United States HAI: First Time: 1st Time Buyer Index data was reported at 94.400 NA in Sep 2018. This records an increase from the previous number of 94.100 NA for Jun 2018. United States HAI: First Time: 1st Time Buyer Index data is updated quarterly, averaging 83.900 NA from Mar 1981 (Median) to Sep 2018, with 151 observations. The data reached an all-time high of 136.700 NA in Mar 2012 and a record low of 47.700 NA in Sep 1981. United States HAI: First Time: 1st Time Buyer Index data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB019: Housing Affordability Index: First Time Buyers.

Approximately ** percent of Americans aged 26 to 34 who bought a home were first-home buyers, whereas ** percent of home buyers between 35 and 44 bought their first home in that year. Gen Z and Millennial first-time buyers It is no surprise that many Gen Z (18 to 24 years old) and Millennial (25 to 43 years old) home buyers are mostly first-time home buyers. These home buyers are in the early stages of their careers, or still studying in some cases, and often struggling to repay student debt, so they need to save for many years before they afford a down payment. When do they sell? These generations tend to stay in their first homes for several years, which means that the majority of home sellers are older than them. The share of income needed to afford a trade-up home is significantly lower than the money needed for a starter home. A trade-up home is a larger and more expensive home, which homeowners often buy after living in their starter home, or their first home, for several years. This progression generally happens when homeowners have climbed the career ladder and increased their incomes.

Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).

New Home Sales in the United States decreased to 623 Thousand units in May from 722 Thousand units in April of 2025. This dataset provides the latest reported value for - United States New Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Home Ownership Rate in the United States decreased to 65.10 percent in the first quarter of 2025 from 65.70 percent in the fourth quarter of 2024. This dataset provides the latest reported value for - United States Home Ownership Rate - 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 Homeownership Rate in the United States (RHORUSQ156N) from Q1 1965 to Q1 2025 about homeownership, housing, rate, and USA.

Since 1995, River City Housing (RCH) has developed and sold over 130 new construction and 91 acquisition/rehab single family homes to income-qualified, first-time homebuyers. We help to make purchasing one of our houses even more affordable by providing down payment assistance to our homebuyers to help cover their down payment, prepaids and closing costs. RCH actively entered the rehab market at the end of 2009 to meet the overwhelming availability of foreclosures in an effort to help stabilize a volatile housing market. Currently we have eight homes, both acquisition/rehabilitations and new construction, in process. We have proudly maintained a reputation for high quality workmanship and strongly support creating housing that is energy-efficient so it is safe and affordable at the time of purchase, and affordable long-term. It is our intention to help the owner avoid becoming cost burdened with costly maintenance and repairs, so we prioritize repairs and new installations on major mechanicals, roofs, electrical and plumbing systems, added insulation in attics and crawl spaces, and energy efficient doors, windows, and appliances.

River city Housing’s mission is to improve the quality of life for low and moderate-income families and strengthen neighborhoods by developing safe and affordable housing. We believe so strongly in homeownership because owners benefit by gaining equity through the property and value of their home, achieving housing stability for themselves and their families, and receiving all of the added benefits homeownership offers.

RCH is also fully committed to bridging the black wealth gap by increasing black home ownership, particularly for current and legacy residents in neighborhoods where redlining and other discriminatory policies were enacted to restrict homeownership. We are one of several organizations thinking innovatively about ways to develop more affordable housing options in these particular neighborhoods including but not limited to the creation of Louisville’s first Community Land Trust to support this effort.

https://wfpl.org/louisville-takes-steps-for-first-community-land-trust-an-affordable-housing-tool/

This dataset contains quarterly numbers of mortgages to first time buyers in England

This dataset contains quarterly number of mortgages to first time buyers in England. The data is owned by the Council of Mortgage Lenders (CML) and permission has been given to publish to ODC.

