Graph and download economic data for Housing Inventory Estimate: Vacant Housing Units for Rent in the United States (ERENTUSQ176N) from Q2 2000 to Q1 2025 about vacancy, inventories, rent, housing, and USA.

United States Number of Housing Unit: Vacant: Year Round: Other Reasons data was reported at 4,146.000 Unit th in Jun 2018. This records an increase from the previous number of 4,006.000 Unit th for Mar 2018. United States Number of Housing Unit: Vacant: Year Round: Other Reasons data is updated quarterly, averaging 2,142.500 Unit th from Mar 1965 (Median) to Jun 2018, with 214 observations. The data reached an all-time high of 4,146.000 Unit th in Jun 2018 and a record low of 931.000 Unit th in Dec 1970. United States Number of Housing Unit: Vacant: Year Round: Other Reasons data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.EB011: Number of Housing Units. Series Remarks1. Data for 1979 Q1 to Q4 was revised to reflect changes made in 1980.2. Data for 1989 Q1 to Q4 was revised to include year-round vacant mobile homes.3. Data for 1993 Q1 to Q4 was revised based on the 1990 Census.4. Data for 2002 Q1 to Q4 was revised based on the 2000 Census.

Mail carriers routinely collect data on address no longer receiving mail due to vacancy. This vacancy data is reported quarterly at census tract geographies in the United States for residential, commercial, and industrial properties along with counts of total mailing addresses.

Preprocessing/Formatting

The data is split into separate tables because different decades of data use different US Census geographies (e.g., 2010 U.S. Census tracts).

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

Number of vacant properties Source: Census 2001 Publisher: Neighbourhood Statistics Geographies: Output Area (OA), Lower Layer Super Output Area (LSOA), Middle Layer Super Output Area (MSOA), Ward, Local Authority District (LAD), Government Office Region (GOR), National Geographic coverage: England Time coverage: 2001 Type of data: Survey (census)

This data calculates the number of dwellings per hectare in each LSOA in the West of England and North Somerset, using the below data –(1) Dwellings dataThe selected dataset provides Census 2021 estimates on the number of dwellings in England and Wales. The estimates are as at Census Day, 21 March 2021.Dwelling definition“A dwelling is a unit of accommodation that may be empty or being lived in, for example houses or flats. They are usually made up of one household, but those with more than one household are shared and called a “shared dwelling”.If a dwelling has no usual residents living in them, for example they are empty after being sold, these are called “unoccupied dwellings” but may be used by short-term residents or visitors on Census Day, 21 March 2021, for example holiday homes.” (ONS)(2) Hectares dataTaken from: Standard Area Measurements for 2021 Statistical Geographies (March 2021) in EW (V2)Column used: Land count (Area in Hectares)

Dataset contains occupied and unoccupied private dwelling counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the occupied and unoccupied private dwelling counts between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by regional council.

Map shows the percentage change in number of occupied and unoccupied private dwellings between the 2018 and 2023 Censuses.

Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Dwelling occupancy status quality rating

Dwelling occupancy status is rated as high quality.

Dwelling occupancy status – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Dwelling type quality rating

Dwelling type is rated as moderate quality.

Dwelling type – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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This layer shows vacant housing by type (for rent/sale, vacation home, etc.). This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.This layer is symbolized to show the percent of housing units that are vacant. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B25004, B25002, B25003 (Not all lines of ACS tables B25002 and B25003 are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

All data are 2020 Census Tract (neighborhood) level five-year estimates from the U.S. Census Bureau American Community Survey from 2017 to 2021. Median household income earned in the past 12 months. Includes 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. Median home value (an estimate of how much the property would sell for if it were for sale) for properties owned, being bought, vacant for sale, or sold but not occupied at the time of the survey. Data are based on values reported by property owners. Median real estate taxes (due to all taxing jurisdictions) for owner-occupied properties are based on taxes reported by homeowners to the Census Bureau in the American Community Survey from 2017 to 2021.

This table contains data described by the following dimensions (Not all combinations are available): Geography (69 items: Saguenay; Quebec; Census metropolitan areas; Census metropolitan areas and large urban areas; Calgary; Alberta ...), Type of unit (2 items: Single-detached and semi-detached units; Row; apartment and other unit types ...).

