Description:

This dataset contains prices of New York houses, providing valuable insights into the real estate market in the region. It includes information such as broker titles, house types, prices, number of bedrooms and bathrooms, property square footage, addresses, state, administrative and local areas, street names, and geographical coordinates.

Key Features:

• BROKERTITLE: Title of the broker
• TYPE: Type of the house
• PRICE: Price of the house
• BEDS: Number of bedrooms
• BATH: Number of bathrooms
• PROPERTYSQFT: Square footage of the property
• ADDRESS: Full address of the house
• STATE: State of the house
• MAIN_ADDRESS: Main address information
• ADMINISTRATIVE_AREA_LEVEL_2: Administrative area level 2 information
• LOCALITY: Locality information
• SUBLOCALITY: Sublocality information
• STREET_NAME: Street name
• LONG_NAME: Long name
• FORMATTED_ADDRESS: Formatted address
• LATITUDE: Latitude coordinate of the house
• LONGITUDE: Longitude coordinate of the house

Potential Use Cases:

• Price analysis: Analyze the distribution of house prices to understand market trends and identify potential investment opportunities.
• Property size analysis: Explore the relationship between property square footage and prices to assess the value of different-sized houses.
• Location-based analysis: Investigate geographical patterns to identify areas with higher or lower property prices.
• Bedroom and bathroom trends: Analyze the impact of the number of bedrooms and bathrooms on house prices.
• Broker performance analysis: Evaluate the influence of different brokers on the pricing of houses.

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Graph and download economic data for All-Transactions House Price Index for New York (NYSTHPI) from Q1 1975 to Q2 2025 about appraisers, NY, HPI, housing, price index, indexes, price, and USA.

Enrich your real estate strategies and market insights with our comprehensive New York Housing dataset. Analyzing this dataset can aid in understanding housing market dynamics and trends, empowering organizations to refine their investment strategies and business decisions. Access the entire dataset or tailor a subset to fit your requirements.

Popular use cases include optimizing investment strategies based on neighborhood engagement and property popularity, performing detailed user behavior analysis and segmentation by housing type, price range, and location to tailor marketing and engagement efforts, and identifying and forecasting emerging trends in the New York housing market to stay ahead in the competitive real estate industry.

Graph and download economic data for S&P CoreLogic Case-Shiller NY-New York Home Price Index (NYXRSA) from Jan 1987 to Jul 2025 about New York, NY, HPI, housing, price index, indexes, price, and USA.

In October 2024, the median sales price of residential properties in New York City reached approximately ******* U.S. dollars, down from almost ******* U.S. dollars in July 2024. This was significantly higher than the national average for existing single-family homes.

Graph and download economic data for Condo Price Index for New York, New York (NYXRCSA) from Jan 1995 to Jul 2025 about New York, HPI, housing, price index, indexes, price, and USA.

View monthly updates and historical trends for Case-Shiller Home Price Index: New York, NY. Source: Standard and Poor's. Track economic data with YCharts …

Graph and download economic data for Housing Inventory: Active Listing Count in New York (ACTLISCOUNY) from Jul 2016 to Sep 2025 about active listing, NY, listing, and USA.

Graph and download economic data for All-Transactions House Price Index for Nassau County-Suffolk County, NY (MSAD) (ATNHPIUS35004Q) from Q3 1975 to Q2 2025 about Nassau, appraisers, NY, HPI, housing, price index, indexes, price, and USA.

View quarterly updates and historical trends for New York House Price All-Transactions Index. Source: Federal Housing Finance Agency. Track economic data …

Explore borrowing and mortgage trends in Washington County, including conventional vs. government loan performance, average loan sizes, and market share shifts. Data sourced from HMDA regulatory filings shows how local lending patterns evolve through changing market conditions.

All-Transactions House Price Index for New York was 1136.35000 Index 1980 Q1=100 in April of 2025, according to the United States Federal Reserve. Historically, All-Transactions House Price Index for New York reached a record high of 1136.35000 in April of 2025 and a record low of 72.54000 in January of 1976. Trading Economics provides the current actual value, an historical data chart and related indicators for All-Transactions House Price Index for New York - last updated from the United States Federal Reserve on October of 2025.

