The financial crisis in 2008 led to steep declines in the house price in France, followed by some large increases. Since 2024, the French property market has contracted again, with the inflation-adjusted home price declining by **** percent in the second quarter of 2025.

Paris, was the only major city in France where property prices decreased in the period between March 2020 and March 2022. In Strasbourg, on the other hand, residential real estate prices increased by 16.5 percent. Nantes, Rennes, Lille, and Marseille were other cities with double-digit house price growth.

Paris, Boulogne-Billancourt, and Versailles are the most expensive cities for residential real estate in France. In Paris, the average square meter price of an apartment was over 9,700 euros in December 2025, while the price for a house was even higher. Apartment prices in Paris went as high as 14,000 euros, depending on the arrondissement.

The website plans.fr, which lists more than 1,000 house plans online, has listed price increases in construction since 2020. These increases are due to several factors: — Re 2020 replacing the ROE 2012 — COVID with shortages of materials and craftsmen — High inflation of raw materials (+ 60 % on steel,...) The rises in the price of new housing since 2020 are delusional and have never been seen in recent history.

The consumer price index (CPI) is the instrument measuring inflation. It is used to estimate, between two given periods, the average variation in the prices of products consumed by households.This statistic shows the evolution of the consumer price index (CPI) of housing, water, gas, electricity, and other fuels in France, from May 2020 to October 2025. According to the source, the CPI reached 131.01 in October 2025.

General description: File containing the results of the study produced by Yanport in August 2020 on the rental and capital yield of car parks in cities with more than 100,000 inhabitants of metropolitan France. If you use this data please quote Yanport: https://www.yanport.com/ Corresponding Article: https://www.yanport.com/blog/posts/investir-parking-france-2020?utm_source=blog&utm_medium=social&utm_campaign=parking2020 ** Tabs**: Cities: contains results for the 40 cities of Metropolitan France Variables: N_price_medium: number of properties used to calculate the average displayed price (year 2019 Q2 to 2020 Q1 included). price_medium: average price displayed in EUR (year 2019 Q2 to 2020 Q1 included). N_loyer_medium: number of properties used to calculate the average rent (year 2019 Q2 to 2020 Q1 included). rent_medium: average rent in EUR (year 2019 Q2 to 2020 Q1 included). yield_loc: rental yield in % (rent_medium*12/medium price*100) N_prix_2019: number of goods used to calculate the average displayed price in 2019. price_2019: average price displayed in 2019 in EUR. N_prix_2017: number of goods used to calculate the average displayed price in 2017. price_2017: price shown average in 2017 in EUR. yield_cap: annualised return on capital between 2017 and 2019 in %: ((price_2019/price_2017)^(1/2)-1)*100 N_pub_med: number of properties used to calculate the median publication period for rentals (including Q2 to 2020 Q1) pub_med: median publication duration for rentals in days (including Q2 to 2020 Q1). License: Open license version 2.0: https://www.etalab.gouv.fr/wp-content/uploads/2017/04/ETALAB-Licence-Ouverte-v2.0.pdf

The consumer price index (CPI) is the instrument used to measure inflation. It is used to estimate the average variation in prices of products consumed by households between two given periods.This graph shows the evolution of the consumer price index (CPI) of the water supply and various services related to housing in France from May 2020 to August 2025. The CPI reached 123.79 in August 2025.

House prices in the UK rose dramatically during the coronavirus pandemic, with growth slowing down in 2022 and turning negative in 2023. The year-on-year annual house price change peaked at 14 percent in July 2022. In April 2025, house prices increased by 3.5 percent. As of late 2024, the average house price was close to 290,000 British pounds. Correction in housing prices: a European phenomenon The trend of a growing residential real estate market was not exclusive to the UK during the pandemic. Likewise, many European countries experienced falling prices in 2023. When comparing residential property RHPI (price index in real terms, e.g. corrected for inflation), countries such as Germany, France, Italy, and Spain also saw prices decline. Sweden, one of the countries with the fastest growing residential markets, saw one of the largest declines in prices. How has demand for UK housing changed since the outbreak of the coronavirus? The easing of the lockdown was followed by a dramatic increase in home sales. In November 2020, the number of mortgage approvals reached an all-time high of over 107,000. One of the reasons for the housing boom were the low mortgage rates, allowing home buyers to take out a loan with an interest rate as low as 2.5 percent. That changed as the Bank of England started to raise the base lending rate, resulting in higher borrowing costs and a decline in homebuyer sentiment.

