Nahb Housing Market Index in the United States increased to 38 points in November from 37 points in October of 2025. This dataset provides the latest reported value for - United States Nahb Housing Market Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Negative Equity in U.S. Housing Market

Measuring Home Values, Debt, and Credit Risk

By Zillow Data [source]

About this dataset

This dataset, Negative Equity in the US Housing Market, provides an in-depth look into the negative equity occurring across the United States during this single quarter. Included are metrics such as total amount of negative equity in millions of dollars, total number of homes in negative equity, percentage of homes with mortgages that are in negative equity and more. These data points provide helpful insights into both regional and national trends regarding the prevalence and rate of home mortgage delinquency stemming from a diminishment of value from peak levels.

Home types available for analysis include 'all homes', condos/co-ops, multifamily units containing five or more housing units as well as duplexes/triplexes. Additionally, Cash buyers rates for particular areas can also be determined by referencing this collection. Further metrics such as mortgage affordability rates and impacts on overall indebtedness are readily calculated using information related to Zillow's Home Value Index (ZHVI) forecast methodology and TransUnion data respectively.

Other variables featured within this dataset include characteristics like region type (i.e city, county ..etc), size rank based on population values , percentage change in ZHVI since peak levels as well as loan-to-value ratio greater than 200 across all regions constituted herein (NE). Moreover Zillow's own Secondary Mortgage Market Survey data is utilized to acquire average mortgage quote rates while correlative Census Bureau NCHS median household income figures represent typical assessable proportions between wages and debt obligations . So whether you're looking to assess effects along metro lines or detailed buffering through zip codes , this database should prove sufficient for insightful explorations! Nonetheless users must strictly adhere to all conditions encompassed within Terms Of Use commitments put forth by our lead provider before accessing any resources included herewith

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Research Ideas

• Analyzing regional and state trends in negative equity: Analyze geographic differences in the percentage of mortgages “underwater”, total amount of negative equity, number of homes at least 90 days late, and other key indicators to provide insight into the factors influencing negative equity across regions, states and cities.
• Tracking the recovery rate over time: Track short-term changes in numbers related to negative equity (e.g., region or area ZHVI Change from Peak) to monitor recovery rates over time as well as how different policy interventions are affecting homeownership levels in affected areas.
• Exploring best practices for promoting housing affordability: Compare affordability metrics (e.g., mortgage payments, price-to-income ratios) across different geographic locations over time to identify best practices for empowering homeowners and promoting stability within the housing market while reducing local inequality impacts related to availability of affordable housing options and access to credit markets like mortgages/loans etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: NESummary_2017Q1_Public.csv | Column name | Description | |:------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | RegionType | The type of region (e.g., city, county, metro etc.) (String) | | City | Name of the city (String) | | County | Name of the county (String) | | State | Name of the state (String) | | Metro ...

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

Housing Starts in the United States decreased to 1307 Thousand units in August from 1429 Thousand units in July 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.

Total Housing Inventory in the United States decreased to 1520 Thousands in October from 1530 Thousands in September of 2025. This dataset includes a chart with historical data for the United States Total Housing Inventory.

Graph and download economic data for Housing Inventory Estimate: Total Housing Units in the United States (ETOTALUSQ176N) from Q2 2000 to Q2 2025 about inventories, housing, and USA.

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Description:

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?

Acknowledgement:

Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the sales w.r.t a single & multiple feature.
• Also evaluate the models & compare thier respective scores like R2, RMSE, etc.

This statistic shows the average time needed for housing short sales in the United States between ************* and *************. In **********, the average time needed to short sell a housing unit was **** weeks.

Existing Home Sales in the United States increased to 4100 Thousand in October from 4050 Thousand in September of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Existing Home Sales (EXHOSLUSM495S) from Oct 2024 to Oct 2025 about headline figure, sales, housing, and USA.

Brief

The dataset contains key factors that could influence Residential home prices in the last 20 years in the United States. This factor falls into two categories i.e. Supply & Demand

The S&P Case-Shiller Housing Price Index(HPI) is taken as the y variable, or dependent variable, as an indicator of change in prices.

