Hospitality properties had the highest square footage price in the U.S. commercial real estate sector in the fourth quarter of 2024. Hospitality properties sold during that period had an average price of ****** U.S. dollars per square foot. Conversely, industrial properties had the lowest price, at ****** U.S. dollars per square foot.

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.

China Property Price: YTD Avg: Commercial Bldg: Existing House: Overall data was reported at 8,550.513 RMB/sq m in Mar 2025. This records a decrease from the previous number of 8,738.992 RMB/sq m for Feb 2025. China Property Price: YTD Avg: Commercial Bldg: Existing House: Overall data is updated monthly, averaging 8,677.458 RMB/sq m from Jan 2006 (Median) to Mar 2025, with 230 observations. The data reached an all-time high of 10,824.073 RMB/sq m in Mar 2019 and a record low of 4,227.000 RMB/sq m in Jun 2006. China Property Price: YTD Avg: Commercial Bldg: Existing House: Overall data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Price – Table CN.PD: NBS: Property Price: Commercial Building: Monthly.

In 2023, the average price of properties for business purposes in Beijing surpassed ** thousand yuan per square meter. The capital, together with major municipalities of Shanghai, and the southern provinces of Guangdong and Hainan are the regions with the most expensive commercial real estate in China, where the average price increased slightly to ****** yuan per square meter in 2023.

This dataset contains property sales data, including information such as PropertyID, property type (e.g., Commercial or Residential), tax keys, property addresses, architectural styles, exterior wall materials, number of stories, year built, room counts, finished square footage, units (e.g., apartments), bedroom and bathroom counts, lot sizes, sale dates, and sale prices. Explore this dataset to gain insights into real estate trends and property characteristics.

Data.milwaukee.gov, (2023). Property Sales Data. [online] Available at: https://data.milwaukee.gov [Accessed 9th October 2023].

Open Definition. (n.d.). Creative Commons Attribution 4.0 International Public License (CC BY 4.0). [online] Available at: http://www.opendefinition.org/licenses/cc-by [Accessed 9th October 2023].

Commercial properties for sale by the City of Detroit.

The Commercial Real Estate (CRE) industry is exhibiting significant variations across markets, with persistently high office vacancy rates juxtaposed against thriving prime office spaces. Hard hit by the widespread adoption of remote and hybrid work models, the overall office vacancy rate rose to 20.7% in Q2 2025, up from the pre-pandemic rate of 16.8%. However, leasing volumes for prime office spaces are climbing, providing opportunities for seasoned investors. On the other hand, the multifamily sector is gaining from a prominent move towards renting, primarily driven by housing affordability concerns and changing lifestyle preferences. This has strengthened demand for multifamily properties and opportunities to convert underutilized properties, such as offices, into residential rentals. The industrial real estate segment is also moderating, with the boom in e-commerce and industrial construction activity in 2021 and 2022 moderating more recently. Industry revenue has gained at a CAGR of 1.7% to reach $1.5 trillion through the end of 2025, including a 1.0% climb in 2025 alone. The industry is grappling with multiple challenges, including wide buyer-seller expectation gaps and significant disparities in demand across different geographies and asset types. Despite interest rate cuts in 2024 and 2025, economic uncertainty and labor market weakness have resulted in tighter credit and lending conditions. Because of remote working trends, office delinquency rates swelled to above 14.0% in 2025, leading to a job market increasingly concentrated in certain urban centers. Through the end of 2030, the CRE industry is expected to stabilize as the construction pipeline shrinks, reducing new supply and, in turn, rebalancing supply and demand dynamics. With this adjustment, occupancy rates will likely improve, and rents may gradually climb. The data center segment will witness accelerating demand propelled by the rapid expansion of artificial intelligence, cloud computing and the Internet of Things. Likewise, mixed-use properties are poised to gain popularity, driven by the growing appeal of flexible spaces that accommodate diverse businesses and residents. This new demand, coupled with the retiring baby boomer generation's preference for leisure-centric locales, is expected to push the transformation of traditional shopping plazas towards destination centers, offering continued opportunities for savvy CRE investors. Industry revenue will expand at a CAGR of 1.9% to reach $1.7 trillion in 2030.

The number of multi-dwelling and commercial buildings sold in Sweden declined gradually, reaching the lowest figure on record in 2023. Approximately 810 properties were sold in that year, down from 3,200 in 2005.

Denmark Property Price: Other Sales: Industrial Properties & Warehouses data was reported at 8,291.000 DKK th in Mar 2018. This records a decrease from the previous number of 17,336.000 DKK th for Dec 2017. Denmark Property Price: Other Sales: Industrial Properties & Warehouses data is updated quarterly, averaging 6,618.000 DKK th from Mar 1992 (Median) to Mar 2018, with 105 observations. The data reached an all-time high of 34,518.000 DKK th in Mar 2011 and a record low of 1,621.000 DKK th in Mar 1994. Denmark Property Price: Other Sales: Industrial Properties & Warehouses data remains active status in CEIC and is reported by Statistics Denmark. The data is categorized under Global Database’s Denmark – Table DK.P001: Property Price.

About this itemInteractive map showing commercial properties for sale or lease in Burnsville. A creative use of ESRI's ops dashboard to provide users with detailed commercial property information and easy/flexible filtering tools. Includes a link for sellers to add their property to the map for free. The dashboard has almost 5,000 views in 3 years. Author/ContributorMatt TaranOrganizationCity of BurnsvilleOrg Websitewww.burnsvillemn.gov

The CoStar Commercial Repeat-Sales Index (CCRSI) for office real estate in the United States started to fall in 2022, after more than a decade of steady growth. The index measures the development of sales prices of office properties with 2000 chosen as a base year. An index value of *** means that sales prices have doubled since 2000. In March 2024, the value-weighed index, which is more representative of the high-value deals in core markets, hit *** index points, down from a market peak of *** in December 2021. The equal-weighed index is more influenced by the lower-priced deals that comprise the higher share of transactions. It stood at *** index points in March 2024, down from a market peak of *** in June 2022.