Real Estate Sales 730 Days

City of Hartford real estate sales for the past 2 years

By [source]

About this dataset

This dataset contains data on City of Hartford real estate sales for the last two years, with comprehensive records including property ID, parcel ID, sale date, sale price and more. This dataset is continuously updated each night and sourced from an official reliable source. The columns in this dataset include LocationStartNumber, ApartmentUnitNumber, StreetNameAndWay, LandSF TotalFinishedArea, LivingUnits ,OwnerLastName OwnerFirstName ,PrimaryGrantor ,SaleDate SalePrice ,TotalAppraisedValue and LegalReference - all valuable information to anyone wishing to understand the recent market trends and developments in the City of Hartford real estate industry. With this data providing detailed insights into what properties are selling at what time frame and for how much money – let’s see what secrets we can learn from examining the City of Hartford real estate activity!

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How to use the dataset

This dataset contains helpful information about homes sold in the Hartford area over the past two years. This data can be used to analyze trends in real estate markets, as well as monitor sales activity for various areas.

In order to use this dataset, you will need knowledge of EDA (Exploratory Data Analysis) such as data cleaning and data visualization techniques. You will also need a basic understanding of SQL queries and Python scripting language.

The first step is to familiarize yourself with the columns and information contained within the dataset by analyzing descriptive statistics like mean, min, max etc. Next you can filter or “slice” the data based on certain criteria or variables that interest you - such as sale date range, location (by street name or zip code), sale price range, type of dwelling unit etc. After using various filters for analysis it is important to take an error-check step by looking for outliers or any discrepancies that may exist - this will ensure more accuracy in results when plotting graphs and visualizing trends via software tools like Tableau and Power BI etc.

Next you can conduct exploratory analysis through plot visualizations of relationships between buyer characteristics (first & last name) vs prices over time; living units vs square footage stats; average price per bedroom/bathroom ratio comparisons etc – all while taking into account external factors such as seasonal changeovers that could affect pricing fluctuations during given intervals across multiple neighborhoods - use interactive maps if available ets. At this point it's easy to compile insightful reports containing commonalities amongst buyers and begin generalizing your findings with extrapolations which allow us gain a better understanding of current market conditions across different demographic spectrums being compared ie traditional Vs luxury properties – all made possible simply through dedicated research with datasets like these!

Research Ideas

• Analyzing market trends in the City of Hartford's real estate industry by tracking sale prices and appraised values over time to identify regions who are being under or over valued.
• Conducting a predictive analysis project to predict future sales prices, annual appreciation rates, and key features associated with residential properties such as total finished area and living units for investment purposes.
• Studying the impact of local zoning laws on property ownership and development by comparing sale dates, primary grantors, legal references, street names and ways in a given area over time

Acknowledgements

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

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: real-estate-sales-730-days-1.csv | Column name | Description | |:------------------------|:---------------------------------------------------------------| | LocationStartNumber | The starting number of the location of the property. (Integer) | | ApartmentUnitNumber | The apartment unit number of the property. (Integer) | | StreetNameAndWay | The st...

Housing indicators, including dwelling characteristics (as well as condominium status and structural type of dwelling), level of dwelling and neighbourhood satisfaction reported by the reference person (the person responsible for housing decisions), reasons for moving from previous dwelling, by tenure including first-time homebuyer status, Canada, provinces and territories, populations centres, select census metropolitan areas (CMAs) and census agglomerations (CAs).

United States HAI: First Time: Starter Home Price data was reported at 226,900.000 USD in Sep 2018. This records a decrease from the previous number of 227,800.000 USD for Jun 2018. United States HAI: First Time: Starter Home Price data is updated quarterly, averaging 119,900.000 USD from Mar 1981 (Median) to Sep 2018, with 151 observations. The data reached an all-time high of 227,800.000 USD in Jun 2018 and a record low of 54,700.000 USD in Mar 1981. United States HAI: First Time: Starter Home Price data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB019: Housing Affordability Index: First Time Buyers.

This data set contains Help to Buy: Equity Loan statistics at local authority level and includes total equity loans and equity loans to first time buyers . For data released from 5 March 2015 onwards, the Homes and Community Agency (HCA) have revised the completion date for the entire Help to Buy Equity Loan time series. The HCA have stopped counting payment date (when the money out is paid out by the HCA) and now report on the expected actual completion date. It is more accurate and is closer to the live situation, especially when HCA now recognise an asset based on a completion, rather than exchange and approved claim. As a result (and due to reinstating accounts) HCA have seen movement of actual completions dates. There should not be this level of difference moving forward, it was a one off activity.

