Graph and download economic data for Commercial Real Estate Prices for United States (COMREPUSQ159N) from Q1 2005 to Q1 2025 about real estate, commercial, rate, and USA.

Commercial property prices in the U.S. plateaued in 2025 after declining in 2023. Between 2014 and 2021, commercial real estate prices nearly doubled, with the index reaching ***** index points. Following a slowdown in the market, the index declined, falling to ****** index points in the second quarter of 2025. Despite the correction, this indicated an increase of almost ** percent in prices since 2010, which was the baseline year for the index. How have prices of different property types developed over the past years? After more than a decade of uninterrupted growth, office real estate prices started to decline in 2022, reflecting a decline in occupier demand and a tougher lending environment. Industrial real estate prices, which have grown rapidly over the past few years, also experienced a correction in late 2022. Retail real estate prices displayed most resilience amid the difficult economic environment, with the equal-weighted repeat sales index remaining stable. How much is invested in new commercial properties? The value of commercial real estate construction has been on the rise since 2010 in the United States. This trend mirrors the recovery seen across all economic sectors after the 2007-2009 recession. However, investment volumes in commercial property vary by type, with private office space, warehouses, and retail leading the pack.

The Canada commercial real estate market size was USD 66.60 Billion in 2022 and is likely to reach USD 128.65 Billion by 2031, expanding at a CAGR of 4.78% during 2023–2031. The growth of the market is attributed to the rising demand for commercial properties.

Commercial real estate is a type of property used entirely for business-related work or to provide a workspace instead of living space. Depending on the functions, commercial property is mainly divided into four classes namely office space, retail, multi-family rental, and industrial use. This four main classes of real estates are further fragmented into three classes namely class A, class B, and class C.

Class A represents best properties in terms of location, quality of infrastructure, age and aesthetic. Class B includes properties, which usually goes for restoration. Class C properties are aged, in need of maintenance, and located in less attractive areas properties. Typically, commercial real estate is rented to tenants for putting the area or space into income-generating activities to earn profit through their business operations. Commercial real estate is widely suitable for opening up various business centers including healthcare facilities, office space, restaurants, hotels, resorts, and all kinds of retailers. In comparison to the residential properties, however, to run a business operation in commercial real estate requires a large amount of capital and systematic engagement for various update business development policies. Publicly traded real estate investment trusts (REITs) is probably a more feasible mode for people to invest in commercial real estate.



The COVID-19 pandemic outbreak had negatively impacted on the market. During the pandemic, emergency lockdown imposed by government body had forced to temporary shutdown of hotels, malls, resorts, and gaming facilities as part of policies to curb the virus spread. Additionally, adoption of work from home policy by many business organizations across the globe resulted in the temporary closure of offi

The Israel Commercial Real Estate Market Report is Segmented by Property Type (Offices, Retail and More), by Business Model (Rental and Sales), by End User (Individuals / Households, Corporates & SMEs and More) and by Region (Tel-Aviv District, Jerusalem District and More). The Report Offers Market Size and Forecasts in Value (USD) for all the Above Segments.

Check Market Research Intellect's Commercial Real Estate Market Report, pegged at USD 1.1 trillion in 2024 and projected to reach USD 1.8 trillion by 2033, advancing with a CAGR of 6.5% (2026-2033).Explore factors such as rising applications, technological shifts, and industry leaders.

Commercial real estate prices in Europe plummeted in 2023 as uncertainty due to macroeconomic headwinds and tighter monetary policy continued to suppress investor sentiment and transaction volume. Green Street's pan-European commercial property price index, which measures the development of commercial real estate prices across ** of the most liquid property markets in Europe with August 2007 as a base month and an index value of 100, stood at ** index points in ************. That was a decline of about *** percent from the same month a year ago. Among the different property sectors, offices were most severely affected.

According to the Act on Reporting Real Estate Transactions, you can search for information on actual transaction prices of commercial real estate for the region and period by entering the first 5 digits of the legal dong code (Example: Jongno-gu, Seoul - 11110) and contract year and month (Example: 201801) of the Administrative Standard Code Management System (www.code.go.kr) in the data reported in accordance with the Act on Reporting Real Estate Transactions. * In order to protect personal information, only some of the address information of general buildings among commercial real estate is provided among the disclosed information.

Find detailed analysis in Market Research Intellect's Commercial Real Estate Solution Market Report, estimated at USD 1.2 trillion in 2024 and forecasted to climb to USD 1.8 trillion by 2033, reflecting a CAGR of 5.2%.Stay informed about adoption trends, evolving technologies, and key market participants.