United States Number of Housing Unit: Vacant: Year Round: For Rent data was reported at 3,343.000 Unit th in Sep 2018. This records an increase from the previous number of 3,206.000 Unit th for Jun 2018. United States Number of Housing Unit: Vacant: Year Round: For Rent data is updated quarterly, averaging 2,802.000 Unit th from Mar 1965 (Median) to Sep 2018, with 215 observations. The data reached an all-time high of 4,588.000 Unit th in Sep 2009 and a record low of 1,120.000 Unit th in Dec 1969. United States Number of Housing Unit: Vacant: Year Round: For Rent data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.EB011: Number of Housing Units. Series Remarks Data for 1979 Q1 to Q4 was revised to reflect changes made in 1980. Data for 1989 Q1 to Q4 was revised to include year-round vacant mobile homes. Data for 1993 Q1 to Q4 was revised based on the 1990 Census. Data for 2002 Q1 to Q4 was revised based on the 2000 Census.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling and person

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: Every separate and independent structure that has been constructed or converted for use as temporary or permanent housing. This includes any class of fixed or mobile shelter used as a place of lodging at the time of enumeration. A dwelling can be a) a private house, apartment, floor in a house, room or group of rooms, ranch, etc. designed to give lodging to one person or a group of people or b) a boat, vehicle, railroad car, barn, shed, or any other type of shelter occupied as a place of lodging at the time of enumeration. - Households: All the occupying members of a family or private dwelling that live together as family. In most cases, a household is made up of a head of the family, relatives of this person (wife or partner, children, grand-children, nieces and nephews, etc.), close friends, guests, lodgers, domestic employees and all other occupants. Households with five or fewer lodgers are considered private,but households with six or more lodgers are considered a non-family group. - Group quarters: Accommodation for a group of people who are not usually connected by kinship ties who live together for reasons of discipline, healthcare, education, mlitary activity, religion, work or other dwellings such as reform schools, boarding schools, barracks, hopsitals, guest houses, nursing homes, workers camps, etc.

Universe

Population in private and communal housing

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the Minnesota Population Center

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 268,248

Mode of data collection

Face-to-face [f2f]

Research instrument

Single record that includes housing and population questionnaires

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: Armed forces, nomads, Jordanians abroad

UNIT DESCRIPTIONS: - Dwellings: Housing unit is a building or part of it with walls and ceiling, virtuous for residence of one or more household regardless of its occupancy at time of census. For the census purposes, each occupied place at time of the census is considered as a housing unit whether designated for use as shops. - Households: One person or more living in a separated housing unit or part of it. For the census purposes, there are two kinds of households, the private household and the collective household. - Group quarters: Collective housing unit is a housing unit designed for the residence of groups of individual with similar conditions, special cases or having common objectives such as prisons, hospitals, old-age houses, orphan-homes, students' hostels, doctors and nurses hostels, workers' camps, hotel and hotel's suites.

Universe

All population inside Jordan regardless of their nationality and Jordanians abroad for less than one year

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: The Department of Statistics

SAMPLE DESIGN: Systematic sample of every 10th private household or every 10th person in collective households with a random start, combined with stratification. Drawn by the country. Thirty formed strata include 6 cities with over 100,000 population, 12 urban strata and 12 rural strata.

SAMPLE UNIT: Private households or persons in collective households

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 510,646

Mode of data collection

Face-to-face [f2f]

Research instrument

Five types of register are used: 1) private household register, 2) collective household register, and 3) hotel lodgers register, and 4) buildings and housing units register for both private and collective households, and 5) reminder questionnaire.

Response rate

COVERAGE: 95.9% (official estimates)

This file contains the initial 2010 census population and housing data at the census block level for blocks defined as being in the City of Houston by the Census Bureau. The population and housing totals in this file represent summarizations of the 288 data items in the original census files. Specifically, populations are aggregated for Hispanic ethnicity and Non-Hispanic populations by 7 racial categories. These same aggregations are available for voting age populations (18 years and over). Housing data is limited to total, vacant and occupied units.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling and person

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: Any room or set of rooms and their components that occupy a building or a structurally separate section of the building that, due to construction of modification, is intended for human habitation and is not being used for any other purpose at the time of enumeration. Any fixed or mobile shelter in which some person spent the night before the census day is also considered a dwelling. - Households: A person or group of people, related or not, that a share a common food budget. - Group quarters: Accommodation for the institutional population, or, people that are not integrated into private homes. This includes people not usually connected by kinship ties who share the dwelling for reasons of work, healthcare, studies, military activity, religion, tourism, etc., such as military installations, correctional institutions and prisons, dormitories of religious institutions, hospitals, student residences, hotels, etc.

Universe

Population in private and communal housing

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the Minnesota Population Center

SAMPLE UNIT: Dwelling

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 315,920

Mode of data collection

Face-to-face [f2f]

Research instrument

Single record that includes housing, home, and population questionnaires

This layer was developed for public use of the most current median household income, median home value and median owner-occupied residential real estate taxes compiled by the US Census Bureau from the 2017 to 2021 American Community Survey at the Census Tract (neighborhood) level.

