100+ datasets found
  1. T

    United States Housing Starts

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 18, 2025
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    TRADING ECONOMICS (2025). United States Housing Starts [Dataset]. https://tradingeconomics.com/united-states/housing-starts
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1959 - Jun 30, 2025
    Area covered
    United States
    Description

    Housing Starts in the United States increased to 1321 Thousand units in June from 1263 Thousand units in May of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  2. New monthly housing construction starts in the U.S. 1968-2025

    • statista.com
    Updated Jun 4, 2025
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    Statista (2025). New monthly housing construction starts in the U.S. 1968-2025 [Dataset]. https://www.statista.com/statistics/184487/us-new-privately-owned-housing-units-started-since-2000/
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    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 1968 - Apr 2025
    Area covered
    United States
    Description

    In April 2025, approximately ******* home construction projects started in the United States. The lowest point for housing starts over the past decade was in 2009, just after the 2007-2008 global financial crisis. Since 2010, the number of housing units started has been mostly increasing despite seasonal fluctuations. Statista also has a dedicated topic page on the U.S. housing market as a starting point for additional investigation on this topic. The impact of the global recession The same trend can be seen in home sales over the past two decades. The volume of U.S. home sales began to drop in 2005 and continued until 2010, after which home sales began to increase again. This dip in sales between 2005 and 2010 suggests that supply was outstripping demand, which led to decreased activity in the residential construction sector. Impact of recession on home buyers The financial crisis led to increased unemployment and pay cuts in most sectors, which meant that potential home buyers had less money to spend. The median income of home buyers in the U.S. fluctuated alongside the home sales and starts over the past decade.

  3. Single-family housing starts in Canada 2016-2023, by province

    • statista.com
    • ai-chatbox.pro
    Updated Jul 9, 2025
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    Statista (2025). Single-family housing starts in Canada 2016-2023, by province [Dataset]. https://www.statista.com/statistics/1006842/single-detached-housing-starts-canada/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Canada
    Description

    The number of single-family housing starts in Canada in 2023 decreased by ****** units in comparison to the previous year. Housing starts also fell in 2022 from a peak of over ****** housing units in 2021. New home construction in Canada overall followed a similar trend during that period.

  4. Canada Mortgage and Housing Corporation, housing starts, under construction...

    • www150.statcan.gc.ca
    • beta.data.urbandatacentre.ca
    • +3more
    Updated Apr 28, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Canada Mortgage and Housing Corporation, housing starts, under construction and completions, all areas, quarterly [Dataset]. http://doi.org/10.25318/3410013501-eng
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    Dataset updated
    Apr 28, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Newfoundland and Labrador; Prince Edward Island; Atlantic provinces ...), Housing estimates (3 items: Housing starts; Housing under construction; Housing completions ...), Type of unit (6 items: Total units; Multiples; Single-detached; Semi-detached ...), Seasonal adjustment (2 items: Unadjusted; Seasonally adjusted at annual rates ...).

  5. T

    Canada Housing Starts

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 17, 2025
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    TRADING ECONOMICS (2025). Canada Housing Starts [Dataset]. https://tradingeconomics.com/canada/housing-starts
    Explore at:
    xml, csv, json, excelAvailable download formats
    Dataset updated
    Jul 17, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1977 - Jun 30, 2025
    Area covered
    Canada
    Description

    Housing Starts in Canada increased to 283.73 Thousand units in June from 282.71 Thousand units in May of 2025. This dataset provides the latest reported value for - Canada Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  6. New residential construction in Canada 1948-2024

    • statista.com
    • ai-chatbox.pro
    Updated May 28, 2025
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    Statista (2025). New residential construction in Canada 1948-2024 [Dataset]. https://www.statista.com/statistics/198040/total-number-of-canadian-housing-starts-since-1995/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Canada
    Description

    In 2024, there were more new home construction starts in Canada than in the previous year. Construction starts peaked in 2021, when there were ******* housing units whose construction started that year. Despite the restrictions imposed in Canada during the COVID-19 pandemic, the industry managed to continue operating, with increases in the number of housing starts in 2020 and 2021. How many homes are under development? In 2023, the number of housing units that were under construction in Canada was approximately ******** units. After a period of stagnation until 2016, the housing industry witnessed a significant surge in construction activity. Numerous factors are attributed to this rise, including the heightened demand for housing, an expanding economy that encouraged investment, and the response to the shortage of housing. How expensive are homes in Canada? In 2024, the average cost of a house in Canada was around ******* Canadian dollars. The average house price had increased that year by ****** Canadian dollars compared in 2024 compared to the previous year. The house price-to-income ratio in Canada increased slightly in the third quarter of 2024.