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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.

1. Customers File (customers.csv)

• Description: This file contains information about clients involved in real estate transactions. It includes personal details such as name, surname, birth date, gender, and country, along with transaction-specific information like the purpose of the deal and the satisfaction level.
• Key Columns:
  • customerid: Unique identifier for the customer.
  • entity: Type of client, whether an individual or a company.
  • name and surname: First and last name of the customer.
  • birth_date: Customer's date of birth.
  • sex: Gender of the customer (Male/Female).
  • country and state: The country and state the customer is associated with.
  • purpose: Purpose of the transaction (e.g., Home purchase or Investment).
  • deal_satisfaction: Customer's satisfaction level with the transaction, ranging from 1 to 5.
  • mortgage: Indicates whether the transaction involved a mortgage (Yes/No).
  • source: How the customer was acquired (e.g., Website or Agency).

2. Properties File (properties.csv)

• Description: This file contains information about the properties sold, including building details, property type, area, price, and sale status.
• Key Columns:
  • id: Unique identifier for the property.
  • building: Number of the building where the property is located.
  • date_sale: The date when the property was sold.
  • type: Type of property (e.g., Apartment).
  • property#: The property number within the building.
  • area: Area of the property in square feet.
  • price: Sale price of the property.
  • status: Status of the sale (e.g., Sold).
  • customerid: The unique identifier of the customer associated with the property.

Suggested Analysis and Tasks

1 Customer Insights: - Customer Segmentation: Group customers based on demographics, purpose, or deal satisfaction to understand different customer profiles. - Satisfaction Analysis: Investigate what factors (e.g., property price, area, or mortgage involvement) influence customer satisfaction levels. - Source Effectiveness: Analyze which acquisition sources (e.g., website or agency) yield the highest deal satisfaction.

2 Property Market Analysis: - Price Trends: Analyze how property prices vary over time or by location to identify market trends. - Demand Analysis: Determine which types of properties (e.g., apartments vs. houses) are most popular based on sales data. - Area vs. Price: Explore the relationship between property area and price to develop pricing models or evaluate property value.

3 Predictive Modeling: - Price Prediction: Build models to predict property prices based on features like area, type, and location. - Satisfaction Prediction: Create models to predict customer satisfaction using transaction details and demographics. - Likelihood of Sale: Develop a model to predict the likelihood of a property being sold based on its attributes and market conditions.

4 Geographical Analysis: - Heatmaps: Create heatmaps to visualize property sales and identify high-demand areas. - Country and State Trends: Examine how real estate trends differ between countries and states.

5 Mortgage Impact Study: - Mortgage vs. Non-Mortgage Analysis: Compare transactions that involved a mortgage to those that didn’t to study the impact on price, satisfaction, and deal closure speed.

6 Time Series Analysis: - Sales Over Time: Analyze property sales over different periods to identify seasonal trends or patterns. - Customer Birth Date Analysis: Study any correlations between customers’ birth years and their purchasing behavior.

