Facebook
TwitterThis 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.
- 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
- 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.
If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you
Facebook
TwitterMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This USA Housing Market Dataset (Synthetic) contains 300 rows and 10 columns of real estate-related data designed for housing price prediction, trend analysis, and investment insights. It includes key property details such as price, number of bedrooms and bathrooms, square footage, year built, garage spaces, lot size, zip code, crime rate, and school ratings.
This dataset is ideal for: ✅ Machine Learning Models for predicting housing prices ✅ Market Research & Investment Analysis ✅ Exploring Property Trends in the USA ✅ Educational Purposes for Data Science and Analytics
This dataset provides a realistic yet synthetic view of the real estate market, making it useful for data-driven decision-making in the housing industry.
Let me know if you need any modifications!
Facebook
TwitterIn 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). 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. This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes: Residential Real Estate Sales Mortgage Foreclosures Residential Vacancy Parcel Year Built Parcel Condition Building Violations Owner Occupancy 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. Please refer to the presentation and executive summary for more information about the data, methodology, and findings.
Facebook
Twitterhttps://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy
Discover the booming global residential real estate market! Our in-depth analysis reveals a $11.14B market in 2025, projected to grow at a 6.07% CAGR through 2033. Learn about key drivers, trends, regional insights, and leading companies shaping this dynamic industry. Get the data-driven insights you need to succeed. Recent developments include: December 2023: The Ashwin Sheth group is planning to expand its residential and commercial portfolio in the MMR (Mumbai Metropolitan Area) region, India., November 2023: Tata Realty and Infrastructure, a wholly-owned subsidiary of Tata Sons, plans to grow its business with more than 50 projects in major cities in India, Sri Lanka and the Maldives. The projects have a development potential of more than 51 million square feet.. Key drivers for this market are: Rapid urbanization, Government initiatives. Potential restraints include: High property prices, Regulatory challenges. Notable trends are: Increased urbanization and homeownership by elderly.
Facebook
TwitterLondon maintains its dominance in European real estate with the highest prospect score of 2.66 for 2026, significantly ahead of Madrid and Paris, which scored 2.22 and 2.04, respectively. This ranking reflects a comprehensive assessment of factors that real estate investors consider crucial, including market size, economic performance, and connectivity. The gap between London and other major cities highlights its resilience despite Brexit concerns and points to continued investor confidence in the British capital's property market fundamentals. Key factors driving city rankings Market size, liquidity, and economic performance emerge as the most critical factors determining a city's investment attractiveness for 2026. London's top position is reinforced by its established market infrastructure and global connectivity, while Madrid and Paris benefit from strong economic forecasts. However, investors face mounting challenges that could impact these markets, with construction costs, capital expenditure requirements, and increasing environmental sustainability regulations cited as major concerns. Industry experts note that these factors could particularly affect development-heavy investments in emerging European markets. (1062070, 376877) Sectoral growth opportunities Data centers represent the most promising real estate investment sector in Europe for 2026, with London, Frankfurt, and Dublin emerging as primary destinations due to their growing data center capacity. New energy infrastructure and student housing follow closely as high-potential sectors. This trend reflects the broader shift toward technology-driven and specialized real estate assets. While traditional suburban offices face diminishing prospects, cities with strong digital infrastructure like London and Frankfurt are positioned to capitalize on the demand for data-focused real estate developments, potentially strengthening their overall market position in the coming years.
Facebook
Twitterhttps://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy
The Housing Data Extracted from Homes.com (USA) dataset is a comprehensive collection of 2 million real estate listings sourced from Homes.com, one of the leading real estate platforms in the United States. This dataset offers detailed insights into the U.S. housing market, making it an invaluable resource for real estate professionals, investors, researchers, and analysts.
The dataset contains extensive property details, including location, price, property type (single-family homes, condos, apartments), number of bedrooms and bathrooms, square footage, lot size, year built, and availability status. Organized in CSV format, it provides users with easy access to structured data for analyzing trends, developing investment strategies, or building real estate applications.
Key Features:
Facebook
Twitterhttps://www.expertmarketresearch.com/privacy-policyhttps://www.expertmarketresearch.com/privacy-policy
The United States real estate market was valued at USD 3.43 Trillion in 2024. The industry is expected to grow at a CAGR of 2.80% during the forecast period of 2025-2034 to reach a value of USD 4.52 Trillion by 2034. The market growth is mainly driven by the rising corporate investment, particularly in addressing the nation’s affordable housing shortage.