France - Gross value added: Real estate activities was EUR93495.10 Million in September of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Gross value added: Real estate activities - last updated from the EUROSTAT on December of 2025. Historically, France - Gross value added: Real estate activities reached a record high of EUR96467.00 Million in March of 2024 and a record low of EUR68229.30 Million in June of 2020.

New version 2.0.0 with majors change

For free and complete informations concerning CASSMIR datasets, please visit our website (in French).

The CASSMIR database (Contribution to the Spatial and Sociological Analysis of Residential Real Estate Markets) is a spatial and population datasets on housing property market of the Parisian metropolitan area, from 1996 to 2018. The indicators in the CASSMIR database cover four "thematic areas of investigation" : prices, socio-demographic profile of buyers and sellers, purchasing regimes and types of property transfers and types of real estate. These indicators characterize spatial units at three scales (communal level, 1km grid and 200m grid) and population groups of buyers and sellers declined according to social, generational and gender criteria. The delivery of the database follows a series of matching and aggregation of individual data from two original databases : a database on real estate transactions (BIEN database) and a database on first-time buyer investments (PTZ database). CASSMIR delivers aggregated data (with nearly 350 variables) in open access for non-commercial use.

This repository consists of sevenfiles.

"CASSMIR_SpatialDataBase" is a Geopackage file, it lists all the data aggregated to spatial units of reference. It is composed of three layers that correspond to the geographical scale of aggregation: at a communal level, a grid of one kilometer on each side and a grid of two hundred meters on each side.

"CASSMIR_GroupesPopDataBase" is a .csv file, it lists all the data aggregated to population groups of reference. There are three types of population groups : groups referenced by the social position of the buyers/sellers (social group), groups referenced by the age group to which the buyers/sellers belong (generational group), groups referenced by the sex of the buyers/sellers (gender group).

Two metadata files (.csv) lists the metadata of the indicators made available. They are systematically structured as follows :

• Id_var: the identifier of the variable contained in "CASSMIR_SpatialDataBase" or "CASSMIR_GroupesPopDataBase"
• Unite d'observation des variables descriptives : descriptive units of observation (Prices, buyers, sellers...)
• Type d'information : precision on the type of information
• Label : Description of the contents of the variable
• Indicator_Group: The group of indicators to which the variable relates (prices, socio-demographics indicators of buyers and sellers...)
• Unit : The unit of measurement of the variable
• Spatial_Availability : A precision on the availability of the variable in the spatial database (communes, 1 km grid and 200m grid)
• GroupesPop_Availability : A precision on the availability of the variable in the population groupes database (Social, generational , gender)
• Data_Source: The main origin of the data (INSEE, BIEN and/or PTZ)
• Remarques : possible remarks on the construction of the variable

"BIENSampleForTest" and "PTZSampleForTest" are two .txt files which restore a sample of individual data from each of the original databases. All data were anonymized and the values randomized. These two files are specifically dedicated to reproducing the different stages of processing that lead to the production of the CASSMIR files ("CASSMIR_SpatialDataBase" or "CASSMIR_GroupesPopDataBase") and cannot be used in any other way.

"LEXIQUE" is a glossary of terms used to name the variables (.csv).

The creation of the database was funded by the National Reseach Agency (ANR WIsDHoM https://anr.fr/Projet-ANR-18-CE41-0004).

All CASSMIR documentation (in French) and R codes are accessible via the Gitlab repository at the following address : https://gitlab.huma-num.fr/tlecorre/cassmir.git

METADATA :

• Licence

This dataset is registered under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. You are free to copy, distribute, transmit, and adapt the data, provided that you give credit to the CASSMIR data base and specify the original source of the data. If you modify or use the data in other derivative works, you may distribute them only under the same license. You may not make commercial use of this database, nor may you use it for any purpose other than scientific research.

• Citation standard

- Figures: (CC - CASSMIR database, indicator(s) constructed from XXX data)

- Bibliography : Productions that use the CASSMIR database must reference the dataset and the data paper.

