presented for household income.

Interpolation is frequently used to calculate medians or quartiles and to approximate standard errors from tables based on interval data. Different kinds of interpolation may be used to estimate the value of a function between two known values, depending on the form of the distribution. The most common distributional assumption is that the data are linear, resulting in linear interpolation.

This measure represents an arithmetic average of a set of values. It is derived by dividing the sum (or aggregate) of a group of numerical questions by the total number of questions in that group. For example, mean household earnings is obtained by dividing the aggregate of all earnings reported by individuals with earnings living in households by the total number of households with earnings. (Additional information on means and aggregates is included in the separate explanations of many population and housing variables.)

This measure represents the middle value (if n is odd) or the average of the two middle values (if n is even) in an ordered list of n data values. The median divides the total frequency distribution into two equal parts: one-half of the cases falling below the median and one-half above the median. Each median is calculated using a standard distribution (see below). (For more information, see "Interpolation.")

For data products displayed in American FactFinder, medians that fall in the upper-most category of an open-ended distribution will be shown with a plus symbol (+) appended (e.g., "$2,000+" for contract rent), and medians that fall in the lowest category of an open-ended distribution will be shown with a minus symbol (-) appended (e.g., "$100- for contract rent"). For other data products and data files that are downloaded by users (i.e., FTP files), plus and minus signs will not be appended. Contract Rent, for example will be shown as $2001 if the median falls in the upper-most category ($2,000 or more) and $99 if the median falls in the lowest category (Less than $100). (The "Median Standard Distributions" section in Appendix A shows the open-ended intervals for medians.)

This measure is calculated by taking the number of questions in a group possessing a characteristic of interest and dividing by the total number of questions in that group, and then multiplying by 100.

This measure divides a distribution into four equal parts. The first quartile (or lower quartile) is the value that defines the upper limit of the lowest one-quarter of the cases. The second quartile is the median. The third quartile (or upper quartile) is defined as the upper limit of the lowest three quarters of cases in the distribution. Quartiles are presented for certain financial characteristics such as housing value and contract rent. The distribution used to compute quartiles is the same as that used to compute medians for that variable.

This measure divides a distribution into five equal parts. The first quintile (or lowest quintile) is the value that defines the upper limit of the lowest one-fifth of the cases. The second quintile is the 40th percentile. The third quintile is the 60th percentile. The fourth quintile is defined as the upper limit of the lowest four fifths of cases in the distribution, or the 80th percentile. Quintiles are presented for household incomes.

This is a measure of occurrences in a given period of time divided by the possible number of occurrences during that period. For example, the homeowner vacancy rate is calculated by dividing the number of vacant units "for sale only" by the sum of owner-occupied units and vacant units that are "for sale only," and then multiplying by 100. Rates are sometimes presented as percentages.

This is a measure of the relative size of one number to a second number expressed as the quotient of the first number divided by the second. For example, the sex ratio is calculated by dividing the total number of males by the total number of females, and then multiplying by 100.

Measures describing the quality of the American Community Survey (ACS) sample and the data collected by the ACS - including sample sizes, coverage rates, and response rates - are available for 2000 through the current data year on the ACS web page, at http://www.census.gov/acs/www/methodology/sample_size_and_data_quality. The quality measures illustrate the steps the Census Bureau takes to ensure that ACS survey data are accurate and reliable.

Since 2007, the quality measures have also been available through American FactFinder in the B98* series of Detailed Tables. Go to http://factfinder.census.gov and select "Advanced Search" to enter the table number.

Beginning in 2018, quality measures available since 2010 are available through https://data.census.gov. Go to https://data.census.gov. and enter "B98" for the full list or a specific table ID in the search box.

There are two kinds of coverage error: under-coverage and over-coverage. Under-coverage exists when housing units or people do not have a chance of being selected in the sample. Over-coverage exists when housing units or people have more than one chance of selection in the sample, or are included in the sample when they should not have been. If the characteristics of under-covered or over-covered housing units or individuals differ from those that are selected, the ACS may not provide an accurate picture of the population.

The coverage rates measure coverage error in the ACS. The coverage rate is the ratio of the ACS population or housing estimate of an area or group to the independent estimate for that area or group, times 100.

Coverage rates for the total resident population are calculated by sex at the national, state, and Puerto Rico levels, and at the national level only for total Hispanics, and non-Hispanics crossed by the five major race categories: White, Black, American Indian and Alaska Native, Asian, and Native Hawaiian and Other Pacific Islander. The total resident population includes persons in both housing units and group quarters. In addition, a coverage rate that includes only the group quarters population is calculated at the national level. Coverage rates for housing units are calculated at the national and state level, except for Puerto Rico because independent housing unit estimates are not available. These rates are weighted to reflect the probability of selection into the sample, the subsampling for personal visit follow-up, and non-response adjustment.

The survey response rate is the ratio of the estimate of units interviewed after data collection is complete to the estimate of all units that should have been interviewed. Separate rates are calculated for housing unit response and GQ person response. For housing units, this means all interviews after mail, telephone and personal visit follow-up. For GQ persons, this means all interviews after the personal visit. Interviews include complete and partial interviews with enough information to be processed.

All final noninterviews have been grouped into one of the following Reasons for Noninterviews:

Refusal: Even though the ACS is a mandatory survey and households whose addresses are selected and GQ persons who are selected for the survey are required to answer the survey questions, a few are reluctant to cooperate and refuse to participate.

Unable to Locate: If the interviewer cannot find the sample address after using all possible sources, they consider it "unable to locate." For GQ persons, the individual could not be located.

No One Home: Interviewers assign this code if they could not find anyone at the housing unit during the entire month's interview period. There is no equivalent rate for GQ persons.

Temporarily Absent: The interviewers confirm that all household members or the GQ person are away during the entire month's interview period on vacation, a business trip, or caring for sick relatives.

Language Problem: The interviewer could not conduct an interview because of language barriers, was not able to get an interpreter who could translate, and the supervisor or regional office could not help complete this case.

Insufficient Data: To be considered an interviewed unit in ACS, a household or GQ person's response needs to have a minimum amount of data. Occupied housing units and GQ persons not meeting this minimum are treated as noninterviews in the estimation process. Responses for vacant housing units are not subject to a minimum data requirement.

Other: Unique situations when the reason for noninterview does not fit into one of the classifications described above. Possible reasons include "death in the family," "household quarantined," or "roads impassable."

Whole GQ Refusal: Some group quarters refuse to allow the ACS to interview any of their residents, citing legal or other reasons.

Whole GQ Other: These account for other situations where no one in the GQ was interviewed due to reasons other than refusals.

Missing data for a particular question or item is called item nonresponse. It occurs when a respondent fails to provide an answer to a required item. The ACS also considers invalid answers as item nonresponse. The Census Bureau uses imputation methods that either use rules to determine acceptable answers or use answers from similar housing units or people who provided the item information. One type of imputation, allocation, involves using statistical procedures, such as within-household or nearest neighbor matrices populated by donors, to impute for missing values.

Overall Person Characteristic Imputation Rate - This rate is calculated by adding together the weighted number of allocated items across a set of person characteristics, and dividing by the total weighted number of responses across the same set of characteristics.

Overall Housing Characteristic Imputation Rate - This rate is calculated by adding together the weighted number of allocated items across a set of household and housing unit characteristics, and dividing by the total weighted number of responses across the same set of characteristics.

These rates give an overall picture of the rate of item nonresponse for a geographic area.

Please see Appendix A.pdf