DisclaimerBefore using this layer, please review the 2018 Rochester Citywide Housing Market Study for the full background and context that is required for interpreting and portraying this data. Please click here to access the study. Please also note that the housing market typologies were based on analysis of property data from 2008 to 2018, and is a snapshot of market conditions within that time frame. For an accurate depiction of current housing market typologies, this analysis would need to be redone with the latest available data.About the DataThis is a polygon feature layer containing the boundaries of all census blockgroups in the city of Rochester. Beyond the unique identifier fields including GEOID, the only other field is the housing market typology for that blockgroup.Information from the 2018 Housing Market Study- Housing Market TypologiesThe City of Rochester commissioned a Citywide Housing Market Study in 2018 as a technical study to inform development of the City's new Comprehensive Plan, Rochester 2034, and retained czb, LLC – a firm with national expertise based in Alexandria, VA – to perform the analysis.Any understanding of Rochester’s housing market – and any attempt to develop strategies to influence the market in ways likely to achieve community goals – must begin with recognition that market conditions in the city are highly uneven. On some blocks, competition for real estate is strong and expressed by pricing and investment levels that are above city averages. On other blocks, private demand is much lower and expressed by above average levels of disinvestment and physical distress. Still other blocks are in the middle – both in terms of condition of housing and prevailing prices. These block-by-block differences are obvious to most residents and shape their options, preferences, and actions as property owners and renters. Importantly, these differences shape the opportunities and challenges that exist in each neighborhood, the types of policy and investment tools to utilize in response to specific needs, and the level and range of available resources, both public and private, to meet those needs. The City of Rochester has long recognized that a one-size-fits-all approach to housing and neighborhood strategy is inadequate in such a diverse market environment and that is no less true today. To concisely describe distinct market conditions and trends across the city in this study, a Housing Market Typology was developed using a wide range of indicators to gauge market health and investment behaviors. This section of the Citywide Housing Market Study introduces the typology and its components. In later sections, the typology is used as a tool for describing and understanding demographic and economic patterns within the city, the implications of existing market patterns on strategy development, and how existing or potential policy and investment tools relate to market conditions.Overview of Housing Market Typology PurposeThe Housing Market Typology in this study is a tool for understanding recent market conditions and variations within Rochester and informing housing and neighborhood strategy development. As with any typology, it is meant to simplify complex information into a limited number of meaningful categories to guide action. Local context and knowledge remain critical to understanding market conditions and should always be used alongside the typology to maximize its usefulness.Geographic Unit of Analysis The Block Group – a geographic unit determined by the U.S. Census Bureau – is the unit of analysis for this typology, which utilizes parcel-level data. There are over 200 Block Groups in Rochester, most of which cover a small cluster of city blocks and are home to between 600 and 3,000 residents. For this tool, the Block Group provides geographies large enough to have sufficient data to analyze and small enough to reveal market variations within small areas.Four Components for CalculationAnalysis of multiple datasets led to the identification of four typology components that were most helpful in drawing out market variations within the city:• Terms of Sale• Market Strength• Bank Foreclosures• Property DistressThose components are described one-by-one on in the full study document (LINK), with detailed methodological descriptions provided in the Appendix.A Spectrum of Demand The four components were folded together to create the Housing Market Typology. The seven categories of the typology describe a spectrum of housing demand – with lower scores indicating higher levels of demand, and higher scores indicating weaker levels of demand. Typology 1 are areas with the highest demand and strongest market, while typology 3 are the weakest markets. For more information please visit: https://www.cityofrochester.gov/HousingMarketStudy2018/Dictionary: STATEFP10: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state in the 2010 census. New York State is 36. COUNTYFP10: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county in the 2010 census. Monroe County is 055. TRACTCE10: The six-digit number assigned to each census tract in a US county in the 2010 census. BLKGRPCE10: The single-digit number assigned to each block group within a census tract. The number does not indicate ranking or quality, simply the label used to organize the data. GEOID10: A unique geographic identifier based on 2010 Census geography, typically as a concatenation of State FIPS code, County FIPS code, Census tract code, and Block group number. NAMELSAD10: Stands for Name, Legal/Statistical Area Description 2010. A human-readable field for BLKGRPCE10 (Block Groups). MTFCC10: Stands for MAF/TIGER Feature Class Code 2010. For this dataset, G5030 represents the Census Block Group. BLKGRP: The GEOID that identifies a specific block group in each census tract. TYPOLOGYFi: The point system for Block Groups. Lower scores indicate higher levels of demand – including housing values and value appreciation that are above the Rochester average and vulnerabilities to distress that are below average. Higher scores indicate lower levels of demand – including housing values and value appreciation that are below the Rochester average and above presence of distressed or vulnerable properties. Points range from 1.0 to 3.0. For more information on how the points are calculated, view page 16 on the Rochester Citywide Housing Study 2018. Shape_Leng: The built-in geometry field that holds the length of the shape. Shape_Area: The built-in geometry field that holds the area of the shape. Shape_Length: The built-in geometry field that holds the length of the shape. Source: This data comes from the City of Rochester Department of Neighborhood and Business Development.