All data are 2020 Census Tract (neighborhood) level five-year estimates from the U.S. Census Bureau American Community Survey from 2017 to 2021. Median household income earned in the past 12 months. Includes 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. Median home value (an estimate of how much the property would sell for if it were for sale) for properties owned, being bought, vacant for sale, or sold but not occupied at the time of the survey. Data are based on values reported by property owners. Median real estate taxes (due to all taxing jurisdictions) for owner-occupied properties are based on taxes reported by homeowners to the Census Bureau in the American Community Survey from 2017 to 2021.

Frequency: OccasionalTable: 46-10-0038-01Release date: 2022-04-12Geography: Province or territory, Census subdivision, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partSymbol legend: .. / not available for a specific reference period x / suppressed to meet the confidentiality requirements of the Statistics Act A / data quality: excellentThe footnotes in the table are represented in brackets.1) The universe of this table is restricted to individual resident owners who occupy a residential property. An owner's geographic location is determined by the location of the occupied property for both single- and multiple-property owners. A residential property refers to all land and structures intended for private occupancy whether on a permanent or a temporary basis.2) The geographic boundaries used in this table are the 2016 census subdivisions boundaries.3) Previous reference period estimates are subject to revision.4) The Composite Quality Indicator (CQI) shown in this table is created by combining many individual quality indicators, each one representing the quality of different Canadian Housing Statistics Program (CHSP) data processing steps (for example: coding, geocoding, linkage and imputation) and includes the following values: A - Excellent: All domain variables and the variable of interest are of excellent quality. B - Very good: All domain variables and the variable of interest are of very good to excellent quality. C - Good: The quality of some of the domain variables or the variable of interest is considered good while all the other variables are of very good to excellent quality. D - Acceptable: The quality of some of the domain variables or the variable of interest is considered acceptable while all the other variables are of good to excellent quality. E - Use with caution: Several domain variables or the variable of interest are of poor quality. F - Too unreliable to be published. The CQIs are available starting with the reference period of 2020, except for the Northwest Territories where they are available from 2019 reference period.5) Property type" refers to property characteristics and/or dwelling configuration on which there can be one or more residential structures. Property types include single-detached houses, semi-detached houses, condominium apartments, mobile homes, other property types, properties with multiple residential units, and vacant land."6) Estimates by property type in Newfoundland and Labrador are only available in the census subdivision of St. John’s.7) Estimates by property type in Northwest Territories ires are not available.8) Estimates by property type in Nunavut are not available.9) The number of properties owned by the property owner is limited to residential properties that are within a given province.10) Newfoundland and Labrador estimates are not available at the provincial level and for the category “Outside of census metropolitan areas (CMAs) and census agglomerations (CAs)”.11) Northwest Territories estimates are only available in the census agglomeration of Yellowknife.12) Counts undergo random rounding, a process that transforms all raw counts into randomly rounded counts. This reduces the possibility of identifying individuals in the tabulations. All percentages are derived from rounded counts, subtotals and totals may not exactly equal the sum of components due to system rounding.13) The number of property owners estimates are not available for the 2018 reference period.14) The number of owners should be used with caution outside of census metropolitan areas (CMAs) and census agglomerations (CAs), as well as the proportion of owners by geography. This note does not apply to Nunavut.15) Assessment value" refers to the assessed value of the property for the purposes of determining property taxes. It is important to note that the assessed value does not necessarily represent the market value. Given that different provinces and territories have their own assessment periods and duration of the valuation roll it is difficult to make accurate comparisons of similar properties from one province or territory to another. For properties that are being utilized for both residential and non-residential purposes only the residential portion's value has been taken into account. The reference years of the assessment values by province or territory are available here: Canadian Housing Statistics Program (CHSP)."16) For Nunavut, the property use indicator is not available, the universe of this table includes all individual resident owners. For owners with multiple properties, the geographic location and type of property are from the residential property with the highest assessment value.17) Averages and medians are calculated using values greater than zero for the variables of interest.18) Total assessment value" represents the sum of the assessment values of all residential properties owned by an owner within a given province."19) Total income of person" refers to the total income of an individual, before deductions for income taxes, during the previous year. This income measure is the sum of market income and government transfers. Market income includes employment income, investment income, private retirement income and other income from market sources during the previous year. Government transfers refer to all cash benefits received from federal, provincial, territorial or municipal governments during the previous year."Cite: Statistics Canada. Table 46-10-0038-01 Single and multiple residential property owners: demographic data and value of properties ownedhttps://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=4610003801

