EUROPEAN COMMERCIAL PROPERTY FOCUS

Transcription

1 EUROPEAN COMMERCIAL PROPERTY FOCUS Editors: Roger Bootle and Ed Stansfield Where is the potential for office rental value growth strongest? An analysis of current office rental values relative to estimates of their equilibrium levels suggests that Madrid, Barcelona, the main German cities and Brussels offer the best medium-term growth potential. At the other end of the spectrum, Helsinki, Lisbon and the Italian cities are likely to underperform over the next five years. Over the last five years or so, office rental values across the euro-zone have followed very different paths. Whereas rents in some Northern euro-zone cities have increased more or less continuously since 21, in other cities office rents may not even have reached a floor. This divergence can make it hard to think about the medium-term outlook. For instance, is it the case that those markets that have already seen sizeable rental gains will now lag behind, or have these markets been strong for good reason, so that recent performance will have little bearing on the medium-term outlook? To help answer that question, in this Focus we present estimates for equilibrium office rental values across the euro-zone. To calculate these equilibrium values, we use two methods. The first method is a model based on city-level fundamental variables. We then combine the results of this model with a second set of estimates, calculated by looking at how rents and economic factors have developed in relative terms between cities. Based on the equilibrium estimates alone, it is not the case that those cities that have underperformed in recent years will automatically outperform. For instance, while the scope for gains in Madrid and Barcelona looks large, in Rome and Milan there seems much less potential for rental growth. Similarly, the outperformance of some cities in recent years is not a sign that they will now underperform. Admittedly, the potential for further gains in Helsinki seems limited, but in the German cities there seems ample scope for rents to rise further. Given we also need to take into account factors such as the economic outlook and supply developments, our final office rental forecasts will vary from the conclusions presented here, which are based on the equilibrium estimates alone. Nevertheless, they provide a useful framework for thinking about the medium-term outlook for rental values across different euro-zone cities. 19 th Aug 215 Stephen Brown Tel: +44 () North America Europe Asia 2 Bloor Street West, Suite Buckingham Palace Road #26-3 Income at Raffles Toronto, ON London 16 Collyer Quay M4W 3E2 SW1W 9TR Singapore Canada United Kingdom Tel: Tel: Tel: +44 () Managing Director Chief Property Economist Property Economist Property Economist Roger Bootle (roger.bootle@capitaleconomics.com) Ed Stansfield (ed.stansfield@capitaleconomics.com) Stephen Brown (stephen.brown@capitaleconomics.com) Kiran Raichura (kiran.raichura@capitaleconomics.com) European Commercial Property Focus 1

