11 datasets found
  1. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Jul 24, 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
    Jul 24, 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 Q2 2025 about sales, median, housing, and USA.

  2. T

    United Kingdom House Price Index

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 15, 2025
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    TRADING ECONOMICS (2025). United Kingdom House Price Index [Dataset]. https://tradingeconomics.com/united-kingdom/housing-index
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    Aug 15, 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, 1983 - Aug 31, 2025
    Area covered
    United Kingdom
    Description

    Housing Index in the United Kingdom increased to 516.20 points in August from 514.60 points in July of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. f

    Data from: Mitigating housing market shocks: an agent-based reinforcement...

    • tandf.figshare.com
    bin
    Updated Jul 10, 2024
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    Sedar Olmez; Alison Heppenstall; Jiaqi Ge; Corinna Elsenbroich; Dan Birks (2024). Mitigating housing market shocks: an agent-based reinforcement learning approach with implications for real-time decision support [Dataset]. http://doi.org/10.6084/m9.figshare.26232214.v1
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    binAvailable download formats
    Dataset updated
    Jul 10, 2024
    Dataset provided by
    Taylor & Francis
    Authors
    Sedar Olmez; Alison Heppenstall; Jiaqi Ge; Corinna Elsenbroich; Dan Birks
    License

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

    Description

    Research in modelling housing market dynamics using agent-based models (ABMs) has grown due to the rise of accessible individual-level data. This research involves forecasting house prices, analysing urban regeneration, and the impact of economic shocks. There is a trend towards using machine learning (ML) algorithms to enhance ABM decision-making frameworks. This study investigates exogenous shocks to the UK housing market and integrates reinforcement learning (RL) to adapt housing market dynamics in an ABM. Results show agents can learn real-time trends and make decisions to manage shocks, achieving goals like adjusting the median house price without pre-determined rules. This model is transferable to other housing markets with similar complexities. The RL agent adjusts mortgage interest rates based on market conditions. Importantly, our model shows how a central bank agent learned conservative behaviours in sensitive scenarios, aligning with a 2009 study, demonstrating emergent behavioural patterns.

  4. e

    Interviews: Sustainable housing growth - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Oct 22, 2023
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    (2023). Interviews: Sustainable housing growth - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/7ca3d878-7995-5b4d-a8ec-a1410c5ca9cb
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    Dataset updated
    Oct 22, 2023
    Description

    Local interviews: policy and other actors engaged in planning and delivery of sustainable housing. This project will examine the challenges and tensions associated with new housing growth in South Central England. It is concerned with the complex relationships between local communities, government agencies and the house building industry, at a time of market and public policy uncertainty. Using the Milton Keynes/Northamptonshire area as the laboratory, the project investigates the tensions and debates about new housing developments in three periods: before the slow-down in the housing market, during the property crash period, and in the current period of slow growth, public expenditure reductions and radical changes in Government planning and housing policy. Using reports and documents (such as local newspapers and planning reports) and interviews with local authorities, developers and community leaders, it will explore how attitudes to new housing among local policymakers have changed, why some areas find it acceptable and some do not. The research will also examine changes in support for sustainable development. Sustainability was a much-publicized objective of the previous government, with the promise to create "sustainable communities" through better urban design (including low carbon buildings), community-based planning and improved public transport, and remains a core element of contemporary planning policy.

  5. d

    Replication Data for: How Global is the Affordable Housing Crisis?...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
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    Coupe, Tom (2023). Replication Data for: How Global is the Affordable Housing Crisis? International Journal of Housing Markets and Analysis [Dataset]. http://doi.org/10.7910/DVN/NVGSV7
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    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Coupe, Tom
    Description

    these are the Replication files for: How Global is the Affordable Housing Crisis? accepted by the International Journal of Housing Markets and Analysis

  6. Average resale house prices Canada 2011-2024, with a forecast until 2026, by...

    • statista.com
    Updated Jun 20, 2025
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    Statista (2025). Average resale house prices Canada 2011-2024, with a forecast until 2026, by province [Dataset]. https://www.statista.com/statistics/587661/average-house-prices-canada-by-province/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Canada
    Description