Supply_dataset(Monthly_data)

• Building Permits(Permit Number)-Number of building permits allotted
• Construction Spending (Million $)-The amount spent (in millions of USD) is a measure of the activity in the construction industry.
• Housing Starts(New Housing Project)-This is a measure of the number of units of new housing projects started in a given period.
• Homes Sold(units)-House for sale is a basic measure of supply.

Demand_dataset(Quaterly_data)

• Mortgage Rates(%)
• USA GDP(Billions$ )-Quarterly Real GDP (adjusted for inflation)
• Unemployment(%)
• Delinquency Rate(%) on Mortgages(Foreclosure on the mortgage)-an indicator of the number of foreclosures in real estate.

Inspiration

Building a Data Science model to find the factors which influenced the home prices the most in the last 20 years.

Summary

https://docs.google.com/presentation/d/1SFQg-cwu2JRr-85uvU1jYY4KDtTjqKuG/edit#slide=id.p3

The manufactured housing market is experiencing robust growth, driven by increasing demand for affordable and sustainable housing solutions. The market size in 2025 is estimated at $50 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 6% from 2025 to 2033. This growth is fueled by several factors, including rising housing costs in many regions, shorter construction times compared to traditional housing, and growing government initiatives promoting sustainable and efficient building practices. The increasing adoption of modular construction techniques and advancements in building materials further contribute to market expansion. The residential segment currently dominates the market, but the commercial sector is witnessing significant growth, driven by the need for flexible and quickly deployable spaces for offices, retail, and temporary facilities. Different floor sizes cater to varied needs, with the 1000-1500 sq ft segment showing particularly strong growth due to its suitability for families and small businesses. Key regional markets include North America, Europe, and Asia Pacific, reflecting strong housing demand and supportive government policies. Growth is however not without its restraints. Fluctuations in raw material prices, stringent building codes and regulations in certain regions, and potential labor shortages in the construction industry may impede market expansion. However, innovations in design, technology, and sustainable materials, coupled with increasing consumer awareness of the benefits of manufactured housing, are expected to mitigate these challenges. The competitive landscape features a mix of established players and emerging companies, indicating a dynamic and evolving market. The continued focus on innovation and addressing the aforementioned challenges will be crucial in shaping the future trajectory of this rapidly expanding sector.

Housing Index in the United States decreased to 435.40 points in September from 435.60 points in August of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The global housing rental service market is experiencing robust growth, driven by factors such as increasing urbanization, changing lifestyle preferences, and the rise of the gig economy. The market, valued at approximately $2 trillion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This significant expansion is fueled by several key trends, including the growing popularity of short-term rentals facilitated by platforms like Airbnb and VRBO, the increasing demand for flexible lease options catering to transient populations, and the emergence of innovative property management technologies enhancing efficiency and tenant experience. The market segmentation reveals a significant share held by the long-term lease segment, driven by stable rental income and predictable cash flows, while the short-term rental segment is witnessing rapid growth, propelled by the tourism and business travel sectors. Furthermore, the commercial segment is expanding, reflecting the growing need for flexible workspace solutions. Geographic distribution shows strong performance in North America and Europe, with emerging markets in Asia-Pacific presenting significant growth opportunities. However, the market faces certain restraints, including fluctuating interest rates impacting mortgage costs, potential regulatory changes affecting short-term rentals, and the challenges of maintaining consistent property standards across diverse portfolios. Despite these challenges, the long-term outlook for the housing rental service market remains positive, driven by continuous technological advancements, evolving consumer preferences, and the persistent demand for housing in rapidly urbanizing regions. Key players in the market, including Invitation Homes, Blueground, and Vacasa, are actively innovating to meet these changing demands and capitalize on growth opportunities within different segments and geographic regions. Strategic acquisitions, technological integrations, and expansion into new markets are crucial strategies for sustained success within this dynamic sector.

