Out of a total of 7.8 million housing units in New York City in 2021, approximately 1.5 million units were between 1,000 and 1,499 square feet. The share of owner occupied homes in this category was slightly higher than the share of rented homes. It can be seen, however, that renter occupied homes are generally smaller.

Telluride, CO, was the most expensive market for luxury single-family home market in the United States in 2024. In February that year, the median sales price of a single-family home in Telluride was 6.3 million U.S. dollars. Park City, UT, Paradise Valley, AZ, and the Los Angeles Beach Cities, CA, were other locations that fetched prices over 4.3 million U.S. dollars.

Graph and download economic data for Housing Inventory: Total Listing Count in Salt Lake County, UT (TOTLISCOU49035) from Jul 2016 to Feb 2025 about Salt Lake County, UT; Salt Lake City; UT; listing; and USA.

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

Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Feb 2025 about median and USA.

Paper Abstract: The US urban population increased by almost 50 percent between 1980 and 2020, with this growth heavily concentrated in the Sun Belt and at the fringes of metropolitan areas. This paper considers the role of housing supply in shaping the growth of cities and neighborhoods. Housing supply constraints have meant that demand growth has increasingly manifested as price growth rather than as increases in housing units or population in larger and denser metropolitan areas and neighborhoods. New housing is provided at increasingly higher cost in areas that have higher intensity of existing development and more restrictive regulatory environments. Both forces have strengthened over time, making quantity supplied less responsive to growing demand, driving housing price growth in many areas, and pushing housing quantity growth further out into urban fringes. As a result of such pressures on the cost of new construction, the US has recently experienced more rapid price growth and a declining influence of new construction on the housing stock.

The number of housing units added to the housing stock in New York-Newark-Jersey City in 2022 and 2023 was 51,050 short of the number of new households formed that year. Meanwhile, the number of net additions to the housing stock in the metro area of Los Angeles fell short of the number of households both years. Meanwhile, the metropolitan areas of Dallas, Atlanta, Phoenix, and San Francisco among others had enough housing units added to its stock to meet the new demand.

Graph and download economic data for Housing Inventory: New Listing Count Month-Over-Month in Baltimore City, MD (NEWLISCOUMM24510) from Jul 2017 to Feb 2025 about Baltimore City, MD; Baltimore; MD; new; listing; and USA.

Out of a total of 7.8 million housing units in New York City, approximately 3.6 million units were single family detached homes and 350 unites were single family attached homes in 2021. Unlike single family homes which were mostly owner occupied, housing in multifamily buildings was predominantly renter occupied. In buildings with 50 or more housing units, one million out of 1.3 million units were rented.

Our goal in this paper is to examine whether there are similar patterns in the distribution of tree canopy by Home Owners’ Loan Corporation (HOLC) graded neighborhoods across 37 cities. A pre-print of the paper can be found here: https://osf.io/preprints/socarxiv/97zcs This data packages contains: 1. City-specific file geodatabases with features classes of the HOLC polygons obtained from the Mapping Inequality Project https://dsl.richmond.edu/panorama/redlining/ , and tables summarizing tree canopy, and in some cases other land cover classes. 2. An *.R script that replicates all of the analyses, graphs, and tables in the paper. Other double checks, exploratory, and miscellaneous outputs are created by the script too as a bonus. Everything in the paper can be done with the script; additional work outputs are also created. 3. A *.csv file containing city, the HOLC grade, and the percent tree canopy cover. This can be used to create the main findings of the paper and this flat file is provided as an alternative to running the R script to extract information from the geodatabases, combine, and analyze them. The intention is that this file is more widely accessible; the underlying information is the same. Redlining was a racially discriminatory housing policy established by the federal government’s Home Owners’ Loan Corporation (HOLC) during the 1930s. For decades, redlining limited access to homeownership and wealth creation among racial minorities, contributing to a host of adverse social outcomes, including high unemployment, poverty, and residential vacancy, that persist today. While the multigenerational socioeconomic impacts of redlining are increasingly understood, the impacts on urban environments and ecosystems remains unclear. To begin to address this gap, we investigated how the HOLC policy administered 80 years ago may relate to present-day tree canopy at the neighborhood level. Urban trees provide many ecosystem services, mitigate the urban heat island effect, and may improve quality of life in cities. In our prior research in Baltimore, MD, we discovered that redlining policy influenced the location and allocation of trees and parks. Our analysis of 37 metropolitan areas here shows that areas formerly graded D, which were mostly inhabited by racial and ethnic minorities, have on average ~23% tree canopy cover today. Areas formerly graded A, characterized by U.S.-born white populations living in newer housing stock, had nearly twice as much tree canopy (~43%). Results are consistent across small and large metropolitan regions. The ranking system used by Home Owners’ Loan Corporation to assess loan risk in the 1930s parallels the rank order of average percent tree canopy cover today.

Graph and download economic data for Housing Inventory: Active Listing Count in the United States (ACTLISCOUUS) from Jul 2016 to Feb 2025 about active listing, listing, and USA.

Analysis of ‘Housing stock by type of energy source, statistical zone and construction period since 2017’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/61078b36-b895-4d00-bac6-10549bb7d655-stadt-zurich on 15 January 2022.

--- Dataset description provided by original source is as follows ---

These data include the housing stock of the city of Zurich by type of energy source. The data are available on an annual basis from 2017.

For the correct understanding of the data, please refer to the further explanations given below in the section “Remarks”.

--- Original source retains full ownership of the source dataset ---

Graph and download economic data for Housing Inventory: New Listing Count in New York-Newark-Jersey City, NY-NJ-PA (CBSA) (NEWLISCOU35620) from Jul 2016 to Feb 2025 about NJ, New York, PA, NY, new, listing, and USA.