Browse the full historical data for New York County mortgage loan limits from 1972 to 2025. This comprehensive table shows how loan limits have changed over 50+ years, helping you understand long-term trends in your local housing market.

The United States home construction market, valued at approximately $700 billion in 2025, is experiencing robust growth, projected to maintain a compound annual growth rate (CAGR) exceeding 3% through 2033. This expansion is fueled by several key factors. Firstly, a persistent housing shortage, particularly in desirable urban areas like New York City, Los Angeles, and San Francisco, continues to drive demand. Secondly, favorable demographic trends, including millennial household formation and an increasing preference for homeownership, are bolstering the sector. Furthermore, low interest rates (though this is subject to change depending on economic conditions) have historically made mortgages more accessible, stimulating construction activity. However, the market isn't without its challenges. Rising material costs, labor shortages, and supply chain disruptions continue to exert upward pressure on construction prices, potentially impacting affordability and slowing growth in certain segments. The market is segmented by dwelling type (apartments & condominiums, villas, other), construction type (new construction, renovation), and geographic location, with significant activity concentrated in major metropolitan areas. The dominance of large national builders like D.R. Horton, Lennar Corp, and PulteGroup highlights the industry's consolidation trend, while the growth of multi-family construction reflects shifting urban preferences. Looking ahead, the market's trajectory will depend on macroeconomic factors, interest rate fluctuations, government policies impacting housing affordability, and the ability of the industry to address supply-chain and labor challenges. Innovation in construction technologies, sustainable building practices, and prefabricated homes are also emerging trends expected to significantly influence market dynamics over the forecast period. The competitive landscape is characterized by a mix of large publicly traded companies and smaller regional builders. While established players dominate the market share, opportunities exist for smaller firms specializing in niche markets, such as sustainable or luxury home construction, or those focused on specific geographic areas. The ongoing expansion of the market signifies significant potential for investment and growth, despite the hurdles currently impacting the sector. Addressing supply chain disruptions and labor shortages will be crucial for sustained growth. Continued demand in key urban centers and evolving consumer preferences toward specific dwelling types will be critical factors determining the market's future trajectory. Recent developments include: June 2022 - Pulte Homes - a national brand of PulteGroup, Inc. - announced the opening of its newest Boston-area community, Woodland Hill. Offering 46 new construction single-family homes in the charming town of Grafton, the community is conveniently located near schools, dining, and entertainment, with the Massachusetts Bay Transportation Authority commuter rail less than a mile away. The collection of home designs at Woodland Hill includes three two-story floor plans, ranging in size from 3,013 to 4,019 sq. ft. with four to six bedrooms, 2.5-3.5 baths, and 2-3 car garages. These spacious home designs feature flexible living spaces, plenty of natural light, gas fireplaces, and the signature Pulte Planning Center®, a unique multi-use workstation perfect for homework or a family office., December 2022 - D.R. Horton, Inc. announced the acquisition of Riggins Custom Homes, one of the largest builders in Northwest Arkansas. The homebuilding assets of Riggins Custom Homes and related entities (Riggins) acquired include approximately 3,000 lots, 170 homes in inventory, and 173 homes in the sales order backlog. For the trailing twelve months ended November 30, 2022, Riggins closed 153 homes (USD 48 million in revenue) with an average home size of approximately 1,925 square feet and an average sales price of USD 313,600. D.R. Horton expects to pay approximately USD 107 million in cash for the purchase, and the Company plans to combine the Riggins operations with the current D.R. Horton platform in Northwest Arkansas.. Notable trends are: High-interest Rates are Negatively Impacting the Market.

Comprehensive data on average rents, vacancy rates, and market trends for New York State apartments in 2025.

View yearly updates and historical trends for New York-Jersey City-White Plains, NY-NJ Housing Affordability Index. Source: National Association of Realto…

The median rent for one- and two-bedroom apartments in New York City, NY, exceeded 2,328 U.S. dollars at the beginning of 2025. Rents soared during the COVID-19 pandemic rising by over 32 percent in December 2021. Rental growth slowed in the following three years but remained positive. In January 2025, rents increased by 3.9 percent year-on-year.Among the different states in the U.S., New York ranks as one of the most expensive rental markets.