This data set contains Help to Buy: Equity Loan statistics at local authority level and includes total equity loans and equity loans to first time buyers . For data released from 5 March 2015 onwards, the Homes and Community Agency (HCA) have revised the completion date for the entire Help to Buy Equity Loan time series. The HCA have stopped counting payment date (when the money out is paid out by the HCA) and now report on the expected actual completion date. It is more accurate and is closer to the live situation, especially when HCA now recognise an asset based on a completion, rather than exchange and approved claim. As a result (and due to reinstating accounts) HCA have seen movement of actual completions dates. There should not be this level of difference moving forward, it was a one off activity. The figures cover the launch of the scheme on 1 April 2013 until 30 September 2016.

Information on the allocation of completed sales to postcode sectors is derived using the latest available information on the full postcode for each scheme, which may be subject to revision.

For sales before 31 March 2014, properties are included under the local authority district to which they were initially allocated. In some cases, this differs from latest information, which forms the basis of the first column of local authority district figures. Figures for some local authorities may be subject to revisions later in the year.

Although local authority information is validated against other geographic data at the time of data entry, detailed reconciliation of the data, conducted twice a year, may result in a small number of changes to these monthly releases, for example where a new development crosses a local authority boundary.

An equity loan is Government financial assistance given to eligible applicants to purchase an eligible home through a Government equity mortgage secured on the home. The Government equity mortgage is ranked second in priority behind an owner’s main mortgage lender.

This scheme offers up to 20 per cent of the value as Government assistance to purchasers buying a new build home. The buyer must provide a cash deposit of at least 5 per cent and a main mortgage lender must provide a loan of at least 75 per cent.

The Government assistance to buy is made through an equity loan made by the Homes and Communities Agency (HCA) to the purchaser.

Help to Buy equity loans are only available on new build homes and the maximum purchase price is £600,000. Equity loan assistance for purchasers is paid via house builders registered with the HCA to participate in the Help to Buy equity loan initiative. The payment is made to builders (via solicitors) at purchaser legal completion.

The equity loan is provided without fees for the first five years of ownership.

The property title is held by the home owner who can therefore sell their home at any time and upon sale should provide the government the value of the same equity share of the property when it is sold.

For further information see
Help to Buy (equity loan) scheme monthly statistics.

Analysis of ‘Maryland Mortgage (Single Family Loans) FY 2011-2019’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/0479e22f-5548-4e3c-ba58-a418f8649f2f on 27 January 2022.

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

The Maryland Mortgage Program provides help in the form of Down Payment Assistance, as well as a range of Partner Match programs from employers, developers and community organizations that can help you cover these down payment and closing costs. These programs may make it possible for first-time homebuyers to afford a mortgage when they would not be able to do so the conventional way.

DISCLAIMER: Some of the information may be tied to the Department’s bond funded loan programs and should not be relied upon in making an investment decision. The Department provides comprehensive quarterly and annual financial information and operating data regarding its bonds and bond funded loan programs, all of which is posted on the publicly-accessible Electronic Municipal Market Access system website (commonly known as EMMA) that is maintained by the Municipal Securities Rulemaking Board, and on the Department’s website under Investor Information.

More information accessible here: http://dhcd.maryland.gov/Investors/Pages/default.aspx

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

This dataset contains quarterly median loan to value ratios for first time buyers in England.

This dataset contains quarterly median loan to value ratios for first time buyers in England. The data is owned by the Council of Mortgage Lenders (CML) and permission has been given to publish to ODC.

This dataset contains quarterly median capital and interest payments as a percentage of income for first time buyers in England This dataset contains quarterly median capital and interest payments as a percentage of income for first time buyers in England. The data is owned by the Council of Mortgage Lenders (CML)and permission has been given to publish to ODC.

Household characteristics, including household type, age group of the reference person (the person responsible for housing decisions), employment status of the reference person, visible minority status of the reference person, and degree of difficulty for the household to meet its financial needs, by tenure including first-time homebuyer status, Canada, provinces and territories, population centres, and selected census metropolitan areas (CMAs) and census agglomerations (CAs).

This dataset comprises annual rolling total of the number of mortgages to first time buyers in England.