2 Where is the potential for office rental value growth strongest? Over the past few years, rental values in the major euro-zone office markets have followed very different paths. At one end of the spectrum, rents in Vienna, Helsinki and Munich have risen more or less continuously over the past five years and now stand 7% to 13% above their pre-crisis highs. At the other end, rents may not even have reached a floor yet in Rome and are falling again in Paris and Brussels. Meanwhile, rents in Lisbon have been more or less unchanged, at a level 13% below their pre-crisis peak, for the past 15 quarters. This divergence makes it hard to think about the medium-term outlook. Is it the case, for example, that markets which have already enjoyed sizeable gains will now lag behind markets such as Rome or Paris? Or have the stronger markets been strong for good reason, so recent performance will have little bearing on the medium term outlook? In this Focus, we present a framework for thinking about such issues. To be specific, we present an analysis of equilibrium rental values across eurozone cities and see how they compare to current levels. From there we assess what this means for future rental growth. It is worth clarifying what we mean by equilibrium rental values. We define this as where rents should be when supply and demand are balanced at a normal level. By normal, for most markets that means when vacancy rates are around 6% to 8% and when economic output and employment are in line with potential. Of course, simply defining equilibrium rental values does not tell us where they are. As such, the report starts with two sections that cover the different methods we use to determine the estimates. 1. The fundamental model The first method is a model of the relationship between rents and their various fundamental determinants. There are many different variables that will have a bearing on the level of rental values. But we have found that four key variables can explain 8% to 9% of the deviation in rental values between cities. The first variable is gross value added (GVA) per worker in the office sector. Assuming a broadly equal amount of office space per worker in each city, a higher GVA suggests that such space is being used more productively. All else being equal, that leads to a higher equilibrium rental value as firms are able to pay more for that space. The second variable is GDP per capita. This is fairly closely correlated with office GVA per worker, but it needs to be included for a couple of data reasons. Firstly, office GVA per worker is more volatile than GDP per capita and is more likely to be influenced by single industries. Secondly, Eurostat regional definitions vary widely. For instance, regional German data covers just the cities themselves, but in Spain the data cover the city and the surrounding region. These differences are more likely to affect the office GVA data than GDP per capita, given that office production is focused in city centres. Hence, we include GDP per capita as a health check. The third variable is the population of the city and surrounding urban area. A higher population provides a signal for a number of factors that may attract firms and thus influence rental values, such as a large pool of potential workers and beneficial clustering effects. Finally, proximity to the next major city provides an indication of how easy it is for firms to relocate. In theory, the closer the proximity to the nearest city, the less office space will cost as there will be greater competition between landlords. This effect seems to be enhanced by the fact that there is a positive correlation between a city s proximity to the nearest major city and the proportion of top companies headquartered there. 2 European Commercial Property Focus

3 One issue we encounter is that directly comparable city-level GVA data by sector are only available from Eurostat for 28 to either 211 or 212. However, we can use this data to calibrate our model and to gauge the relative importance of each of our four variables. We can then apply those estimated coefficients to our own up-to-date estimates of fundamentals, derived from more timely local economic indicators and national data. In isolation, there is a fairly weak correlation between each of our four variables and city-level rental values across the euro-zone. However, taking the four variables together provides much greater explanatory power. Using the 28 data, we find that the four variables explain 89% of the variation in rents across cities. While offering decent explanatory power for 28, we cannot use these initial results to estimate current equilibrium values. That s because, by its nature, the linear regression technique we use implicitly assumes that, on average, 5% of rents are too high and 5% too low. Yet in 28 it s likely that most rental values were too high, given that the economy was in the final stages of a long upswing. To correct for this problem, we also estimate the model using 211 data, and then combine the 28 and 211 coefficients. Thus, the influence of excess demand in 28 should be broadly offset by the impact of excess supply in 211. Having derived our coefficients in this way we can then apply them to our estimates of the current values of the model s four explanatory variables. To estimate 214 values for our model s inputs we have assumed that city-level economic trends have approximately matched national ones. Additionally, we have made some adjustments based on factors such as local labour market developments, for which data tend to be timelier. The largest adjustment is for Berlin, where, compared to Germany as a whole, the unemployment rate fell by an extra 1%pt over Combined with the fact that productivity probably also increased due to structural factors, we raised our mechanical estimate of Berlin GDP per capita and office GVA by a further 4%. Such estimates may prove inaccurate once official data are released, but these errors should not make large differences to our results. For instance, if we had assumed that Berlin s growth rates were in line with Germany s, than our equilibrium rental value estimate for Berlin would be just 2.5% lower. Having estimated up-to-date values for the four variables, we use the coefficients from our model to estimate equilibrium rental values. The difference between end-214 rents and the equilibrium estimates are displayed in Chart 1. CHART 1: 214 RENTS: SCOPE FOR CHANGE VERSUS Source Capital Economics EQUILIBRIUM ESTIMATE (%) Hence, based on this method, rents in Barcelona appear to have scope to increase the most, while in Amsterdam and Helsinki rents are above the equilibrium estimates. The extent of the apparent mispricing in Barcelona, at just under 5%, is large. Yet such a rise, even during a short time, is not without precedent for instance rents in Dublin have so far increased by over 65% since their trough in Rental value trends between cities Given that the differences in rental values between cities can be explained by fundamental factors, it should be the case that changes in these fundamentals between cities are reflected in European Commercial Property Focus 3