Update Frequency: Yearly

Access to Residential, Condominium, Commercial, Apartment properties and vacant land sales history data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.

The Office of Policy and Management maintains a listing of all real estate sales with a sales price of $2,000 or greater that occur between October 1 and September 30 of each year. For each sale record, the file includes: town, property address, date of sale, property type (residential, apartment, commercial, industrial or vacant land), sales price, and property assessment. Data are collected in accordance with Connecticut General Statutes, section 10-261a and 10-261b: https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261a and https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261b. Annual real estate sales are reported by grand list year (October 1 through September 30 each year). For instance, sales from 2018 GL are from 10/01/2018 through 9/30/2019. Some municipalities may not report data for certain years because when a municipality implements a revaluation, they are not required to submit sales data for the twelve months following implementation.

Graph and download economic data for Producer Price Index by Industry: Insurance Agencies and Brokerages: Sale of Commercial Property and Casualty Insurance (PCU524210524210102) from Dec 2002 to Sep 2025 about property-casualty, brokers, agency, insurance, commercial, sales, PPI, industry, inflation, price index, indexes, price, and USA.

Context

This dataset consists of 1500+ listings, scraped from an Australian commercial real estate website on 14 April 2021. Only listings under 200 square meters in area were scraped to exclude large, but very sparse rural properties.

Columns

The data comes with some small processing from the listings, including the metadata. Here is a brief overview.

• title : title of the listing
• price: indicated price for the property. Unlike residential real estate, it can be quite obscure.
• nbn : availability of National Broad Band Network (fast-ish internet connection) on premises.
• address : property address.
• text : text of the add, line breaks included to replicate the structure as in the listing.
• area: floor or land area, in usually in square meters.
• type: type of business that property is most suitable for. Often regulated by local authorities.
• lattitude: geographic coordinate
• longitude: geographic coordinate

If you find this dataset interesting to play with, please come back and upvote, it helps me a ton! Also, check out my other dataset for time-series on Daily Electricity Demand in Victoria.

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.

The ProspectNow Data API delivers all the data and metadata you need for residential and commercial properties across the U.S.

It is designed to provide flexibility, as well as qualified, up-to-date data from a dependable source, so you can focus on providing great customer experiences.

Whether you want to enrich existing datasets, improve your own customer-facing application, or integrate our data into your tech stack, we have everything you need in our REST API, including:

Property Ownership Building Characteristics Valuation Mortgage Information Foreclosure/Preforeclosures Property Tax Info Market Data Properties Predicted to Sell Properties Predicted To Refinance +more

The CoStar Commercial Repeat-Sales Index (CCRSI) for hospitality real estate in the United States increased in **********, after two mild corrections in the previous year. In **********, the index stood at *** index points, down from a market peak of *** index points in **************. The index measures the development of sales prices of hospitality properties, with 2000 chosen as a base year. An index value of *** means that sales prices have doubled since 2000.

introduction

This dataset provides comprehensive information on property sales in England and Wales, as sourced from the UK government's HM Land Registry. It offers valuable insights into property transactions, including sale prices, locations, and types of properties sold. This dataset is particularly useful for analysts, researchers, and businesses looking to understand market trends, property valuations, and investment opportunities in the real estate sector of England and Wales.

Summary of Results

The dataset contains records of property sales dating back to January 1995, up to the most recent monthly data. It covers various types of transactions, from residential to commercial properties, providing a holistic view of the real estate market in England and Wales.

Column Descriptions

colnames=['Transaction_unique_identifier', 'price', 'Date_of_Transfer', 'postcode', 'Property_Type', 'Old/New', 'Duration', 'PAON', 'SAON', 'Street', 'Locality', 'Town/City', 'District', 'County', 'PPDCategory_Type', 'Record_Status - monthly_file_only' ]

Address data Explaination Postcode: The postal code where the property is located. PAON (Primary Addressable Object Name): Typically the house number or name. SAON (Secondary Addressable Object Name): Additional information if the building is divided into flats or sub-buildings. Street: The street name where the property is located. Locality: Additional locality information. Town/City:The town or city where the property is located. District: The district in which the property resides. County:The county where the property is located. Price Paid:The price for which the property was sold.

Legal and Ethical Considerations

Ownership and Attribution

This dataset is the property of HM Land Registry and is released under the Open Government Licence (OGL). If you use or publish this dataset, you are required to include the following attribution statement:

"Contains HM Land Registry data © Crown copyright and database right 2021. This data is licensed under the Open Government Licence v3.0."

Usage Guidelines

The data can be used for both commercial and non-commercial purposes.

The OGL does not cover third-party rights, which HM Land Registry is not authorized to license. For any other use of the Address Data, you must contact Royal Mail.

##Suggested Usages Market Trend Analysis: Understand the ups and downs of the property market over time. Investment Research: Identify potential areas for property investment. Academic Studies: Use the data for economic research and studies related to the housing market. Policy Making: Assist government agencies in making informed decisions regarding housing policies. Real Estate Apps: Integrate the data into apps that provide property price information services.

By using this dataset, you agree to abide by the terms and conditions as specified by HM Land Registry. Failure to do so may result in legal consequences.