    The average resale house price in Canada was forecast to reach nearly ******* Canadian dollars in 2026, according to a January forecast. In 2024, house prices increased after falling for the first time since 2019. One of the reasons for the price correction was the notable drop in transaction activity. Housing transactions picked up in 2024 and are expected to continue to grow until 2026. British Columbia, which is the most expensive province for housing, is projected to see the average house price reach *** million Canadian dollars in 2026. Affordability in Vancouver Vancouver is the most populous city in British Columbia and is also infamously expensive for housing. In 2023, the city topped the ranking for least affordable housing market in Canada, with the average homeownership cost outweighing the average household income. There are a multitude of reasons for this, but most residents believe that foreigners investing in the market cause the high housing prices. Victoria housing market The capital of British Columbia is Victoria, where housing prices are also very high. The price of a single family home in Victoria's most expensive suburb, Oak Bay was *** million Canadian dollars in 2024.

  7. w

    Dataset of publication dates of book subjects that contain Subprime nation :...

    • workwithdata.com
    Updated Nov 7, 2024
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    Work With Data (2024). Dataset of publication dates of book subjects that contain Subprime nation : American power, global capital, and the housing bubble [Dataset]. https://www.workwithdata.com/datasets/book-subjects?col=book_subject%2Cj0-publication_date&f=1&fcol0=j0-book&fop0=%3D&fval0=Subprime+nation+%3A+American+power%2C+global+capital%2C+and+the+housing+bubble&j=1&j0=books
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about book subjects. It has 10 rows and is filtered where the books is Subprime nation : American power, global capital, and the housing bubble. It features 2 columns including publication dates.

  8. e

    The uneven impact of the economic crisis on cities and households: Bristol...

    • b2find.eudat.eu
    Updated Oct 28, 2023
    + more versions
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    (2023). The uneven impact of the economic crisis on cities and households: Bristol and Liverpool compared - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/3f9e43a2-3b6f-59fc-8004-511fc4650c2b
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    Dataset updated
    Oct 28, 2023
    Description

    This project will explore the impact of the economic recession on cities and households through a systematic comparison of the experiences of two English cities, Bristol and Liverpool.The research will use both quantitative and qualitative approaches. Interviews will be held in both cities with stakeholders from across the public, private and voluntary and community sectors. A social survey of 1000 households will also be conducted in the two cities covering 10 specific household types. A series of in-depth qualitative interviews will then be held with households drawn from the survey and chosen to illustrate the spectrum of experience.In the context of globalisation and the rescaling of cities and states, the research aims to develop our understanding of the relationship between economic crisis, global connectivity and the transnational processes shaping cities and the everyday lives of residents. It will explore the 'capillary-like' impact of the crisis and austerity measures on local economic development, and local labour and housing markets, as well as highlight the intersecting realities of everyday life for households across the life course.The research will document the responses and coping strategies developed across different household types and evaluate the impact and effectiveness of 'anti-recession' strategies and policies. The research draws on a mixed methods approach, using sequentially staged methods in a ‘nested relationship’across the three stages of data collection and analysis. Stage 1: Literature search; Review of existing data on recent social, economic and labour market trends for Bristol and Liverpool; 21 qualitative interviews and one focus group with relevant local government departments, partnerships, business organisations, trade unions, and voluntary and community sector organisations. Interviews were taped, transcribed and analysed around an agreed framework. Stage 2: The Stage 2 household sample was drawn geographically - in Bristol within the local authorities of Bristol, North Somerset and South Gloucestershire and in Liverpool from Liverpool, Sefton and Knowsley. Geodemographic segmentation was used to identify and target a range of households that were comparable across locations, via the ACORN index. Ten of the seventeen ACORN household types were selected and the sample was drawn by pre-selecting addresses in the specified areas. The survey captured a broad picture of the impact of the downturn from the households’ perspectives. Stage 1 work informed the design. Between September and December 2011, Ipsos MORI piloted and conducted 1013, 20 minute, face-to-face interviews using CAPI and a structured interview schedule, supported by a range of showcards. They provided results, unweighted, in pre-coded format, with cross-breaks. Further analysis was undertaken by the research team using SPSS and GIS mapping. The four open ended questions were coded thematically. Responses were then analysed by city, gender and ACORN type. 722 households agreed to be re-contacted for Stage 3: 371 in Bristol; and 351 in Liverpool. Stage 3: Qalitative interviews provided in-depth data on the impact of the downturn and how households adapted and coped, highlighting the macro ‘through the lens of the micro’. The headline survey findings informed the sampling and design, with cases selected purposively to demonstrate a spectrum of experiences and coping strategies. The aim was to identify ‘information-rich’ cases that are relevant to the specific purposes of the research. The original timetable was for these interviews to commence in June 2012, but we delayed this to avoid the summer period, with the 2012 Olympic and Paralympic Games. A total of 58 interviews of up to 1.5 hours were conducted mostly in participants’ homes between September and December 2012. Each participant was given information about the interview prior to giving their consent, which was recorded on a signed form. Participants were offered a £15 voucher at the end of the interview. Interviews were recorded and transcribed.