4 relative rents over time. Hence, the next method involves assessing whether rental value trends between cities are consistent with the respective economic trends. Data limitations mean that we cannot compare fundamentals over time in great detail. Yet we can gain an appreciation for how the city-level variables might have developed by looking at national economic trends. To put the cross-city trend analysis into context, consider Chart 2, which shows rents in Madrid and Munich. Since 1995, rents in Madrid have been significantly more volatile than those in Munich. The question we want to examine is whether this volatility has been justified by underlying economic fundamentals. CHART 2: OFFICE RENTAL VALUES IN MUNICH AND MADRID (EUR/SQM/ANNUM) 54 Madrid Munich Source Various Agents To answer that, we can compare the ratio of rents between cities to their relative fundamentals, represented by the ratio of GDP per capita in both markets. (See Chart 3.) It is worth noting that if GDP per capita in one city is 1% higher than in another, it does not necessarily follow that office rents will also be 1% higher as other factors also determine rental values. However, a 1% rise in GDP per capita in, say, Spain, that was not matched by a corresponding rise in Germany, ought over time to boost relative rents in Spain by around 1%. Therefore, divergences between trends in the two ratios could still represent a relative mispricing of rents. CHART 3: RATIOS OF OFFICE RENTS IN MADRID TO MUNICH AND GDP PER CAPITA IN SPAIN TO GERMANY GDP per Capita (LHS) Rents (RHS) Sources Various Agents, Thomson Datastream, Capital Economics For instance, large rises in rents in Madrid meant that the rental ratio diverged massively from the GDP per capita ratio over 2-1. In other words, rents in Madrid outperformed strongly and to a far greater extent than can be explained by Spain s comparatively stronger economic growth alone. And in 27/8 a similar spike in relative rents was also not driven by economic fundamentals. Not surprisingly, in both cases these strong rises proved unsustainable. Yet Chart 3 also suggests that rents in Madrid may now have fallen too far, given that the rental ratio has now fallen below the GDP per capita ratio. To correct this divergence, rents in Madrid would need to rise relative to Munich by 14%. For some cities, the ratios paint a less clear picture. Chart 4 repeats the exercise for Berlin and Munich. (For the German cities we can use city-level GDP per capita, as longer time series are available.) European Commercial Property Focus

5 CHART 4: RATIOS OF OFFICE RENTS IN BERLIN TO MUNICH AND GDP PER CAPITA IN BERLIN TO MUNICH expected the two ratios to converge to some degree, in line with what has actually happened GDP per capita (LHS) Rents (RHS) Sources Various Agents, Destatis, Various Agents Now that we have illustrated the principals in detail, we can repeat the exercise for the other cities. Table 1 displays the results. Based on this method, rents in Barcelona again seem to have the most potential to rise relative to Munich. However, in contrast to the conclusions from the fundamental model estimates, rents in Amsterdam do not look too high relative to Munich. In this case, there is no visible relationship between the two ratios although they both trended down from 1993 to 23, GDP per capita in Berlin has since risen strongly without any corresponding rise in the rental ratio. Why might this be? On the previous page, we said that the value of the GDP per capita ratio could not be used as an indication of where the rental ratio should be. Nevertheless, in this case the values can still provide clues as to why the rental ratio has not risen strongly in line with the GDP ratio. Simplistically, the ratio of rents gives us a rough indication of how much input costs vary by city and the ratio of GDP per capita shows us how productive each unit of input is. For Berlin and Munich, a rental ratio of.9 in 1993 tells us that the costs of production were very similar, despite the fact that in Berlin each unit of input was producing half as much output. In other words, in 1993 companies in Berlin had to pay double the rent for every unit of output that they produced compared to their counterparts in Munich. Where companies do not face obstacles to moving, such a large divergence does not make economic sense. So why did this ratio prevail in the early 199s? An obvious reason is that, before reunification, companies were not free to move. Hence, after reunification, we should have TABLE 1: 214 RENTS: SCOPE FOR CHANGE VERSUS EQUILIBRIUM ESTIMATE (%) City Fundamental Model Relative to Munich Amsterdam Athens Barcelona Berlin 7 13 Brussels 24 3 Dublin 2 6 Frankfurt 6 5 Hamburg 17 4 Helsinki Lisbon -6 9 Madrid Milan 11 Munich -4 - Paris 1-4 Rome 5-8 Vienna 6-8 Source Capital Economics 4. Combining the estimates We now combine the results of the two methods and discuss the implications for rental growth. Technically, the trend analysis results imply rental growth potential relative to Munich. Yet the fundamental model suggests that rents in Munich are more or less in-line with their equilibrium. Hence, for the sake of simplicity we do not make any adjustments to the trend analysis results. Plotting the two sets of results produces a clear trend, showing that they tend to agree. (See Chart 5.) Yet the shallowness of the trend line shows that European Commercial Property Focus 5

