Same, same – but different. There obviously should be (and is) a strong connection with the overall business cycles and the investments in the housing sector – especially regarding the production of new dwellings. These correlations are more and more visible in-line with the deregulation of markets throughout the European continent, and especially in the Nordic countries. When it comes to the development of housing prices from country to country, it seems to be, as mentioned, just accidental connections.
In the case of the Nordic countries we find parallel trends in Denmark and Finland, both with a 35 % growth in the house prices from 2005 to 2017 (February). We have not succeeded in finding common explanations for this development. Same, same – but different. In regards to Norway and Sweden, we find the same parallel, however, on a higher level. In total the Norwegian house prices in February 2017 is 2.4 times higher than in 2005 (Feb), the equivalent figure for Sweden is 2.6. This parallel exists despite of the very different trends in the overall business cycles in Norway and Sweden.
Further, it is a fact that the structure in the housing markets of these two countries are very different. In Norway the deregulation of the market started early in the 80s and today’s market has no safe haven and with an ownership rate of 80 %. The Swedish market still have “safe havens” e.g. parts of the markets are still regulated (rental levels and corrections) and the total ownership rate is close to 60 %.
The Norwegian and Swedish economy has followed different curves over the past 10 years. Sweden with its EU membership (though not EURO) and a strong, traditional export orientated industry is closely correlated to the overall business cycles in Europe. On the other hand, Norway, which is very much outside the EU-system (though more inside than the Norwegians themselves believe), in possession of its own currency, an independent interest rate policy (again not so independent as the Norwegians believe) and an economy (in this period) heavy effected by the oil/gas sector.
The housing prices and markets of Europe are local. This also counts for different parts of single countries. We see a wide spread in the house prices in different parts of each country. This is obviously also the case in the following example: Oslo and Stockholm.
As shown in the above graph (left, house prices) we have had a close to identical development of the house prices in Oslo and Stockholm in the period post 2005. Important here is that this period also includes the fundamental financial crisis in 2008. This crisis had a much stronger effect on the Swedish economy than the on the Norwegian. While Sweden experienced a strong downturn in their economy, lucky Norway was hit by a steep growth in the oil prices. From 40 $ level in 2009 to a stable 100 $ level through 2010 and all the way to then end of 2014. This development clearly boosted the Norwegian economy and saved it from heavy negative effects of the financial crisis.
In 2015 and 2016, we observe total opposite trends in the two countries. The oil prices dropped from 100 $ down to 30 $ in the beginning of 2016. This development, naturally, had strong negative effect on the Norwegian economy. In the same period, we saw strong growth in the Swedish economy (probably the strongest growth in Europe). In other words, two very different economic scenarios gave identical development in the house prices both overall in the two countries and especially in the capitols Oslo and Stockholm.
On average, from 2005 to 2016, both cities have had a 2.0 % growth in population. The year 2017 seems to be a turning point where Stockholm will experience an even stronger population increase in the years to come, while we will have the opposite situation in Oslo.
An obvious consequence of the strong price growth should be a strong upturn in the production of new dwelling/houses. In the case of Stockholm, this is partly correct. From an extreme low level in 2005, we can observe rising levels before a very noticeable growth from 2015. The same figures for Oslo shows a falling trend from 2005 to 2011, upward in 2012 and then down again to 2015, before an expected strong growth in 2018.
Logically these different trends should have had measurable effect on the housing prices. Both Oslo and Stockholm have in common a growing backlog when it comes to producing new houses. The backlog for Oslo over the past 5 years is 16.000 units (similar to 3 years of production with ref to the level of 2017), the backlog of Stockholm for the same period is 30.000 units (similar to 6 years of production = the level of 2017). The reasonable conclusion should have been stronger price growth in Stockholm than in Oslo.
Euro/m2 (ppp-adjusted) Oslo (feb. 17) Stockholm (feb. 17)
Max 9 513 10 335
Min 4 652 3 906
Difference 104 % 165 %
Average 7 596 7 355
The average m2 housing prices per February 2017 in Oslo and Stockholm were quite identical both in real terms and ppp-adjusted (as shown in the table). An interesting difference though is the spread. A much wider spread in Stockholm could give the impression that the top prices in Oslo (the Frogner area) is to low compared with the top prices in Stockholm (Vasastan/Normalm area). However, the explanation could also be that there is a wider spread in the structure of the population in Stockholm combined with the fact that the area in Stockholm with the lowest prices (Kista) is dominated by rental houses.
Same, same – but different. The development in the housing markets of Oslo and Stockholm has been almost identical in the period after 2005, despite big differences in both overall economic development, housing needs, housing production, housing prices and market structure.
This again shows that housing prices and markets are local business and one should be careful to use trends in the Norwegian market to explain the Swedish market and vice-versa. Further, we see that all countries in Europe have chosen to adapt different political strategies to secure that the production of new houses in-line with the development of the needs of the population. So far, no one model can claim to more successful than other.