Graph and download economic data for Housing Inventory Estimate: Seasonal Housing Units in the United States (ESEASONUSQ176N) from Q2 2000 to Q2 2025 about inventories, housing, and USA.

Graph and download economic data for Housing Inventory Estimate: Seasonal Housing Units in the West Census Region (ESEASONWEQ176N) from Q2 2000 to Q2 2025 about West Census Region, inventories, housing, and USA.

Housing Inventory Estimate: Seasonal Housing Units in the West Census Region was 766.00000 Thous. of Units in January of 2025, according to the United States Federal Reserve. Historically, Housing Inventory Estimate: Seasonal Housing Units in the West Census Region reached a record high of 970.00000 in July of 2008 and a record low of 578.00000 in January of 2002. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory Estimate: Seasonal Housing Units in the West Census Region - last updated from the United States Federal Reserve on July of 2025.

This layer shows vacant housing by type (for rent/sale, vacation home, etc.). This is shown by tract, county, and state centroids. 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 count and 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.

Housing Inventory Estimate: Seasonal Housing Units in the Northeast Census Region was 689.00000 Thous. of Units in January of 2025, according to the United States Federal Reserve. Historically, Housing Inventory Estimate: Seasonal Housing Units in the Northeast Census Region reached a record high of 1107.00000 in April of 2014 and a record low of 624.00000 in October of 2024. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory Estimate: Seasonal Housing Units in the Northeast Census Region - last updated from the United States Federal Reserve on July of 2025.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows vacant housing by type (for rent/sale, vacation home, etc.). This is shown by tract, county, and state boundaries. 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. Vintage: 2010-2014ACS 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: November 11, 2020National 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 has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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.

Housing characteristics (tenure, seasonal housing, vacant housing, value, rent, age of structure) and household characteristics (household size, families, marital status, presence of children, nonfamily households) as reported by the US Census Bureau for subcounty areas (townships, census tracts).

Housing characteristics (tenure, seasonal housing, vacant housing, value, rent, age of structure) and household characteristics (household size, families, marital status, presence of children, nonfamily households) as reported by the US Census Bureau.

Graph and download economic data for Housing Inventory Estimate: Seasonal Housing Units in the South Census Region (ESEASONSOQ176N) from Q2 2000 to Q2 2025 about South Census Region, inventories, housing, and USA.

Housing characteristics (tenure, seasonal housing, vacant housing, value, rent, age of structure) and household characteristics (household size, families, marital status, presence of children, nonfamily households) as reported by the US Census Bureau for census block groups (ie statistical subdivisions of county census tracts).

Housing Inventory Estimate: Seasonal Housing Units in the South Census Region was 1396.00000 Thous. of Units in January of 2025, according to the United States Federal Reserve. Historically, Housing Inventory Estimate: Seasonal Housing Units in the South Census Region reached a record high of 2027.00000 in July of 2012 and a record low of 1122.00000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory Estimate: Seasonal Housing Units in the South Census Region - last updated from the United States Federal Reserve on July of 2025.

United States Number of Housing Unit: Vacant: Seasonal data was reported at 4,011.000 Unit th in Sep 2018. This records an increase from the previous number of 3,970.000 Unit th for Jun 2018. United States Number of Housing Unit: Vacant: Seasonal data is updated quarterly, averaging 2,995.000 Unit th from Mar 1965 (Median) to Sep 2018, with 215 observations. The data reached an all-time high of 4,894.000 Unit th in Mar 2009 and a record low of 1,486.000 Unit th in Dec 1976. United States Number of Housing Unit: Vacant: Seasonal 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.

Housing Inventory Estimate: Seasonal Housing Units in the Midwest Census Region was 688.00000 Thous. of Units in January of 2025, according to the United States Federal Reserve. Historically, Housing Inventory Estimate: Seasonal Housing Units in the Midwest Census Region reached a record high of 1093.00000 in January of 2016 and a record low of 577.00000 in July of 2024. Trading Economics provides the current actual value, an historical data chart and related indicators for Housing Inventory Estimate: Seasonal Housing Units in the Midwest Census Region - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Housing Inventory Estimate: Seasonal Housing Units in the Midwest Census Region (ESEASONMWQ176N) from Q2 2000 to Q2 2025 about Midwest Census Region, inventories, housing, and USA.

This dataset contains Iowa vacant housing units estimate by vacancy status for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B25004. Vacancy status includes the following: Total, For rent, For sale only, Other vacant, Rented not occupied, Sold not occupied, For migrant workers, and For seasonal recreational or occasional use.

US Census 2020 Census Block geometries with IDs, permanent population, number of occupied housing units, and number of vacant housing units. Used to provide a permanent population per household value for buildings in the tsunami evacuation zone, and to provide seasonal occupancy per census block for use in temporary population assignment.

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.

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in these particular RGIS Clearinghouse tables are for New Mexico and all census tracts in the state. There are two data tables in this file that show housing units by vacancy status (type of vacancy). Table DC10_01031 shows the number of vacant housing units by the following categories--total, for rent, rented but not yet occupied, for sale only, sold but not yet occupied, seasonal or recreational or occasional use, for migrant workers, and vacant for some other reason. Table DC10_01032 shows percent distribution of housing units for each of these same categories. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

Graph and download economic data for Monthly Supply of New Houses in the United States (MSACSR) from Jan 1963 to Jun 2025 about supplies, new, housing, and USA.

description: The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in this particular RGIS Clearinghouse table is for McKinley County and all census blocks in the county. Table DC10_01116 shows counts of housing units by vacancy status (type of vacancy). The table includes the number of vacant housing units by the following categories; total, for rent, rented but not yet occupied, for sale only, sold but not yet occupied, seasonal or recreational or occasional use, for migrant workers, and vacant for some other reason. This file, along with file-specific descriptions (in Word and text formats) are available in a single zip file.; abstract: The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in this particular RGIS Clearinghouse table is for McKinley County and all census blocks in the county. Table DC10_01116 shows counts of housing units by vacancy status (type of vacancy). The table includes the number of vacant housing units by the following categories; total, for rent, rented but not yet occupied, for sale only, sold but not yet occupied, seasonal or recreational or occasional use, for migrant workers, and vacant for some other reason. This file, along with file-specific descriptions (in Word and text formats) are available in a single zip file.