6 the trend analysis results typically show less mispricing than those derived from the fundamental model. Cross-city analysis CHART 5: 214 RENTS: SCOPE FOR CHANGE VERSUS EQUILIBRIUM ESTIMATE (%) Results disagree Results agree Ams Hel Lis Ber Dub Fra Par Mil Vie Rom Mad Ham Fundamental Model Source Capital Economics Bru Results agree Ath Results disagree A likely reason for this is that the fundamental model does not take into account specific factors that keep rents relatively high or low in individual cities. For instance, the responsiveness of supply and demand to changes in prices will vary by city, as will the bargaining power of landlords and tenants. A good example is Brussels, where the fundamental model suggests that rents should be 24% higher than current levels, whereas the trend analysis suggests that they are just 3% too low. A number of reasons may explain why rents have tended to be much lower than the model implies. Firstly, many tenants in Brussels are linked to the public sector. Such occupants would normally sign long-term leases and represent lower risks to landlords, thus helping to keep rents low. Moreover, academic research by other authors has shown that Brussels has some of the lowest regulatory hurdles to new supply development, which also serves to keep rents low. Although some of the results of the fundamental model look questionable, the results of our analysis on relative rental trends also require a degree of judgement to be exercised. And we are not convinced that one approach is intrinsically Bar superior to the other. Hence, to calculate our final equilibrium value estimates in most cases we take an average of the two results. The exception is when the two results disagree by a wide margin. This is the case for Amsterdam, Brussels and Barcelona, where we give a greater weight to the relative trend model. Naturally, our confidence in the final equilibrium estimate is lowest for these cities in which the estimates differ the most. With that health warning, the final estimates are presented in Table 2. TABLE 2: 214 EQUILIBRIUM RENTAL VALUE ESTIMATES City Estimate ( ) Implied Growth Barcelona Athens Madrid Berlin Hamburg Brussels Frankfurt Milan Dublin Paris Lisbon Munich Amsterdam Rome Vienna Helsinki Source Capital Economics 4. The outlook for rents Now, we address the question of how our estimates will impact the path of rental values over the next few years. In part, the outlook for rental values in each city will depend on how far rents currently are from their equilibrium. For those cities where rents look too high or too low, we might expect rents to return to these equilibrium values over the medium 6 European Commercial Property Focus