Analysis of ‘ Zillow Housing Aspirations Report’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/zillow-housing-aspirations-reporte on 13 February 2022.

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

About this dataset

Additional Data Products

Product: Zillow Housing Aspirations Report

Date: April 2017

Definitions

Home Types and Housing Stock

• All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.
• Condo/Co-op: Condominium and co-operative homes.
• Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.
• Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Additional Data Products

• Zillow Home Value Forecast (ZHVF): The ZHVF is the one-year forecast of the ZHVI. Our forecast methodology is methodology post.
• Zillow creates our negative equity data using our own data in conjunction with data received through our partnership with TransUnion, a leading credit bureau. We match estimated home values against actual outstanding home-related debt amounts provided by TransUnion. To read more about how we calculate our negative equity metrics, please see our here.
• Cash Buyers: The share of homes in a given area purchased without financing/in cash. To read about how we calculate our cash buyer data, please see our research brief.
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio, Historical ZHVI, Historical ZHVI and Houshold Income are calculated as a part of Zillow’s quarterly Affordability Indices. To calculate mortgage affordability, we first calculate the mortgage payment for the median-valued home in a metropolitan area by using the metro-level Zillow Home Value Index for a given quarter and the 30-year fixed mortgage interest rate during that time period, provided by the Freddie Mac Primary Mortgage Market Survey (based on a 20 percent down payment). Then, we consider what portion of the monthly median household income (U.S. Census) goes toward this monthly mortgage payment. Median household income is available with a lag. For quarters where median income is not available from the U.S. Census Bureau, we calculate future quarters of median household income by estimating it using the Bureau of Labor Statistics’ Employment Cost Index. The affordability forecast is calculated similarly to the current affordability index but uses the one year Zillow Home Value Forecast instead of the current Zillow Home Value Index and a specified interest rate in lieu of PMMS. It also assumes a 20 percent down payment. We calculate rent affordability similarly to mortgage affordability; however we use the Zillow Rent Index, which tracks the monthly median rent in particular geographical regions, to capture rental prices. Rents are chained back in time by using U.S. Census Bureau American Community Survey data from 2006 to the start of the Zillow Rent Index, and Decennial Census for all other years.
• The mortgage rate series is the average mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate mortgage in 15-minute increments during business hours, 6:00 AM to 5:00 PM Pacific. It does not include quotes for jumbo loans, FHA loans, VA loans, loans with mortgage insurance or quotes to consumers with credit scores below 720. Federal holidays are excluded. The jumbo mortgage rate series is the average jumbo mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate, jumbo mortgage in one-hour increments during business hours, 6:00 AM to 5:00 PM Pacific Time. It does not include quotes to consumers with credit scores below 720. Traditional federal holidays and hours with insufficient sample sizes are excluded.

About Zillow Data (and Terms of Use Information)

• Zillow is in the process of transitioning some data sources with the goal of producing published data that is more comprehensive, reliable, accurate and timely. As this new data is incorporated, the publication of select metrics may be delayed or temporarily suspended. We look forward to resuming our usual publication schedule for all of our established datasets as soon as possible, and we apologize for any inconvenience. Thank you for your patience and understanding.
• All data accessed and downloaded from this page is free for public use by consumers, media, analysts, academics etc., consistent with our published Terms of Use. Proper and clear attribution of all data to Zillow is required.
• For other data requests or inquiries for Zillow Real Estate Research, contact us here.
• All files are time series unless noted otherwise.
• To download all Zillow metrics for specific levels of geography, click here.
• To download a crosswalk between Zillow regions and federally defined regions for counties and metro areas, click here.
• Unless otherwise noted, all series cover single-family residences, condominiums and co-op homes only.

Source: https://www.zillow.com/research/data/

This dataset was created by Zillow Data and contains around 200 samples along with Unnamed: 1, Unnamed: 0, technical information and other features such as: - Unnamed: 1 - Unnamed: 0 - and more.

How to use this dataset

• Analyze Unnamed: 1 in relation to Unnamed: 0
• Study the influence of Unnamed: 1 on Unnamed: 0
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Acknowledgements

If you use this dataset in your research, please credit Zillow Data

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