  7. Housing Market Value Analysis - Urban Redevelopment Authority

    • data.wprdc.org
    • s.cnmilf.com
    • +3more
    html, pdf, zip
    Updated May 21, 2023
    + more versions
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    Urban Redevelopment Authority of Pittsburgh (2023). Housing Market Value Analysis - Urban Redevelopment Authority [Dataset]. https://data.wprdc.org/dataset/market-value-analysis-urban-redevelopment-authority
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    pdf, zip, htmlAvailable download formats
    Dataset updated
    May 21, 2023
    Dataset provided by
    Urban Redevelopment Authority of Pittsburghhttp://www.ura.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional neighborhood boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

    Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016:

    • Median Sales Price

    • Variance of Sales Price

    • Percent Households Owner Occupied

    • Density of Residential Housing Units

    • Percent Rental with Subsidy

    • Foreclosures as a Percent of Sales

    • Permits as a Percent of Housing Units

    • Percent of Housing Units Built Before 1940

    • Percent of Properties with Assessed Condition “Poor” or worse

    • Vacant Housing Units as a Percentage of Habitable Units

    The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

    During the research process, staff from the URA and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

  8. M

    U.S. Housing - Days on Market (2016-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). U.S. Housing - Days on Market (2016-2025) [Dataset]. https://www.macrotrends.net/3210/us-housing-days-on-market
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2016 - 2025
    Area covered
    United States
    Description

    The median number of days property listings spend on the market in a given geography during the specified month (calculated from list date to closing, pending, or off-market date depending on data availability).

    With the release of its September 2022 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology updates and improves the calculation of time on market and improves handling of duplicate listings. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since October 2022 will not be directly comparable with previous data releases (files downloaded before October 2022) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

    With the release of its November 2021 housing trends report, Realtor.com® incorporated a new and improved methodology for capturing and reporting housing inventory trends and metrics. The new methodology uses the latest and most accurate data mapping of listing statuses to yield a cleaner and more consistent measurement of active listings at both the national and local level. The methodology has also been adjusted to better account for missing data in some fields including square footage. Most areas across the country will see minor changes with a smaller handful of areas seeing larger updates. As a result of these changes, the data released since December 2021 will not be directly comparable with previous data releases (files downloaded before December 2021) and Realtor.com® economics blog posts. However, future data releases, including historical data, will consistently apply the new methodology. More details are available at the source's Real Estate Data Library (https://www.realtor.com/research/data/).

  9. C

    Housing Market Value Analysis - Allegheny County Economic Development

    • data.wprdc.org
    • catalog.data.gov
    csv, html, lyr, pdf +2
    Updated May 26, 2023
    + more versions
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    Allegheny County (2023). Housing Market Value Analysis - Allegheny County Economic Development [Dataset]. https://data.wprdc.org/dataset/market-value-analysis-allegheny-county-economic-development
    Explore at:
    lyr, zip, png, pdf(9358422), pdf(11534), html, csvAvailable download formats
    Dataset updated
    May 26, 2023
    Dataset provided by
    Allegheny County
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Allegheny County
    Description

    In 2017, the County Department of Economic Development, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for Allegheny County. A similar MVA was completed with the Pittsburgh Urban Redevelopment Authority in 2016. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

    The 2016 Allegheny County MVA does not include the City of Pittsburgh, which was characterized at the same time in the fourth update of the City of Pittsburgh’s MVA. All calculations herein therefore do not include the City of Pittsburgh. While the methodology between the City and County MVA's are very similar, the classification of communities will differ, and so the data between the two should not be used interchangeably.

    Allegheny County's MVA utilized data that helps to define the local real estate market. Most data used covers the 2013-2016 period, and data used in the analysis includes:

    •Residential Real Estate Sales; • Mortgage Foreclosures; • Residential Vacancy; • Parcel Year Built; • Parcel Condition; • Owner Occupancy; and • Subsidized Housing Units.

    The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

    During the research process, staff from the County and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

    Please refer to the report (included here as a pdf) for more information about the data, methodology, and findings.