CityPropStat provides aggregated property statistics for 795 cities and towns (i.e., Metropolitan and Micropolitan statistical areas) in the conterminous United States. These statistics include sum, mean, median, Gini index and entropy of residential floor space, cadastral parcel size, floor-area ratio, and property value, approximately for the reference year 2020, aggregated by building construction year in decadal steps (cumulative and incremental) from 1910 to 2020.Cumulative statistics: CBSA_Property_Statistics_1910-2020_cumulative.csvDecadal time slices statistics: CBSA_Property_Statistics_1910-2020_decadal_slices.csvData source: Zillow Transaction and Assessment Dataset (ZTRAX), provided to University of Colorado Boulder via a data share agreement (2016-2023).CityPropStats is a supplementary dataset to:Ortman S.G., et al. (accepted): "Changes in Agglomeration and Productivity are Poor Predictors of Inequality Across the Archaeological Record". Proceedings of the National Academy of Sciences (2025).Column description:cbsa_idCBSA GEOIDcbsa_nameFull namecbsa_typeCBSA type (metro vs micropolitan statistical area)year_fromEarliest year for selection interval of properties based on their construction yearyear_toLatest year for selection interval of properties based on their construction yearcbsa_popCBSA population or population change (US Census)tot_res_propsTotal residential propertiestot_res_area_sqkmTotal indoor area of residential properties in sqkmavg_res_area_sqmAverage indoor area of residential properties in sqmmedian_res_area_sqmMedian indoor area of residential properties in sqmq25_res_area_sqm25th percentile of indoor area of residential properties in sqmq75_res_area_sqm75th percentile of indoor area of residential properties in sqmgini_res_areaGini index of residential property indoor areatot_prop_value_usdTotal residential property value in USDmedian_prop_value_usdMedian residential property value in USDq25_prop_value_usd25th percentile of residential property values in USDq75_prop_value_usd75th percentile of residential property values in USDgini_prop_valueGini index of residential property valuestot_lot_area_sqkmTotal lot (cadastral parcel) area in sqkmavg_lot_area_sqmMean lot area in sqmmedian_lot_area_sqmMedian lot area in sqmq25_lot_area_sqm25th percentile of lot area in sqmq75_lot_area_sqm75th percentile of lot area in sqmgini_lot_areaGini index of lot areaavg_farMean floor-area-ratio (FAR), with FAR being the ratio of building indoor area and lot area, based on residential propertiesmedian_farMedian floor-area-ratio (FAR), with FAR being the ratio of building indoor area and lot area, based on residential propertiesq25_far25th percentile of floor-area-ratio (FAR), with FAR being the ratio of building indoor area and lot area, based on residential propertiesq75_far75th percentile of floor-area-ratio (FAR), with FAR being the ratio of building indoor area and lot area, based on residential propertiesentropy_res_areaShannon entropy of the indoor area of residential properties, based on propertiesentropy_prop_valueShannon entropy of the property value of residential properties, based on propertiesentropy_lot_areaShannon entropy of the lot size of residential properties, based on propertiesarea_completenessRatio of properties with a valid indoor area attribute [0,1]value_completenessRatio of properties with a valid property value attribute [0,1]lotsize_completenessRatio of properties with a valid indoor area, property value, and lot size attribute [0,1]area_value_completenessRatio of properties with a valid lot size attribute [0,1]area_value_lotsize_completenessRatio of properties with both a valid indoor area and property value attribute [0,1]

Graph and download economic data for Housing Inventory: Active Listing Count in Florida (ACTLISCOUFL) from Jul 2016 to Feb 2025 about active listing, FL, listing, and USA.

The number of vacant homes for rent in the United States increased for the third year in a row in 2024, after reaching a record low in 2021. In the third quarter of 2024, there were approximately 6.9 million unoccupied housing units for rent.

Graph and download economic data for Housing Inventory: Active Listing Count in Minneapolis-ST. Paul-Bloomington, MN-WI (CBSA) (ACTLISCOU33460) from Jul 2016 to Feb 2025 about Minneapolis, MN, active listing, WI, listing, and USA.

Graph and download economic data for Housing Inventory: Active Listing Count in California (ACTLISCOUCA) from Jul 2016 to Feb 2025 about active listing, CA, listing, and USA.

Graph and download economic data for Housing Inventory: Active Listing Count in Bay County, FL (ACTLISCOU12005) from Jul 2016 to Feb 2025 about Bay County, FL; Panama City; active listing; FL; listing; and USA.

The year-end value of the S&P Case Shiller National Home Price Index amounted to 310.76 in December 2023. The index value was equal to 100 as of January 2000, so if the index value is equal to 130 in a given year, for example, it means that the house prices increased by 30 percent since 2000. S&P/Case Shiller U.S. home indices – additional informationThe S&P Case Shiller National Home Price Index is calculated on a monthly basis and is based on the prices of single-family homes in nine U.S. Census divisions: New England, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain and Pacific. The index is the leading indicator of the American housing market and one of the indicators of the state of the broader economy. The index illustrates the trend of home prices and can be helpful during house purchase decisions. When house prices are rising, a house buyer might want to speed up the house purchase decision as the transaction costs can be much higher in the future. The S&P Case Shiller National Home Price Index has been on the rise since 2011.The S&P Case Shiller National Home Price Index is one of the indices included in the S&P/Case-Shiller Home Price Index Series. Other indices are the S&P/Case Shiller 20-City Composite Home Price Index, the S&P/Case Shiller 10-City Composite Home Price Index and twenty city composite indices.