Frequency: OccasionalTable: 46-10-0038-01Release date: 2022-04-12Geography: Province or territory, Census subdivision, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partSymbol legend:.. / not available for a specific reference periodx / suppressed to meet the confidentiality requirements of the Statistics ActA / data quality: excellentThe footnotes in the table are represented in brackets.1) The universe of this table is restricted to individual resident owners who occupy a residential property. An owner's geographic location is determined by the location of the occupied property for both single- and multiple-property owners. A residential property refers to all land and structures intended for private occupancy whether on a permanent or a temporary basis.2) The geographic boundaries used in this table are the 2016 census subdivisions boundaries.3) Previous reference period estimates are subject to revision.4) The Composite Quality Indicator (CQI) shown in this table is created by combining many individual quality indicators, each one representing the quality of different Canadian Housing Statistics Program (CHSP) data processing steps (for example: coding, geocoding, linkage and imputation) and includes the following values: A - Excellent: All domain variables and the variable of interest are of excellent quality. B - Very good: All domain variables and the variable of interest are of very good to excellent quality. C - Good: The quality of some of the domain variables or the variable of interest is considered good while all the other variables are of very good to excellent quality. D - Acceptable: The quality of some of the domain variables or the variable of interest is considered acceptable while all the other variables are of good to excellent quality. E - Use with caution: Several domain variables or the variable of interest are of poor quality. F - Too unreliable to be published. The CQIs are available starting with the reference period of 2020, except for the Northwest Territories where they are available from 2019 reference period.5) Property type" refers to property characteristics and/or dwelling configuration on which there can be one or more residential structures. Property types include single-detached houses, on which there can be one or more residential structures. Property types include single-detached houses, condominium apartments, mobile homes, other property types, properties with multiple residential units, and vacant land."6) Estimates by property type in Newfoundland and Labrador are only available in the census subdivision of St. John’s.7) Estimates by property type in Northwest Territories are not available.8) Estimates by property type in Nunavut are not available.9) The number of properties owned by the property owner is limited to residential properties that are within a given province.10) Newfoundland and Labrador estimates are not available at the provincial level and for the category “Outside of census metropolitan areas (CMAs) and census agglomerations (CAs)”.11) Northwest Territories estimates are only available in the census agglomeration of Yellowknife.12) Counts undergo random rounding, a process that transforms all raw counts into randomly rounded counts. This reduces the possibility of identifying individuals in the tabulations. All percentages are derived from rounded counts, subtotals and totals may not exactly equal the sum of components due to system rounding.13) The number of property owners estimates are not available for the 2018 reference period.14) The number of owners should be used with caution outside of census metropolitan areas (CMAs) and census agglomerations (CAs), as well as the proportion of owners by geography. This note does not apply to Nunavut.15) Assessment value" refers to the assessed value of the property for the purposes of determining property taxes. It is important to note that the assessed value does not necessarily represent the market value. Given that different provinces and territories have their own assessment periods and duration of the valuation roll, it is difficult to make accurate comparisons of similar properties from one province or territory to another. For properties that are being utilized for both residential and non-residential purposes, only the residential portion's value has been taken into account. The reference years of the assessment values by province or territory are available here: Canadian Housing Statistics Program (CHSP)."16) For Nunavut, the property use indicator is not available, the universe of this table includes all individual resident owners. For owners with multiple properties, the geographic location and type of property are from the residential property with the highest assessment value.

Dataset contains occupied and unoccupied private dwelling counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the occupied and unoccupied private dwelling counts between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by territorial authority and Auckland local board

Map shows the percentage change in number of occupied and unoccupied private dwellings between the 2018 and 2023 Censuses.

Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

​

Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

​

Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Dwelling occupancy status quality rating

Dwelling occupancy status is rated as high quality.

Dwelling occupancy status – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Dwelling type quality rating

Dwelling type is rated as moderate quality.

Dwelling type – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

HUD’s Multifamily Housing property portfolio consist primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also include nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. HUD provides subsidies and grants to property owners and developers in an effort to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled. The portfolio can be broken down into two basic categories: insured, and assisted. The three largest assistance programs for Multifamily Housing are Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly, and Section 811 Supportive Housing for Persons with Disabilities. The Multifamily property locations represent the approximate location of the property. The locations of individual buildings associated with each property are not depicted here. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information (PII), the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. To learn more about Multifamily Housing visit: https://www.hud.gov/program_offices/housing/mfh, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov.Data Dictionary: DD_HUD Assisted Multifamily Properties Date of Coverage: 12/2023