Major corporations are actively investing to integrate housing stability with social responsibility, supporting both new construction and the preservation of existing homes. In September 2024, UnitedHealth Group surpassed USD 1 billion in investments for affordable and mixed-income housing through direct capital and tax credits. These projects span 31 states and have delivered over 25,000 homes, simultaneously improved community health and providing secure housing for low- and moderate-income households.
Such corporate involvements are reshaping trends in United States real estate market by expanding the supply of affordable housing, reducing barriers for renters and homeowners, and stimulating development in high-demand urban and suburban areas. By aligning financial resources with strategic planning, corporations are enabling scalable solutions that meet social and economic objectives while enhancing overall market efficiency.
Facebook
Twitterhttps://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy
Discover the latest trends in the booming €1.95 trillion European residential real estate market. Explore growth forecasts (CAGR 4.5%), key drivers, regional breakdowns (UK, Germany, France), leading companies, and market challenges until 2033. Recent developments include: November 2023: DoorFeed, a Proptech company, raised EUR 12 million (USD 13.24 million) in seed funding, led by Motive Ventures and Stride and supported by renowned investors, including Seedcamp. Founded by veteran proptech entrepreneur and ex-Uber employee James Kirimi, DoorFeed aims to be the first choice for institutional investors seeking to invest in residential real estate. The company is looking to expand its footprint across Europe, with a focus on Spain, Germany, and the United Kingdom., October 2023: H.I.G, a global alternative investment firm with over USD 59 billion in assets under management, invested in the real estate development company, The Grounds Real Estate Development AG (“the Transaction”), which is listed on the alternative stock exchange. The proceeds of the transaction are expected to be utilized to fund the capital expenditures of the current projects of The Grounds. The Grounds, based in Berlin, specializes in the acquisition and development of German residential properties located in large metropolitan areas. In the transaction, the major shareholders of The Grounds, which currently hold 73% of the company’s shares, have agreed to grant H. I.G. the right to share in future rights issues.. Key drivers for this market are: Increasing Developments in the Residential Segment, Investments in the Senior Living Units. Potential restraints include: Limited Availability of Land Hindering the Market. Notable trends are: Student Housing to Gain Traction.
Facebook
TwitterData centers had the highest investment prospects among all sectors in the European real estate market in 2026, with a score of **** out of 5. Europe's main destinations for data center investments in Europe include London, Frankfurt, and Dublin: cities with a growing data center power capacity. New energy infrastructure and student housing ranked second and third with scores of **** and **** out of 5. At the other end of the scale were suburban offices with a score of *** out of 5.
Facebook
Twitterhttps://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy
The US residential real estate market is projected for steady growth (2.04% CAGR) through 2033, driven by factors like population increase and evolving housing preferences. Discover key trends, market segmentation analysis, and leading companies shaping this dynamic sector. Key drivers for this market are: Investment Plan Towards Urban Rail Development. Potential restraints include: Italy’s Fragmented Approach to Tenders. Notable trends are: Existing Home Sales Witnessing Strong Growth.
Facebook
Twitterhttps://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy
Discover the latest trends and insights into the booming US residential real estate market. Our comprehensive analysis reveals a steady CAGR of 2.04%, key drivers, market segmentation, and leading players. Learn about growth projections through 2033 and understand the opportunities and challenges shaping this dynamic sector. Recent developments include: May 2022: Resource REIT Inc. completed the sale of all of its outstanding shares of common stock to Blackstone Real Estate Income Trust Inc. for USD 14.75 per share in an all-cash deal valued at USD 3.7 billion, including the assumption of the REIT's debt., February 2022: The largest owner of commercial real estate in the world and private equity company Blackstone is growing its portfolio of residential rentals and commercial properties in the United States. The company revealed that it would shell out about USD 6 billion to buy Preferred Apartment Communities, an Atlanta-based real estate investment trust that owns 44 multifamily communities and roughly 12,000 homes in the Southeast, mostly in Atlanta, Nashville, Charlotte, North Carolina, and the Florida cities of Jacksonville, Orlando, and Tampa.. Notable trends are: Existing Home Sales Witnessing Strong Growth.
