CoVID has moved to the margin as other crises take centre stage. This analysis prepares you if the virus re-appears in the next few months. It focuses on government measures, as they have more impact on real estate returns now and in the future than excess mortality rates.
We have been tracking many factors that influence the real estate markets in Europe and have also focused on how CoVID impacted European countries and regions. This blog will highlight one of the CoVID sub-factors: government measures. We will share a small part of the process of how we got the data and subsequently processed it to the scores used in the clients’ data portal. At the end of the article, we disclose the most vulnerable regions and listed property companies.
Monitoring 58 government CoVID measures since 2020
The European Centre for Disease Prevention and Control has made an effort to collect and standardise the measures taken on a national level. This dataset has been updated monthly since the start of the pandemic in early 2020. A list of the countries* included in this dataset can be found at the end of this blog. The data consists of a chronological list of measures taken in every country, including their starting- and end date. If you want to look at the original dataset, you can find it on this page. There are 58 measures, ranging from social distancing and mask mandates to a complete lockdown.
Transforming measures into numbers
The data about measures are qualitative. This means that, in this case, it is a description of an event rather than a numerical data point. Our solution to converting this qualitative data to raw numbers is to create a severity scale for the measures. The KR&A team has given all measures a severity score. Once all measures have a severity associated with them, we calculated a monthly raw score for every country, which is the sum of all measures issued within a given month adjusted and weighted for the number of days the measure was in effect.
The raw score was then used in the normalisation process that we use in the portal. It is important to note that a high raw score corresponds to a low normalisation score since more active measures mean that the COVID-impact at that moment is higher.
Since normalisation is done every month over the entire dataset, the scores over time are comparable to each other: a normalisation of 2 in April 2020 is the same as a 2 in August 2022. In Figure 1, we compare some of these normalisations; the data shown is from the update at the start of August 2022.
Figure 1: National government CoVID measures from Jan 2022 to Jun 2022 (1 = strict, 6 = relaxed)
Dutch, German and Belgian CoVID management
In Figure 1, you can see the measures over time for the Netherlands (in blue), Belgium (in red) and Germany (in green). While the shapes of the curves share similarities, for example, seasonality, there are still distinct peaks or valleys visible between countries. Very noticeable in Germany is that after the winter of 2021, the authorities were very slow to let go of measures, compared to the Netherlands and Belgium.
However, this isn’t necessarily a bad thing for all sectors. During the pandemic, working from home has been accepted a lot more, meaning that even during times when there are a lot of measures, some economic sectors can still thrive.
Europe’s most CoVID-sensitive regions
These measures were all collected on a national level. We have also analysed vaccinations and excess mortality numbers, the latter for all regions in Europe. And we have created a regional CoVID sensitivity indicator that highlights which regions are susceptible to CoVID outbreaks as a result of their economic structure, dependence on international tourism, or the performing arts. We list the top ten regions that are most sensitive in Table 1.
Table 1: The top 20 regions in Europe that are most susceptible to CoVID outbreaks
| Region | Country | Nat. COVID measures Nov22 | Excess mortality Mar20-May22 | Nat. Vaccination partial Nov22 | Nat. Vaccination full Nov22 | Nat. Boostered full Nov22 | Covid sensitivity Nov22 |
|---|---|---|---|---|---|---|---|
| Groot-Amsterdam | Netherlands | 5.6 | -246 | 68.2 | 60.0 | 53.8 | 5.9 |
| Hauts-de-Seine | France | 6.0 | -117 | 74.2 | 71.2 | 59.0 | 5.8 |
| Paris | France | 6.0 | -1501 | 74.2 | 71.2 | 59.0 | 5.8 |
| Het Gooi en Vechtstreek | Netherlands | 5.6 | -211 | 68.2 | 60.0 | 53.8 | 5.7 |
| Barcelona | Spain | 4.6 | 7383 | 77.0 | 66.9 | 54.8 | 5.6 |
| Essonne | France | 6.0 | 268 | 74.2 | 71.2 | 59.0 | 5.6 |
| Milano | Italy | 4.6 | 1323 | 77.4 | 70.7 | 69.7 | 5.6 |
| Tarragona | Spain | 4.6 | -239 | 77.0 | 66.9 | 54.8 | 5.6 |
| Yvelines | France | 6.0 | 176 | 74.2 | 71.2 | 59.0 | 5.6 |
| Girona | Spain | 4.6 | 80 | 77.0 | 66.9 | 54.8 | 5.5 |
| Lleida | Spain | 4.6 | -253 | 77.0 | 66.9 | 54.8 | 5.5 |
| Madrid | Spain | 4.6 | 12471 | 77.0 | 66.9 | 54.8 | 5.5 |
| Val-de-Marne | France | 6.0 | 167 | 74.2 | 71.2 | 59.0 | 5.5 |
| Agglomeratie Haarlem | Netherlands | 5.6 | -453 | 68.2 | 60.0 | 53.8 | 5.4 |
| Alkmaar en omgeving | Netherlands | 5.6 | 66 | 68.2 | 60.0 | 53.8 | 5.4 |
| Bergamo | Italy | 4.6 | 2734 | 77.4 | 70.7 | 69.7 | 5.4 |
| Brescia | Italy | 4.6 | 1965 | 77.4 | 70.7 | 69.7 | 5.4 |
| IJmond | Netherlands | 5.6 | -107 | 68.2 | 60.0 | 53.8 | 5.4 |
| Seine-Saint-Denis | France | 6.0 | 813 | 74.2 | 71.2 | 59.0 | 5.4 |
| Zaanstreek | Netherlands | 5.6 | 36 | 68.2 | 60.0 | 53.8 | 5.4 |
CoVID sensitivity of the economic and cultural structure
As we permanently monitor the portfolios of all major listed property companies with reasonable asset disclosure, we can calculate the sensitivity of a REIT for CoVID. This is the regional asset value or GLA surface weighted average of the CoVID impact. The table below shows the top 10 companies, out of 93 listed property companies and German open-ended fund portfolios, with the highest susceptibility to CoVID. Based on dependency on international tourism and other regional factors. It focuses on regional sensitivity and does not reflect specific sectoral property sensitivity.
Table 2: Companies with portfolios that have the highest susceptibility to CoVID
| Company Name | Country of Listing | RE sector | No of assets |
|---|---|---|---|
| Gecina | France | Office | 242 |
| CapCo | UK | Diversified | 2 |
| Inm. Colonial | Spain | Office | 108 |
| Shaftesbury | UK | Diversified | 20 |
| Allreal | Switzerland | Diversified | 62 |
| Covivio | France | Diversified | 12 |
| Great Portland | UK | Diversified | 34 |
| Tour Eiffel | France | Office | 55 |
| Derwent London | UK | Office | 52 |
| Mobimo | Switzerland | Diversified | 117 |