Despite a short period of decrease after the burst of the U.S. housing bubble and the global financial crisis, the total amount of mortgage debt in the United States has been on the rise in recent years. In 2024, the mortgage debt amounted to 20.83 trillion U.S. dollars, up from 13.5 trillion U.S. dollars a decade ago. Which factors impact the amount of mortgage debt? One of the most important factors responsible for the growth of mortgage debt is the number of home sales: The more home transactions, the more mortgages are sold, adding to the volume of debt outstanding. Additionally, as house prices increase, so does the gross lending and debt outstanding. On the other hand, high numbers of housing unit foreclosures and mortgage debt restructuring and short-sales can reduce mortgage debt. Which property type has the largest share of the mortgage market? The total mortgage debt includes different property types, such as one-to-four family residential, multifamily residential, commercial, and farm, but the overwhelming share of debt can be attributed to mortgage debt one-to-four family residences.

Real Estate Breakeven Analysis for U.S. Home Types

Buy vs Rent Comparison Across Markets

By Zillow Data [source]

About this dataset

This dataset provides a comprehensive analysis of the current real estate situation in the United States. It includes breakeven analysis charts that compare buying vs renting across major U.S. markets. This dataset contains various metrics such as home types, housing stock, price-to-income ratio, cash buyers, mortgage affordability and rental affordability to name a few. This data has been compiled using Zillow's own data along with TransUnion financing survey data and the Freddie Mac Primary Mortgage Market Survey to provide an accurate understanding of each metro area’s market health and purchasing power for buyers and renters alike. By downloading this information you can compare different regions based on size rank and other factors to get full insights regarding their potential fit for your needs or investments strategies as well as any potential risks associated with each region's housing market health

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How to use the dataset

This dataset is for real estate professionals, owner-occupants, potential buyers and renters who are interested in understanding which U.S. markets offer the most favorable home buying or rental opportunities from a financial perspective over the long term.

The “Real Estate Breakeven Analysis for U.S Home Types” dataset contains data pulled from Zillow's current and forecasted housing market metrics across many different real estate regions in the United States including cities, counties, states, metro areas and combined statistical areas (CSAs). The data includes several measures of affordability such as median price-to-rent ratio (MedPR), median breakeven horizon (MedBE) - which refers to how long it takes to make up purchase costs when compared with renting; cash purchaser share; mortgage rate; mortgage affordability indices; rental affordability rates etc.

In order to analyze and compare buying vs renting decisions across various regions in the US this dataset provides breakeven analysis at various levels of geographies i.e., state names, region types (city/metro area/county) and show how long it will take homeowners to break even on their purchase costs when compared with renting in that region over a longer period of time using discounted cash flow methodology. This information helps people understand what type of transaction is a better fit for them by weighing short term vs long term goals accordingly by evaluating these different factors related to housing metrics carefully before making financial decisions about purchasing or renting properties in desired location(s).

To use this dataset one can use either basic filters like RegionType or RegionName or more detailed filter criteria like CountyName, City name , Metro area name , State Name etc . For example if someone wanted to look at properties available for rent only then they can apply filters based on Province Type =‘Rental’ Also one can further refine searches based on filtering them with defined SampleRate , Median Price – To – Rent Ratio …..etc . This could be useful if seekers would want only specific type of property like Condominium/Coop /Multifamily 5+ Units /Duplex Triplex listing etc …and then apply other parameters like Cash Buyers percent , Mortgage Affordability Rate….etc ..in order narrow down search results while looking at Breakeven scores /horizons in their target locations . One should take advantages of all relevant parameters while searching through data before making any decision related with owning rental properties so that they can make sure best possible investment decision given

Research Ideas

• Visualizing changes in real estate trends across regions by comparing price to rent ratios, mortgage affordability indices and cash buyers over time.
• Market segmentation analysis based on region-level market characteristics such as negative equity data, rental affordability, median house values and population size.
• Predicting housing demand within a particular region based on its breakeven horizon or price to rent ratio

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: BreakEven_2017-03.csv | Column name | Description | |:----------------|:----------------------------------------------------...

Explore Dallas, TX rental market 2025. The average long-term prices $1,734 and short-term $2,272, with trends shaping housing in a city of 1,299,553 residents.

Discover the booming global housing rental service market! This comprehensive analysis reveals key trends, growth drivers, and challenges impacting short-term and long-term rentals, along with insights into leading companies and regional variations. Explore market projections to 2033 and uncover lucrative investment opportunities.