Ready-to-Move-in Luxury Homes Market Outlook

The global market size of ready-to-move-in luxury homes is projected to experience robust growth, with an estimated CAGR of 6.5% from 2024 to 2032. In 2023, the market size was valued at approximately $160 billion, and it is expected to reach around $285 billion by 2032. This surge in growth is primarily driven by increasing demand from high-net-worth individuals seeking immediate possession properties, as well as a burgeoning preference for luxury living spaces that offer convenience, exclusivity, and top-notch amenities. Urbanization and rising disposable incomes are also significant growth factors, as they enable more people to afford upscale housing options. Furthermore, as cities expand and develop, the need for premium housing that provides both luxury and immediate occupancy has become more pronounced.

One of the key growth factors for the ready-to-move-in luxury homes market is the shift in consumer behavior towards immediate gratification and convenience. Unlike traditional real estate investments that require buyers to wait for completion, ready-to-move-in properties allow purchasers to see exactly what they are buying, eliminating uncertainties associated with delays and potential discrepancies in the final product. This factor is increasingly appealing to discerning buyers who prioritize time savings and hassle-free transactions. Moreover, the pandemic has accelerated this trend as individuals now value having a secure, fully-furnished home that can serve as a sanctuary in uncertain times, thus driving demand for immediately available luxury properties.

The role of technological advancements in real estate is another pivotal growth factor in this market. The integration of smart home technologies and advanced security systems in luxury homes has heightened their appeal, providing affluent buyers with cutting-edge living experiences. Smart homes, equipped with automated systems for lighting, climate control, and security, enhance the convenience and sophistication of luxury properties. Additionally, these technologies offer energy efficiency and sustainability benefits, aligning with the growing consumer demand for green living spaces. Sellers and developers are leveraging these technologies to differentiate their offerings in an increasingly competitive market, thereby attracting a larger pool of potential buyers.

Furthermore, the global luxury real estate market is benefiting from an influx of foreign investment, particularly in regions with stable economic conditions and favorable investment climates. International buyers are drawn to ready-to-move-in luxury homes as they provide an opportunity to diversify their portfolios with tangible assets in prime locations. Tax incentives, investment-friendly policies, and the allure of a cosmopolitan lifestyle are compelling factors attracting overseas buyers. As a result, there is an increasing trend of cross-border property investments, particularly in metropolitan areas renowned for their luxury real estate markets, such as New York, London, and Singapore.

Regionally, the market dynamics are influenced by varying economic conditions and cultural preferences. In North America, the market is buoyed by a strong economy and a high concentration of affluent individuals seeking luxury properties as both primary and secondary residences. The Asia Pacific region, particularly China and India, is witnessing rapid urbanization and wealth accumulation, contributing significantly to the demand for luxury homes. Europe, with its rich cultural heritage and stable property markets, continues to attract international buyers, especially in cities like Paris and Berlin. Meanwhile, the Middle East & Africa region is capitalizing on its luxury tourism boom, with cities like Dubai becoming hotspots for high-end residential investments.

Property Type Analysis

Within the ready-to-move-in luxury homes market, the property type segment comprises apartments, villas, townhouses, and others. Each of these categories caters to diverse consumer preferences and lifestyle requirements. Apartments are often favored in densely populated urban areas where land is scarce, providing vertical living solutions with panoramic city views and convenient access to urban amenities. Luxury apartments often feature state-of-the-art facilities, including gyms, pools, and concierge services, appealing to buyers seeking a comprehensive living experience without the upkeep of standalone properties. As urban centers continue to grow, the demand for luxury apartments is expected to remain strong.

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Context and Acknowledgements This dataset is inspired by and improves upon the City of New York's NYC Property Sales dataset. The dataset contains a record of every property sold in the New York City property market since 2003 (the first year sales data was first listed on the public record) and updates monthly to include rolling sales.

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Content This dataset contains the location, address, type, sale price, tax category, and sale date of properties sold.

• BOROUGH: Manhattan (1), Bronx (2), Brooklyn (3), Queens (4), and Staten Island (5).
• TAX CLASSES:
  • 1: Most Residential Properties up to Three Units, Vacant Lots Zoned for Residential, Condominiums Less Than Three Stories.
  • 2: All Other Residential Properties.
  • 3: Property with equipment owned by a gas, telephone, or electric company.
  • 4: All other Properties (Garages, Factories, Warehouses...)
• EASEMENT: A right that allows an entity to make limited use of another's real property.
• $0 Sales Prices: Indicates a transfer of ownership without a cash consideration.

For further reference on the fields in this dataset see the City of New York Department of Finance's Glossary of Terms and Building Codes.

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