  10. F

    Housing Inventory: Median Days on Market in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 10, 2025
    + more versions
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    (2025). Housing Inventory: Median Days on Market in the United States [Dataset]. https://fred.stlouisfed.org/series/MEDDAYONMARUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 10, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

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

  11. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
    + more versions
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    (2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 23, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

  12. Live tables on housing supply: indicators of new supply

    • gov.uk
    • s3.amazonaws.com
    Updated Jun 20, 2025
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    Ministry of Housing, Communities and Local Government (2025). Live tables on housing supply: indicators of new supply [Dataset]. https://www.gov.uk/government/statistical-data-sets/live-tables-on-house-building
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    Dataset updated
    Jun 20, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities and Local Government
    Description

    Local authorities compiling this data or other interested parties may wish to see notes and definitions for house building which includes P2 full guidance notes.

    Live tables

    Data from live tables 253 and 253a is also published as http://opendatacommunities.org/def/concept/folders/themes/house-building" class="govuk-link">Open Data (linked data format).

    https://assets.publishing.service.gov.uk/media/68541eb5a3a282804858153b/LiveTable213.ods">Table 213: permanent dwellings started and completed, by tenure, England (quarterly)

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">26.7 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

    https://assets.publishing.service.gov.uk/media/68541ee7a3a282804858153c/LiveTable217.ods">Table 217: permanent dwellings started and completed by tenure and region (quarterly)

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">113 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

  13. Housing units under construction in France 2016-2023

    • ai-chatbox.pro
    • statista.com
    Updated Jan 28, 2025
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    Statista (2025). Housing units under construction in France 2016-2023 [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F1108920%2Fnumber-housing-unit-projects-france%2F%23XgboD02vawLbpWJjSPEePEUG%2FVFd%2Bik%3D
    Explore at:
    Dataset updated
    Jan 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 2016 - Dec 2023
    Area covered
    France
    Description

    The number of housing construction starts in France varied since 2016, from approximately 13,000 in August 2020 to 56,000 in December 2018. As of May 2023, there were approximately 29,000 residential units started, which was slightly lower than the same period in 2022.

  14. Projected size of U.S. green single-family housing market 2005-2016

    • statista.com
    Updated Mar 31, 2012
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    Statista (2012). Projected size of U.S. green single-family housing market 2005-2016 [Dataset]. https://www.statista.com/statistics/248085/projected-size-of-the-us-green-single-family-housing-market/
    Explore at:
    Dataset updated
    Mar 31, 2012
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005 - 2012
    Area covered
    United States
    Description

    This statistic represents the projected size of the U.S. market for green single-family housing projects from 2005 through 2016. In 2008, this market was sized at approximately ** billion U.S. dollars.

  15. Housing Statistics 1 April 2016 to 31 March 2017

    • gov.uk
    Updated Jun 20, 2017
    + more versions
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    Homes and Communities Agency (2017). Housing Statistics 1 April 2016 to 31 March 2017 [Dataset]. https://www.gov.uk/government/statistics/housing-statistics-1-april-2016-to-31-march-2017
    Explore at:
    Dataset updated
    Jun 20, 2017
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Homes and Communities Agency
    Description

    The latest release on the supply of homes delivered by the Homes and Communities Agency (HCA) in England. It excludes London except for delivery of programmes managed by the HCA on behalf of the Greater London Authority.

    The Department for Communities and Local Government has combined the affordable housing statistics in this release with the Greater London Authority’s affordable housing statistics to produce affordable housing starts and completions for England.

  16. F

    Housing Inventory: Median Days on Market in Lake Charles, LA (CBSA)

    • fred.stlouisfed.org
    json
    Updated Jul 10, 2025
    + more versions
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    (2025). Housing Inventory: Median Days on Market in Lake Charles, LA (CBSA) [Dataset]. https://fred.stlouisfed.org/series/MEDDAYONMAR29340
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 10, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    Lake Charles, Louisiana
    Description

    Graph and download economic data for Housing Inventory: Median Days on Market in Lake Charles, LA (CBSA) (MEDDAYONMAR29340) from Jul 2016 to Jun 2025 about Lake Charles, LA, median, and USA.

  17. U.S. growth in residential and non-residential construction starts by region...

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). U.S. growth in residential and non-residential construction starts by region 2016 [Dataset]. https://www.statista.com/statistics/677707/residential-and-non-residential-construction-starts-growth-us-by-region/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2016
    Area covered
    United States
    Description

    This statistic represents the growth of residential and non-residential construction starts in the United States in 2016, with a breakdown by region. Residential construction starts in the Northeastern region declined by approximately **** percent from 2015 to 2016.