Dataset: Le Corre T., 2020, CASSMIR (Version 2.0.0) [Data set], Zenodo. http://doi.org/10.5281/zenodo.4497219

Data paper: Thibault Le Corre, « Une base de données pour étudier vingt années de dynamiques du marché immobilier résidentiel en Île-de-France », Cybergeo: European Journal of Geography [En ligne], Data papers, article No.992, mis en ligne le 09 août 2021. URL : http://journals.openedition.org/cybergeo/37430 ; DOI : https://doi.org/10.4000/cybergeo.37430

• Data paper title

"Une base de données pour étudier vingt années de dynamiques du marché immobilier en Île-de-France"

• Author

Thibault Le Corre

• Keywords

Housing market, data base, Île-de-France, spatio-temporal dynamics

• Related Publication

DOI : https://doi.org/10.4000/cybergeo.37430

• Language

French

• Time Period Covered

The time period covered by the indicators in the database depends on the data sources used, respectively:
For data from BIEN: 1996, 1999, 2003-2012, 2015, 2018
For data from PTZ: 1996-2016

• Kind of data

Nature of data submitted

• vector: Vector data

• grid: Data mesh

• code: programming code (see the website or GitLab of the project)

• Data Sources

Base BIEN

Base PTZ

• Geographical Coverage

Île-de-France region

• Geographical Unit

Municipalities and grid mesh elements (1km side grid and 200 side grid) concerned by real estate transactions

• Geographic Bounding Box

Reference Coordinate System (RCS): EPSG 2154 RGF93/Lambert 93.

- Xmin : 586421.7
- Xmax : 741205.6
- Ymin : 6780020
- Ymax : 6905324

• Type of article

Data Paper

This file makes it possible to distinguish the property of each plot of the 2020 cadastre over the entire territory of Guyana. The owners are categorised here into 6 classes (and 40 subclasses): — State; — Local authority of French Guiana; — Municipalities and their groupings; — Public or similar establishments; — Private; — Not filled in. The method of identification and classification of properties is based on manual processing carried out by AUDEG from the 2020 cadastral documentation of the Regional Directorate of Public Finance (DRFiP) of Guyana. The study report related to this data — the Atlas of Land Properties 2020 — is available for download at the following link: https://www.audeg.fr/digital-viewer/c-225

GDP: GVA: CL 2020p: swda: Services: Tradable: Real Estate Services data was reported at 80.270 EUR bn in Mar 2025. This records an increase from the previous number of 80.132 EUR bn for Dec 2024. GDP: GVA: CL 2020p: swda: Services: Tradable: Real Estate Services data is updated quarterly, averaging 44.379 EUR bn from Mar 1949 (Median) to Mar 2025, with 305 observations. The data reached an all-time high of 80.270 EUR bn in Mar 2025 and a record low of 7.497 EUR bn in Mar 1949. GDP: GVA: CL 2020p: swda: Services: Tradable: Real Estate Services data remains active status in CEIC and is reported by National Institute of Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.A026: ESA 2010: GDP: by Industry: Chain Linked 2020 Prices: Seasonally and Working Day Adjusted.

France GDP: HCE: CL 2020p: swda: Services: Tradable: Real Estate Services data was reported at 71.407 EUR bn in Mar 2025. This records an increase from the previous number of 71.161 EUR bn for Dec 2024. France GDP: HCE: CL 2020p: swda: Services: Tradable: Real Estate Services data is updated quarterly, averaging 35.569 EUR bn from Mar 1949 (Median) to Mar 2025, with 305 observations. The data reached an all-time high of 71.407 EUR bn in Mar 2025 and a record low of 6.386 EUR bn in Sep 1950. France GDP: HCE: CL 2020p: swda: Services: Tradable: Real Estate Services data remains active status in CEIC and is reported by National Institute of Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.A050: ESA 2010: GDP: Household Consumption Expenditure: Chain Linked 2020 Prices: Seasonally and Working Day Adjusted: Quarterly.

France SPPI: Sold: PT: Motion Picture, Video & Television Programme data was reported at 99.300 2015=100 in Dec 2023. This stayed constant from the previous number of 99.300 2015=100 for Sep 2023. France SPPI: Sold: PT: Motion Picture, Video & Television Programme data is updated quarterly, averaging 99.300 2015=100 from Dec 2017 (Median) to Dec 2023, with 25 observations. The data reached an all-time high of 100.300 2015=100 in Dec 2022 and a record low of 95.900 2015=100 in Jun 2020. France SPPI: Sold: PT: Motion Picture, Video & Television Programme data remains active status in CEIC and is reported by National Institute of Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.I038: Services Producer Price Index: 2015=100: French Businesses: Market Price.

