Housing Index in Switzerland increased to 202.23 points in the third quarter of 2025 from 200.07 points in the second quarter of 2025. This dataset provides - Switzerland House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

House prices in Switzerland continued their rise in 2020, having experienced decreases only in late 2016 and early 2017 in the last decade. Based on the average transaction fees of both houses and apartments across three separate providers, house prices grew by by over ***** percent year-on-year in the second quarter of 2020 (over **** percent y-o-y when adjusted for inflation). Before this, growth did slow down a bit due to stricter bank lending criteria in the country.

Key information about House Prices Growth

• Switzerland house prices grew 3.4% YoY in Sep 2025, following an increase of 2.9% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1971 to Sep 2025, with an average growth rate of -0.4%.
• House price data reached an all-time high of 26.2% in Mar 1973 and a record low of -9.0% in Dec 1975.

CEIC calculates House Prices Growth from quarterly Real Estate Price Index. Swiss National Bank provides Real Estate Price Index with base Q1 2000=100. House Prices Growth covers single family homes only.

Geneva was the most expensive Swiss city to buy an apartment in, with average values of approximately ****** euros per square meter in the first quarter of 2025. The price of an apartment in Bern was significantly lower, with values of approximately ***** euros per square meter.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

Comprehensive dataset containing 193 verified Housing complex businesses in Switzerland with complete contact information, ratings, reviews, and location data.

Financial overview and grant giving statistics of Switzerland County Housing Inc.

What are the top vacation rentals in Domleschg? How many vacation rentals have private pools in Domleschg? Which vacation homes in Domleschg are best for families? How many Rentbyowner vacation rentals are available in Domleschg?

This statistic displays the distribution of real estate transactions in Switzerland made between January and October 2017, by category. It can be seen that with ** percent, residential property transactions made up the largest share of transactions.

Switzerland Time Required to Register Property data was reported at 16.000 Day in 2017. This stayed constant from the previous number of 16.000 Day for 2016. Switzerland Time Required to Register Property data is updated yearly, averaging 16.000 Day from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 16.000 Day in 2017 and a record low of 16.000 Day in 2017. Switzerland Time Required to Register Property data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Company Statistics. Time required to register property is the number of calendar days needed for businesses to secure rights to property.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Introduction

This dataset contains detailed data on 42,207 apartments (242,257 rooms) in 3,093 buildings including their geometries, room typology as well as their visual, acoustical, topological and daylight characteristics.

Procurement

The data is sourced from commercial clients of Archilyse AG specializing on the digitization and analysis of buildings. The existing building plans of clients are converted into a geo-referenced, semantically annotated representation and undergo a manual Q/A process to ensure accuracy of the data and to ensure a maximum 5%-deviation in the apartments' areas (validated with a median deviation of 1.2%).

Geometries

The dataset contains a file geometries.csv which contains the geometries of all areas, walls, railings, columns, windows, doors and features (sinks, bathtubs, etc.) of an apartment.

In total the datasets contains the 2D geometry of ~1.2 million separators (walls, railings), ~550,000 openings (windows, doors), ca. 400,000 areas (rooms, bathrooms, kitchens, etc.) and ~240,000 features (sinks, toilets, bathtubs, etc.).

Each row contains:

• entity_type: The entity type (area, separator, opening, feature)
• entity_subtype: The entity’s sub type (e.g. WALL)
• geometry: The element’s geometry as a WKT geometry. The geometry is given in the site’s local coordinate system. I.e. the position between elements of the same site are correct in respect to each other. The +y direction points northwards, the +x direction points eastwards.
• area_id: The ID of the area in which the element is spatially contained (for features)
• unit_id: The ID of the unit in which the element is spatially contained (for features, areas)
• apartment_id: The ID of the apartment (for features, areas)
• floor_id: The ID of the floor
• building_id: The ID of the building
• site_id: The ID of the site

An example:

column
entity_type	area
entity_subtype	ROOM
geometry	POLYGON ((-2.10406 4.02039…
site_id	127
building_id	164
floor_id	12864
apartment_id	d4438f2129b30290845ce7eef98a5ba7
unit_id	76643
area_id	684674

Simulations

Beside the geometrical model, we also provide simulation data on the visual, acoustic, solar, layout and connectivity-related characteristics of the apartments. The file simulations.csv contains the simulation data aggregated on a per-area basis. Each row contains the identifier columns area_id, unit_id, apartment_id, floor_id, building_id, site_id as defined above as well as 367 simulation columns. Each simulation column is formatted as:

For instance. the column view_buildings_median describes the amount of building surface that can be seen from any point in a given room. The aggregation methods vary per simulation category and are described in detail below.

Layout

The layout features represent simple features based on the geometry and composition of a room, the dataset provides the following information in an unaggregated form.

Area Basics / Geometry

dimension	description
layout_area_type	The area’s area type
layout_net_area	The area’s share of the apartment’s net area (e.g. 0 for a balcony)
layout_area	The area’s actual area
layout_perimeter	The area’s perimeter
layout_compactness	The area’s compactness (the Polsby–Popper score)
layout_room_count	The area’s share to the apartment’s room count
layout_is_navigable	True if the area is navigable by a wheelchair

Area Features

dimension	description
layout_has_sink	True if the area has a sink
layout_has_shower	True if the area has a shower
layout_has_bathtub	True if the area has a bathtub
layout_has_toilet	True if the area has a toilet
layout_has_stairs	True if the area has stairs
layout_has_entrance_door	True if the area is directly leading to an exit of the apartment