7 term, say three to five years. Yet how will rental values develop once they return to, or are already in, a position of equilibrium? To answer that question, we can look at underlying trends in real rental values in our historical data. Using real rents allows us to exclude the effects of different inflation rates in different locations. Generally speaking, over the past 2 to 25 years there are no clear trends for real rental growth in the euro-zone data. Indeed, across the euro-zone cities in this report average annual real rental growth has varied from 4.5% to 2%. Given that our euro-zone time series cover a relatively short period, these growth rates may have been affected by one-off factors. One example is the impact of German reunification on Berlin rental values, which we mentioned in Section 3. Moreover, longer-term data for the UK show that there has been no clear trend in real rental values over the past 15 years. (See Charts 6 and 7.) CHART 6: REAL UK ALL-PROPERTY RENTAL VALUES, 2= Sources IPD, Thomson Datastream CHART 7: REAL LONDON CITY OFFICE RENTAL VALUES, = Sources Steven Devaney (21), Trends in Office Rents in the City of London: Given this, we are inclined to believe that longterm real rental growth rates are unlikely to be significantly different from zero. That implies we should factor in real rental growth of % for cities such as Munich, Amsterdam and Rome, where we believe that rents are now essentially at the right level. In reality, our forecasts will depend on our perceptions of how the property cycle will develop. For instance, given the current comparatively strong outlook for the German economy and the low level of vacancy in Munich, rather than stay in line with their equilibrium it s more likely that rents will move higher. Similarly, given the poor outlook for the Greek economy, there is little scope for rents in Athens to return to our equilibrium estimate in the foreseeable future. Nevertheless, if we assume that rents in each city either return to their equilibrium value or remain in-line with it, then combining our estimates from Table 2 with our inflation forecasts provides an indication of medium-term average annual rental growth potential, as outlined in Chart European Commercial Property Focus 7

8 CHART 8: POTENTIAL MEDIUM-TERM AVERAGE ANNUAL Sources Capital Economics RENTAL GROWTH (%) To reiterate, the potential growth rates shown in Chart 8 are not our forecasts. Rather, based on factors such as the economic outlook, our forecasts will depend on how we envision supply and demand fundamentals in each city to develop. Nevertheless, the figures in Chart 8 provide a useful framework for thinking about which cities currently have, or could have, the strongest potential for rental growth. 5. Conclusion The equilibrium estimates suggest that, over the medium to long run, office property in a number of cities could benefit from strong rental growth. The candidates that stand out most are Barcelona, Athens and Madrid. Based on the assumption that rents return to the equilibrium estimates by the end of 219, these three cities have the potential to experience average annual rental growth of 6.7%, 4.7% and 3.8% respectively. However, the presence of Athens at the top of the rankings perhaps best demonstrates the health warning that accompanies this analysis. As was mentioned in the introduction, for the equilibrium rental values to be achieved both the property market and economic conditions need to return to a normal state. For Greece, this is unlikely to happen over the next five years. And, even for Spain, which is now showing signs of recovery, the after-effects of the financial crisis mean that the economy is unlikely to be at full health even by 219. That said, with Spain at least on a much sounder fundamental footing than Greece, the potential for long-run rental growth makes Madrid and Barcelona good investment opportunities. At the other end of the scale, although many investors have recently turned their attention to property in Italy and Portugal, our equilibrium estimates suggest that, based purely on a return to equilibrium, there is limited scope for office rental growth in Milan, Lisbon or Rome. Of the core markets, the results suggest that the base case for investing in Berlin, Hamburg, Brussels and Frankfurt is strongest. Moreover, for Germany at least, there s a good chance that the economy could move above its long-run potential over the coming years. With that in mind, medium-term rental growth could be even stronger than the estimates presented in Chart 8 suggest. Hence, providing investors can time their exit well, the potential for upside is strong Elsewhere in the North, our estimates suggest that, having risen strongly for several years despite the weakness of the Finnish economy, rental growth in Helsinki could now underperform. That s not to say that we expect rents to fall it typically takes a negative shock to cause such a drop but the estimates do suggest that now could be the ideal time for investors to sell office property in Helsinki. Overall, when combined with other factors such as the economic outlook and supply pipelines, the equilibrium estimates provide a useful framework for thinking about the scope for rental growth between markets. Although the estimates presented in Chart 8 are not our final forecasts, these will be updated soon in our upcoming Analyst report. 8 European Commercial Property Focus