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Autostadt Wolfsburg
Among the big winners in this year’s survey were the mid-sized cities of Wolfsburg, Ingolstadt and Erlangen
A close correlation between the degree of dynamism in Germany’s cities and a corresponding increase in property prices and rent levels is clearly evident in the latest annual ranking on Germany’s cities by business magazine Wirtschaftswoche, this time in collaboration with leading German property portal ImmobilienScout24.
Among the big winners in this year’s survey were the mid-sized cities of Wolfsburg, Ingolstadt and Erlangen, which were right up there with Munich at the very top of the table for economic dynamism. These cities had the most attractive job markets and the highest quality of life of the 71 cities included in the survey, with their success mainly attributed to the above-average exposure to the export sector of the local industries (Volkswagen in Wolfsburg, Audi in Ingolstadt, Siemens in Erlangen).
Not surprisingly, rents in Wolfsburg and Ingolstadt have risen by more than 30% over the past five years – according to ImmobilienScout24, as a result of strong inward flows of workers into the cities for comparatively well-paid jobs. The high rents prevailing in Munich, with its booming economy, have long extended way out into the suburbs.
The Wirtschaftswoche rankings indicate that the dynamic in many eastern German cities, so much a feature of the last years, is definitely slowing down as the gap to western German cities is closed. At the bottom of the table, both in existing levels and recent dynamism, are many cities in Germany’s Ruhr region with its stagnating economy, including Oberhausen, Gelsenkirchen and Bottrop.
The methodology of the Wirtschaftswoche study, this year appearing for the tenth time, is to work with researchers from the Institut der deutschen Wirtschaft in Cologne in analysing the relevant cities (this year 71, many more than the typical 50 cities analysed in the past) under 50 different criteria relating to economic structure, labour market, property market and ‘quality of life’ factors. This time the survey incorporated market data from ImmobilienScout24’s comprehensive database.
Meanwhile, a new study has just been published by Vitus Immobilien (featuring elsewhere in this issue as the subject of a possible takeover by Deutsche Annington) which examines the development of yields in Germany’s so-called B-cities, i.e. those outside the Big 7.
The study was carried out by Swiss-based real estate consultancy group Wüest & Partner on behalf of Vitus Immobilien, and concludes that investment in German residential property in the secondary cities can lead to an average of 2.6% higher yields than in the biggest cities, with the risk for investors either comparable or in many cases less.
If the current yield available in Frankfurt is 5.8%, the study claims by way of comparison, then the yield at the same risk in a secondary city should be higher, with examples given of Bremen at 7.4%, Leipzig at 7.7% and Mönchengladbach at even 8.1%. According to Ben Lehrecke, CEO at Vitus Immobilien, commenting on the study, “Investors and residential property owners will find that many secondary cities will provide a sustainably higher yield, largely due to their more balanced risk-yield profile” – yet many of these cities are overlooked or underappreciated. Not all these cities would offer such returns, he concedes, pointing out that risks associated with a location are often very dependent on a mere handful of factors and can hence be very volatile. “Investors with very short investment time horizons also need to be aware of the lower liquidity that secondary cities may offer”, he said.
Karsten Juengk at Wüest & Partner said he sees the value of the study as primarily helping investors to avoid blanket judgements. “The purpose of the study was also to cast some new light onto the frequently very intransparent markets of the secondary cities”, he added.
The study examined the risk-return profiles of 81 German cities with more than 100,000 inhabitants from a residential property investor’s perspective. Factors analysed included rental levels, percentage of income spent on housing, unemployment rate, availability of affordable housing, vacancy rates, and historic local demographic and household trends.