Area Windows / Doors

dimension	description
layout_number_of_doors	The number of doors directly leading to the area
layout_number_of_windows	The number of windows of the area
layout_door_perimeter	The sum of all door lengths directly leading to the area
layout_window_perimeter	The sum of all window lengths of the area

Area Walls / Railings

dimension	description
layout_open_perimeter	The sum of all of the areas boundaries that are neither walls nor railings
layout_railing_perimeter	The sum of all of the areas boundaries that are railings
layout_mean_walllengths	The mean length of the area’s sides
layout_std_walllengths	The standard deviation of the lengths of the area’s sides

Area Adjecency

dimension	description
layout_connects_to_bathroom	True if the area connects to a bathroom
layout_connects_to_private_outdoor	True if the area connects to an outside area that is private to the apartment

View

The views from an object help to understand the impact of the surroundings on the object. The view simulation calculates the visible amount of buildings, greenery, water etc. on each individual hexagon from the analyzed object. The values are expressed in steradians (sr) and represent the amount a certain object category occupies in the spherical field of view.

Each of the following dimension is provided using the room-wise aggregations min, max, mean, std, median, p20 and p80. For instance, the column view_greenery_p20 describes the amount of greenery that can be seen from at least 20% of the positions in the area.

dimension	description
view_buildings	The amount of visible buildings
view_greenery	The amount of visible greenery
view_ground	The amount of visible ground
view_isovist	The amount of visible isovist
view_mountains_class_2	The amount of visible mountains of UN mountain class 2
view_mountains_class_3	The amount of visible mountains of UN mountain class 3
view_mountains_class_4	The amount of visible mountains of UN mountain class 4
view_mountains_class_5	The amount of visible mountains of UN mountain class 5
view_mountains_class_6	The amount of visible mountains of UN mountain class 6
view_railway_tracks	The amount of visible railway_tracks
view_site	The amount of visible site
view_sky	The amount of visible sky
view_tertiary_streets	The amount of visible tertiary_streets
view_secondary_streets	The amount of visible secondary_streets
view_primary_streets	The amount of visible primary_streets
view_pedestrians	The amount of visible pedestrians
view_highways	The amount of visible highways
view_water	The amount of visible water

Sun

Sun simulations help to understand the impact of the solar radiation on the object. The outcome of the sun simulations helps to

Switzerland Procedures to Register Property data was reported at 4.000 Number in 2017. This stayed constant from the previous number of 4.000 Number for 2016. Switzerland Procedures to Register Property data is updated yearly, averaging 4.000 Number from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 4.000 Number in 2017 and a record low of 4.000 Number in 2017. Switzerland Procedures to Register Property data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Company Statistics. Number of procedures to register property is the number of procedures required for a businesses to secure rights to property.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Geneva stands out as Europe's most expensive city for apartment purchases in early 2025, with prices reaching a staggering 15,720 euros per square meter. This Swiss city's real estate market dwarfs even high-cost locations like Zurich and London, highlighting the extreme disparities in housing affordability across the continent. The stark contrast between Geneva and more affordable cities like Nantes, France, where the price was 3,700 euros per square meter, underscores the complex factors influencing urban property markets in Europe. Rental market dynamics and affordability challenges While purchase prices vary widely, rental markets across Europe also show significant differences. London maintained its position as the continent's priciest city for apartment rentals in 2023, with the average monthly costs for a rental apartment amounting to 36.1 euros per square meter. This figure is double the rent in Lisbon, Portugal or Madrid, Spain, and substantially higher than in other major capitals like Paris and Berlin. The disparity in rental costs reflects broader economic trends, housing policies, and the intricate balance of supply and demand in urban centers. Economic factors influencing housing costs The European housing market is influenced by various economic factors, including inflation and energy costs. As of April 2025, the European Union's inflation rate stood at 2.4 percent, with significant variations among member states. Romania experienced the highest inflation at 4.9 percent, while France and Cyprus maintained lower rates. These economic pressures, coupled with rising energy costs, contribute to the overall cost of living and housing affordability across Europe. The volatility in electricity prices, particularly in countries like Italy where rates are projected to reach 153.83 euros per megawatt hour by February 2025, further impacts housing-related expenses for both homeowners and renters.

In 2023, the average rent for apartments with one to *** rooms in Switzerland amounted to 1,000 Swiss francs. Renting an apartment with **** to *** rooms cost more than double, at ***** Swiss francs. In 2023, Zurich and Geneva were the Swiss cities with the highest rents.

What are the top vacation rentals in Speicher? How many vacation rentals have private pools in Speicher? Which vacation homes in Speicher are best for families? How many Rentbyowner vacation rentals are available in Speicher?

Comprehensive dataset containing 397 verified Apartment rental agency businesses in Switzerland with complete contact information, ratings, reviews, and location data.

What are the top vacation rentals in Urnaesch? How many vacation rentals have private pools in Urnaesch? Which vacation homes in Urnaesch are best for families? How many Rentbyowner vacation rentals are available in Urnaesch?

This statistic illustrates the total annual number of newly built dwelling completions and conversions in Switzerland between 2010 and 2017. Overall the number of completions and conversions in Switzerland's residential market have increased between 2010 and 2017. The number of completions increased from over **** thousand in 2010 to over ** thousand in 2017.

What are the top vacation rentals in Nods? How many vacation rentals have private pools in Nods? Which vacation homes in Nods are best for families? How many Rentbyowner vacation rentals are available in Nods?

In 2023, the average rent in Swiss cities ranged between ** Swiss franks per square meter and ** Swiss franks per square meter. In the fourth quarter of 2023, Zurich had the highest rent, at **** Swiss franks per square meter. In 2023, Switzerland was the country with the highest share of population living in rented housing in Europe.