  18. Spain Housing Market Indicators: Mortgage Lending: Percent of GDP

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Spain Housing Market Indicators: Mortgage Lending: Percent of GDP [Dataset]. https://www.ceicdata.com/en/spain/housing-market-indicators/housing-market-indicators-mortgage-lending-percent-of-gdp
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2014 - Mar 1, 2017
    Area covered
    Spain
    Variables measured
    Sales
    Description

    Spain Housing Market Indicators: Mortgage Lending: Percent of GDP data was reported at 58.310 % in Mar 2017. This records a decrease from the previous number of 59.730 % for Dec 2016. Spain Housing Market Indicators: Mortgage Lending: Percent of GDP data is updated quarterly, averaging 52.430 % from Mar 1989 (Median) to Mar 2017, with 113 observations. The data reached an all-time high of 101.760 % in Dec 2009 and a record low of 14.820 % in Mar 1989. Spain Housing Market Indicators: Mortgage Lending: Percent of GDP data remains active status in CEIC and is reported by Bank of Spain. The data is categorized under Global Database’s Spain – Table ES.EB003: Housing Market Indicators.

  19. C

    Data from: Residential Vacancy Rate

    • data.ccrpc.org
    csv
    Updated Oct 17, 2024
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    Champaign County Regional Planning Commission (2024). Residential Vacancy Rate [Dataset]. https://data.ccrpc.org/ar/dataset/residential-vacancy-rate
    Explore at:
    csvAvailable download formats
    Dataset updated
    Oct 17, 2024
    Dataset authored and provided by
    Champaign County Regional Planning Commission
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    The residential vacancy rate is the percentage of residential units that are unoccupied, or vacant, in a given year. The U.S. Census Bureau defines occupied housing units as “owner-occupied” or “renter-occupied.” Vacant housing units are not classified by tenure in this way, as they are not occupied by an owner or renter.

    The residential vacancy rate serves as an indicator of the condition of the area’s housing market. Low residential vacancy rates indicate that demand for housing is high compared to the housing supply. However, the aggregate residential vacancy rate is lacking in granularity. For example, the housing market for rental units in the area and the market for buying a unit in the same area may be very different, and the aggregate rate will not show those distinct conditions. Furthermore, the vacancy rate may be high, or low, for a variety of reasons. A high vacancy rate may result from a falling population, but it may also result from a recent construction spree that added many units to the total stock.

    The residential vacancy rate in Champaign County appears to have fluctuated between 8% and 14% from 2005 through 2022, reaching a peak near 14% in 2019. In 2023, this rate dropped to about 7%, its lowest value since 2005. However, this rate was calculated using the American Community Survey’s (ACS) estimated number of vacant houses per year, which has year-to-year fluctuations that are largely not statistically significant. Thus, we cannot establish a trend for this data.

    The residential vacancy rate data shown here was calculated using the estimated total housing units and estimated vacant housing units from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

    As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

    Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

    For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Occupancy Status.

    Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (4 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25002, generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table SB25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25002; generated by CCRPC staff; using American FactFinder; (16 March 2016).

  20. a

    Housing Market Typology

    • austin.hub.arcgis.com
    Updated Oct 16, 2018
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    City of Austin (2018). Housing Market Typology [Dataset]. https://austin.hub.arcgis.com/datasets/f95951f76c2147ebbacd607448876872
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    Dataset updated
    Oct 16, 2018
    Dataset authored and provided by
    City of Austin
    Area covered
    Description

    Layer shows housing market typology by census tract based on the UT Uprooted report. Census tracts are divided into categories of most adjacent, accelerating, appreciated, missing home value data, and other/no change based on changes in neighborhoods' median home values between 1990 to 2016.

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TRADING ECONOMICS (2025). United States Housing Starts [Dataset]. https://tradingeconomics.com/united-states/housing-starts

United States Housing Starts

United States Housing Starts - Historical Dataset (1959-01-31/2025-06-30)

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7 scholarly articles cite this dataset (View in Google Scholar)
json, excel, csv, xmlAvailable download formats
Dataset updated
Jul 18, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 31, 1959 - Jun 30, 2025
Area covered
United States
Description

Housing Starts in the United States increased to 1321 Thousand units in June from 1263 Thousand units in May of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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