France SPPI: Sold: Rental & Leasing: Other Machinery & Equipment data was reported at 108.400 2015=100 in Dec 2023. This stayed constant from the previous number of 108.400 2015=100 for Sep 2023. France SPPI: Sold: Rental & Leasing: Other Machinery & Equipment data is updated quarterly, averaging 98.700 2015=100 from Dec 2017 (Median) to Dec 2023, with 25 observations. The data reached an all-time high of 108.400 2015=100 in Dec 2023 and a record low of 97.300 2015=100 in Mar 2020. France SPPI: Sold: Rental & Leasing: Other Machinery & Equipment data remains active status in CEIC and is reported by National Institute of Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.I038: Services Producer Price Index: 2015=100: French Businesses: Market Price.

This statistic shows the average price per square meter for rental houses in France as of June, 2020, according to the price range. In 2020, the average price per square meter for rental houses reached **** euros in France.

This statistic shows the annual change in the median selling price of old houses in the largest cities in France between the first quarter of 2019 and the first quarter of 2020. During this time period, the sale price of old houses in Bordeaux increased by 2.9 percent.

Cadastre – Parcels of the territory of the Basque Country 2020 The cadastre is a set of plans and administrative files that list all the real estate properties located in each French municipality, and which records the value of them in order to serve as a basis for calculating certain taxes. (Wikipedia). The data open to date are those of the cadastral plan: plots, sections, buildings and cladding elements.The files of the properties and owners are not affected. The policy of openness and sharing of public data (“Open Data”) is led, under the authority of the Prime Minister, by the Etalab mission, led by Ms Laure Lucchesi. Raw data: https://cadastre.data.gouv.fr/datasets/cadastre-etalabCadastre – Parcels of the territory of the Basque Country 2020 The cadastre is a set of plans and administrative files that list all the real estate properties located in each French municipality, and which records the value of them in order to serve as a basis for calculating certain taxes.(Wikipedia). The data open to date are those of the cadastral plan: plots, sections, buildings and cladding elements. The files of the properties and owners are not affected. The policy of openness and sharing of public data (“Open Data”) is led, under the authority of the Prime Minister, by the Etalab mission, led by Ms Laure Lucchesi. Raw data:https://cadastre.data.gouv.fr/datasets/cadastre-etalab The cadastre is a set of plans and administrative files that list all the real estate properties located in each French municipality, and which records the value of them in order to serve as a basis for calculating certain taxes. (Wikipedia). The data open to date are those of the cadastral plan:plots, sections, buildings and cladding elements. The files of the properties and owners are not affected. The policy of openness and sharing of public data (“Open Data”) is led, under the authority of the Prime Minister, by the Etalab mission, led by Ms Laure Lucchesi. Raw data: https://cadastre.data.gouv.fr/datasets/cadastre-etalab

France E-Commerce Transactions: Value: Business & Consumer Services: Real Estate data was reported at 12.650 USD in 17 Nov 2023. This records a decrease from the previous number of 14.879 USD for 16 Nov 2023. France E-Commerce Transactions: Value: Business & Consumer Services: Real Estate data is updated daily, averaging 13.564 USD from Jan 2019 (Median) to 17 Nov 2023, with 472 observations. The data reached an all-time high of 365.514 USD in 01 Sep 2020 and a record low of 6.779 USD in 03 Nov 2023. France E-Commerce Transactions: Value: Business & Consumer Services: Real Estate data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s France – Table FR.GI.EC: E-Commerce Transactions: by Category.

This dataset describes the properties of 350 data items. This table has 18 columns that include the following: (1) the type of data: i.e. map, cross-section, long profile, table, topo-bathymetry drawn on the map, (2) the source (archive service) and reference (box number), (3) the original title (in French) and a translated English title, (4) the scale, author, and survey period, (5) the communes covered by the upstream-downstream Kilometric Points (KPs; km 0 is in Lyon, distances upstream from this reference point are negative and distances downstream are positive; the KPs were identified in ArcMap 10.5 using the GIS layer of riverine communes and active channels in 1860, to help in locating the maps with secondary channels), (6) comments on the quality and content of the data, (7) the number of images and their type (on a table or a magnetic board, HD scan, scanned and georeferenced), and (8) the storage file and sub-file.