Facebook
Twitterhttps://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy
Discover the booming European residential real estate market! This in-depth analysis reveals a €1.95 trillion market projected for 4.50% CAGR growth (2025-2033), driven by urbanization, rising incomes, and government initiatives. Explore market trends, key players (Elm Group, Places for People, etc.), and regional insights (UK, Germany, France). Recent developments include: November 2023: DoorFeed, a Proptech company, raised EUR 12 million (USD 13.24 million) in seed funding, led by Motive Ventures and Stride and supported by renowned investors, including Seedcamp. Founded by veteran proptech entrepreneur and ex-Uber employee James Kirimi, DoorFeed aims to be the first choice for institutional investors seeking to invest in residential real estate. The company is looking to expand its footprint across Europe, with a focus on Spain, Germany, and the United Kingdom., October 2023: H.I.G, a global alternative investment firm with over USD 59 billion in assets under management, invested in the real estate development company, The Grounds Real Estate Development AG (“the Transaction”), which is listed on the alternative stock exchange. The proceeds of the transaction are expected to be utilized to fund the capital expenditures of the current projects of The Grounds. The Grounds, based in Berlin, specializes in the acquisition and development of German residential properties located in large metropolitan areas. In the transaction, the major shareholders of The Grounds, which currently hold 73% of the company’s shares, have agreed to grant H. I.G. the right to share in future rights issues.. Key drivers for this market are: Increasing Developments in the Residential Segment, Investments in the Senior Living Units. Potential restraints include: Increasing Developments in the Residential Segment, Investments in the Senior Living Units. Notable trends are: Student Housing to Gain Traction.
Facebook
TwitterThis statistic shows the investment volume in the construction of student housing in the Netherlands from 2015 to 2018 (in million euros). As of 2018, the investment volume amounted to approximately *** million euros. This is an increase when compared to the previous year. The source mentions that 2017 saw an "expected fall" in investment volume as there was a shortage of supply, naming the student housing market a niche market that is growing in popularity.
Facebook
Twitterhttps://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy
Discover the booming Latin American residential real estate market! This in-depth analysis reveals a $477.77M (2025) market with an 8.32% CAGR, driven by urbanization and economic growth. Explore key trends, challenges, and top players in Mexico, Brazil, Colombia, and beyond. Invest wisely with our comprehensive market insights. Recent developments include: November 2023: CBRE, a prominent global consultancy and real estate services firm, unveiled its latest initiative, the Latam-Iberia platform. The platform's primary goal is to reinvigorate the real estate markets in Europe and Latin America while fostering investment ties between the two regions. By enhancing business collaborations and amplifying the visibility of real estate solutions, CBRE aims to catalyze growth in the sector., May 2023: CJ do Brasil, a subsidiary of multinational firm CJ Bio, completed its USD 57 million plant expansion in Piracicaba, 160 km from Brazil's capital. CJ Bio is renowned for its expertise in amino acid production. The expansion is projected to create 650 new job opportunities, and the investment also encompasses the establishment of residential, research, and development centers.. Key drivers for this market are: Increase in Population is Boosting the Residential Real Estate Market, Rapid Growth in Urbanization. Potential restraints include: Accelerated Increase in Construction Costs. Notable trends are: Increase in Urbanization Boosting Demand for Residential Real Estate.
Facebook
Twitterhttps://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/
Real Estate Market size was valued at USD 79.7 Trillion in 2024 and is projected to reach USD 103.6 Trillion by 2031, growing at a CAGR of 5.1% during the forecasted period 2024 to 2031
Global Real Estate Market Drivers
Population Growth and Urbanization: In order to meet the demands of businesses, housing needs, and infrastructure development, there is a constant need for residential and commercial properties as populations and urban areas rise.
Low Interest Rates: By making borrowing more accessible, low interest rates encourage both individuals and businesses to make real estate investments. Reduced borrowing costs result in reduced mortgage rates, opening up homeownership and encouraging real estate investments and purchases.
Economic Growth: A thriving real estate market is a result of positive economic growth indicators like GDP growth, rising incomes, and low unemployment rates. Robust economies establish advantageous circumstances for real estate investment, growth, and customer assurance in the housing sector. Job growth and income increases: As more people look for rental or purchase close to their places of employment, housing demand is influenced by these factors. The housing market is driven by employment opportunities and rising salaries, which in turn drive home buying, renting, and property investment activity. Infrastructure Development: The demand and property values in the surrounding areas can be greatly impacted by investments made in infrastructure projects such as public facilities, utilities, and transportation networks. Accessibility, convenience, and beauty are all improved by improved infrastructure, which encourages real estate development and investment.