The United States real estate brokerage market, valued at $197.33 billion in 2025, is projected to experience steady growth, exhibiting a Compound Annual Growth Rate (CAGR) of 2.10% from 2025 to 2033. This growth is driven by several key factors. A robust housing market, fueled by increasing population and urbanization, continues to generate significant demand for brokerage services. Technological advancements, such as improved online platforms and data analytics, are streamlining operations and enhancing efficiency for both brokers and consumers. The rise of iBuyers and proptech companies, while posing some competition, also contribute to market expansion by creating innovative solutions and attracting a broader customer base. Furthermore, a shift toward specialized services, catering to niche markets like luxury properties or commercial real estate, is expected to contribute to market diversification and growth. The market is segmented into residential and non-residential sectors, with sales and rental services further dividing each segment. Major players such as Keller Williams, RE/MAX, Coldwell Banker, and Berkshire Hathaway Home Services maintain significant market shares, competing through brand recognition, extensive networks, and technological capabilities. However, certain restraints are present. Interest rate fluctuations and economic uncertainty can impact buyer confidence and consequently, transaction volume. Increasing regulatory scrutiny and compliance costs also add operational challenges for brokerage firms. Competition from independent agents and disruptive technologies demands continuous adaptation and innovation to maintain market competitiveness. The residential segment is expected to remain the largest, driven by consistent demand, while the non-residential sector may show slightly slower growth given fluctuations in commercial investment and development cycles. The sales segment will likely maintain its predominance, although the rental market is anticipated to see growth, reflecting evolving consumer preferences and rental market trends. The ongoing evolution of the market will likely see greater consolidation among larger firms and an increased focus on technological solutions, enhancing transparency, customer experience, and overall market efficiency. This comprehensive report provides an in-depth analysis of the United States real estate brokerage market, covering the period from 2019 to 2033. It leverages extensive market research and data analysis to offer valuable insights into market trends, growth drivers, challenges, and key players. The report is essential for investors, industry professionals, and anyone seeking a comprehensive understanding of this dynamic sector. The base year for this analysis is 2025, with estimations for 2025 and forecasts extending to 2033, utilizing historical data from 2019-2024. Search terms optimized for maximum visibility include: real estate brokerage, US real estate market, real estate trends, residential real estate, commercial real estate, real estate agents, real estate investment, real estate technology, M&A real estate, and real estate market analysis. Recent developments include: May 2024: Compass Inc., the leading residential real estate brokerage by sales volume in the United States, acquired Parks Real Estate, Tennessee's top residential real estate firm that boasts over 1,500 agents. Known for its strategic acquisitions and organic growth, Compass's collaboration with Parks Real Estate not only enriches its agent pool but also grants these agents access to Compass's cutting-edge technology and a vast national referral network., April 2024: Compass has finalized its acquisition of Latter & Blum, a prominent brokerage firm based in New Orleans. Latter & Blum, known for its strong foothold in Louisiana and other Gulf Coast metros, has now become a part of Compass. This strategic move not only solidifies Compass' presence in the region but also propels it to a significant market share, estimated at around 15% in New Orleans.. Key drivers for this market are: 4., Increasing Urbanization Driving the Market4.; Regulatory Environment Driving the market. Potential restraints include: 4., Increasing Urbanization Driving the Market4.; Regulatory Environment Driving the market. Notable trends are: Industrial Sector Leads Real Estate Absorption, Retail Tightens Vacancy Rates.

The Vietnam Commercial Real Estate Market Report is Segmented by Property Type (Offices, Retail and More), by Business Model (Rental and Sales), by End User (Individuals / Households and More) and by Region (Ho Chi Minh City, Hanoi and More). The Report Offers Market Size and Forecasts in Value (USD) for all the Above Segments.

Japan - Commercial property price index, all properties, Tokyo

The India Commercial Real Estate Market Report is Segmented by Property Type (Offices, Retail, Logistics, and Others), by Business Model (Sales and Rental), by End-User (Individuals/Households, Corporates & SMEs, and Others), and by Geography (West, South, North, and East). The Market Forecasts are Provided in Terms of Value (USD).

Real Estate Market Outlook

According to our latest research, the global real estate market size reached USD 7.12 trillion in 2024, with a robust compound annual growth rate (CAGR) of 5.3% projected through 2033. By 2033, the market is expected to surge to USD 11.36 trillion, propelled by ongoing urbanization, infrastructure development, and evolving investment patterns. Key growth factors include rising population densities in urban centers, increased demand for commercial and residential spaces, and the proliferation of digital platforms transforming property transactions and management. As per our latest research, the market is experiencing a paradigm shift, driven by technological integration, regulatory reforms, and changing consumer preferences.

The real estate market's expansion is primarily fueled by the rapid pace of urbanization and demographic shifts, particularly in emerging economies across Asia Pacific and Africa. As more people migrate to urban areas in search of better employment opportunities and improved living standards, the demand for residential and commercial properties continues to escalate. This urban influx is prompting governments and private developers to invest heavily in new housing projects, commercial complexes, and supporting infrastructure. Additionally, the rise of smart cities and sustainable development initiatives is contributing significantly to the sectorÂ’s growth, as there is an increasing emphasis on energy-efficient buildings and integrated community planning.

Another critical growth driver is the integration of technology within the real estate sector. The adoption of digital platforms, artificial intelligence, and data analytics has revolutionized property search, transactions, and management, making the process more transparent, efficient, and accessible. Online platforms are now facilitating seamless property listings, virtual tours, and digital documentation, which have become especially prominent post-pandemic. This digital transformation is attracting a new generation of tech-savvy investors and homebuyers, while also enabling real estate professionals to reach broader audiences and streamline their operations.