  9. T

    Canada Average House Prices

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +7more
    csv, excel, json, xml
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    TRADING ECONOMICS, Canada Average House Prices [Dataset]. https://tradingeconomics.com/canada/average-house-prices
    Explore at:
    json, csv, xml, excelAvailable download formats
    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, 2005 - Aug 31, 2025
    Area covered
    Canada
    Description

    Average House Prices in Canada decreased to 687300 CAD in August from 688100 CAD in July of 2025. This dataset includes a chart with historical data for Canada Average House Prices.

  10. f

    Robustness test (Random effect).

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jan 11, 2024
    + more versions
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Robustness test (Random effect). [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t018
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    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

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

    Description

    Moderate rising of house prices are beneficial to the economic development. However, over high house prices worsen the economic distortions and thus hinder the development of the real economy. We use the stochastic frontier models to calculate the fundamental value in the housing in Chinese large and medium cities, and then obtain indexes which could measure the house prices’ deviations from the fundamental value. With the macroeconomic data in the city-level, this paper empirically investigates the effects of the house prices’ deviations on macro-economic variables like consumption, investment and output. The study reveals that the housing bubble exists in most Chinese cities, and first-tier cities fare the worst. House prices over the fundamental value, which could increase the scale of real estate investment, bring adverse impacts on GDP, as it causes declining civilian consumption and discourages real economy’s investment and production. The encouragement and the discouragement on macroeconomy caused by house prices’ deviation from its basic value take turns to play a key role in the process of China’ eco-nomic growth. In the early stage of China’s economic growth, the encouragement effect predominates. As urbanization and industrialization gradually upgrade to a higher level, the discouragement effect takes charge.

  11. D

    Eviction Data Bubble

    • data.sfgov.org
    csv, xlsx, xml
    Updated Sep 16, 2025
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    (2025). Eviction Data Bubble [Dataset]. https://data.sfgov.org/Housing-and-Buildings/Eviction-Data-Bubble/dwmg-gwb6
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    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Sep 16, 2025
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Data includes eviction notices filed with the San Francisco Rent Board per San Francisco Administrative Code 37.9(c). A notice of eviction does not necessarily indicate that the tenant was eventually evicted, so the notices below may differ from actual evictions. Notices are published since January 1, 1997. Please note that there are blank values for neighborhoods that could not be automatically assigned. These counts are automatically derived and there could be errors, please check the source to verify accuracy. The neighborhood boundaries used in this dataset correspond to these: https://data.sfgov.org/d/p5b7-5n3h

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    Learn how you can add new datasets to our index.

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(2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS

Median Sales Price of Houses Sold for the United States

MSPUS

Explore at:
59 scholarly articles cite this dataset (View in Google Scholar)
jsonAvailable download formats
Dataset updated
Jul 24, 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 Q2 2025 about sales, median, housing, and USA.

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