Government Policies and Incentives: Tax breaks, subsidies, and first-time homebuyer programs are a few examples of government policies and incentives that can boost the real estate market and homeownership. Market stability and growth are facilitated by regulatory actions that promote affordable housing, urban redevelopment, and real estate development.
Foreign Investment: Foreign capital can be used to stimulate demand, diversify property portfolios, and pump capital into the real estate market through direct property purchases or real estate investment funds. Foreign investors are drawn to the local real estate markets by favorable exchange rates, stable political environments, and appealing returns.
Demographic Trends: Shifting demographic trends affect housing preferences and demand for various property kinds. These trends include aging populations, household formation rates, and migration patterns. It is easier for real estate developers and investors to match supply with changing market demand when they are aware of demographic fluctuations.
Technological Innovations: New technologies that are revolutionizing the marketing, transactions, and management of properties include digital platforms, data analytics, and virtual reality applications. In the real estate industry, technology adoption increases market reach, boosts customer experiences, and increases operational efficiency.
Environmental Sustainability: Decisions about real estate development and investment are influenced by the growing knowledge of environmental sustainability and green building techniques. Market activity in environmentally aware real estate categories is driven by demand for eco-friendly neighborhoods, sustainable design elements, and energy-efficient buildings.
Facebook
TwitterAttribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
This project comprises two studies that examine the relationship between investor attention and house prices in the Australian housing market. The first study investigates the correlation between investor attention, measured by the Google Search Volume Index, and house prices in Australia. It uncovers a strong positive correlation, indicating that fluctuations in investor attention closely align with changes in house prices. The study also highlights the predictive potential of investor attention in forecasting housing market trends, supported by behavioural finance principles that emphasise the impact of investor sentiment on asset pricing, particularly in real estate. The second study explores the bidirectional relationship between house prices and investor attention using OLS regression, VAR modeling, Granger causality tests, impulse response functions, and forecast error variance decomposition. The findings confirm that investor attention significantly influences housing prices, and past house prices can also impact current investor attention. In addition, short-term shocks in house prices cause fluctuations in investor attention, although these effects are transient. This study underscores the importance of integrating investor attention with traditional economic factors to better understand and predict housing market dynamics. These empirical studies contribute significantly to the literature on investor attention and housing market dynamics, representing some of the earliest empirical inquiries into the relation between housing market fluctuations and investor attention. By bridging these two critical domains, the research provides valuable insights for policymakers, real estate investors, and market analysts. The findings also lay a foundation for scholars and practitioners to enhance housing market analysis and prediction, offering substantial implications for market forecasting and intervention strategies.
Facebook
TwitterDisclaimerBefore 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.
Facebook
TwitterIn 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.
Facebook
Twitterhttps://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy
Discover the booming global condominiums and apartments market! This in-depth analysis reveals a CAGR exceeding 3%, driven by urbanization and evolving lifestyles. Explore market size, regional trends, key players (Christie International, Lennar, Savills), and future growth projections for 2025-2033. Invest wisely with our comprehensive market insights. Recent developments include: October 2022: City Developments Ltd. (CDL), controlled by billionaire Kwek Leng Beng, is proceeding with the launch of a suburban residential condominium project in Singapore's western region, indicating its confidence that property demand will be sustained despite the government's new property curbs., June 2022: ALTIDO, a European property management company, has announced two mergers and acquisitions, including Flatty and A&A Apartments & Boats. It comes less than four months after ALTIDO was acquired by Italian living company DoveVivo, ensuring it emerged from the COVID-19 pandemic with a large injection of financing under its belt and the ability to expand its inventory by 51 properties through the combined acquisitions.. Notable trends are: Increasing Demand for Condominiums in Several Regions Driving the Market.
Facebook
TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset provides monthly rental price statistics for apartments across urban neighborhoods, including average, median, minimum, and maximum rents by apartment type and location. It enables detailed market trend analysis, investment strategy development, and urban planning by offering granular insights into rental dynamics over time. The dataset is ideal for real estate professionals, investors, and researchers seeking to understand rental market fluctuations.
Facebook
TwitterThis 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.
- 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
- 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.
If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂 Thank you