Furthermore, the increasing involvement of institutional investors and real estate investment trusts (REITs) is reshaping the market landscape. These entities bring in significant capital, promote professionalism, and enhance market liquidity, which helps stabilize property prices and foster sustainable growth. The growing trend of mixed-use developments—combining residential, commercial, and recreational spaces—caters to evolving consumer lifestyles and is further accelerating market expansion. Favorable government policies, such as relaxed foreign investment norms and tax incentives, are also encouraging both domestic and international investments, contributing to the overall dynamism of the global real estate market.

Commercial Real Estate plays a pivotal role in the broader real estate market, particularly in urban centers where economic activities are concentrated. The demand for office spaces, retail outlets, and hospitality properties is witnessing a significant upsurge, driven by the expansion of multinational corporations and the resurgence of the tourism and hospitality industries in the post-pandemic era. The evolution of flexible workspaces and co-working environments is reshaping the commercial real estate landscape, prompting developers to innovate and adapt to changing tenant requirements. Furthermore, the integration of smart building technologies and green certifications is attracting environmentally conscious tenants and investors, positioning the commercial segment for robust long-term growth.

From a regional perspective, Asia Pacific dominates the global real estate market, accounting for the largest share in 2024, followed closely by North America and Europe. The Asia Pacific regionÂ’s growth is fueled by rapid urbanization, a burgeoning middle class, and significant infrastructure projects in countries like China, India, and Southeast Asia. North America remains a key player, underpinned by strong demand for residential and commercial properties in the United States and Canada, while Europe benefits from stable economic conditions and a focus on sustainable development.

Dataset from Urban Redevelopment Authority. For more information, visit https://data.gov.sg/datasets/d_f333bf427c827efb484cf57a73ff700a/view

The Australia Commercial Real Estate Market Report is Segmented by Property Type (Offices, Retail and More), by Business Model (Rental and Sales), by End User (Individuals / Households, Corporates & SMEs and More) and by Region (New South Wales, Victoria, Queensland and More). The Report Offers Market Size and Forecasts in Value (USD) for all the Above Segments.

The United States, Canada, and Brazil were the largest commercial real estate markets in the Americas region in 2024. As of the last month of 2024, the value of commercial real estate in the United States was estimated at nearly **** trillion U.S. dollars. In Brazil, this figure stood at ***** billion U.S. dollars.

In 2023, the average cost for properties for business purposes in China dropped slightly, to ****** yuan per square meter. The market saw steep price rises until around 2013 when the prices were generally stabilized. Business properties can be immensely expensive in China's major cities, especially in economic hubs like Beijing and Shanghai.

The property listings dataset contains information about real estate properties available for sale or rent in Brazil. It includes details such as property type (apartment, house, commercial property), location (city, neighborhood), size (square footage, number of rooms), price, amenities, and contact information for the property owner or real estate agent. This dataset can be used for market analysis, property valuation, and identifying trends in the real estate market.

Sales and Rental Prices Dataset: The sales and rental prices dataset provides information about the prices of real estate properties in Brazil. It includes data on property transactions, including sale prices and rental prices per square meter or per month. This dataset can be used to analyze price trends, compare property prices across different regions, and identify areas with high or low real estate market demand.

Property Characteristics Dataset: The property characteristics dataset contains detailed information about the features and attributes of real estate properties. It includes data such as the number of bedrooms, bathrooms, parking spaces, floor plan, construction year, building amenities, and property condition. This dataset can be used for property classification, identifying popular property features, and evaluating property quality.

Geographical Data: Geographical data includes information about the location and spatial features of real estate properties in Brazil. It can include data such as latitude and longitude coordinates, zoning information, proximity to amenities (schools, hospitals, parks), and neighborhood demographics. This dataset can be used for spatial analysis, identifying hotspots or desirable locations, and understanding the neighborhood characteristics.

Property Market Trends Dataset: The property market trends dataset provides information about market conditions and trends in the real estate sector in Brazil. It includes data such as the number of property listings, average time on the market, price fluctuations, mortgage interest rates, and economic indicators that impact the real estate market. This dataset can be used for market forecasting, understanding market dynamics, and making informed investment decisions.

Real Estate Regulatory Data: Real estate regulatory data includes information about legal and regulatory aspects of the real estate sector in Brazil. It can include data on property ownership, property taxes, zoning regulations, building permits, and legal restrictions on property transactions. This dataset can be used for legal compliance, understanding property ownership rights, and assessing the legal framework for real estate transactions.

Historical Data: Historical real estate data includes past records and trends of property prices, market conditions, and sales volumes in Brazil. This dataset can span several years and can be used to analyze long-term market trends, compare current market conditions with historical data, and assess the performance of the real estate market over time.