Looking back on the year of the coronavirus in Switzerland

This analysis provides insight into the development of the residential real estate market in Switzerland during 2020, the year of the pandemic.

The following data include information on sales and rental prices for residential flats:

Sales price index: 2019 vs. 2020

The sales prices for flats rose in both 2019 and 2020. In urban areas and in agglomerations, the rise in prices was about equal. In rural areas, however, the rise in prices was sharper starting in Q2 2020 than in the previous year.

The following chart clearly shows the difference in the sales prices of flats:

The sales prices in rural areas rose by 1.5 percentage points in 2019, while prices rose by 2.7 percentage points in 2020. In agglomerations and cities, by contrast, prices continued to rise at roughly the same rate.

Rental price index: 2019 vs. 2020

The prices of rental flats saw effectively no change in either year across all areas through the end of Q1. In Q2 2019, rental prices started to rise. The sharpest rise was found in urban areas. The reverse was true in 2020: rental prices fell in all three areas starting in Q2, with urban areas witnessing the sharpest drop.

The following chart shows the change in rental prices:

Rental prices in rural areas, agglomerations and cities rose between 0.3 and 0.7 percentage points in 2019. While the rental prices in 2020 fell in all three areas, the drop was the largest in cities at 0.7 percentage points.

Number of properties on the market: 2020 vs. 2019

The change in the number of properties available to rent was similar in 2019 and 2020: the number rose sharply at the beginning of the year, up around 50%, and then levelled off for a while before falling precipitously again at the end of the year.

The supply of properties for sale rose much faster at the beginning of 2019 than in 2020. Otherwise, the developments in both years were similar.

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Methodology:
The analysis of transaction and supply data for residential real estate and the PriceHubble model based on big data and machine learning are used to create the indices presented here.

The PriceHubble model adjusts the prices for differences in quality to achieve a “typical standard flat”. Local differences do not materialise as a result of different property qualities, but on account of the general price development in the respective situation.

A standard flat can be described as follows: 4 rooms, 100 square metres, built in 2000, good maintenance and average fit-out standard. PriceHubble reserves the right to make adjustments, corrections and changes to the indices retrospectively.