Excerpt
Index of the thesis
Introduction
Personal motivation and aim
House price development in Berlin
Definition of bubble and structure
Analysis
Credit supply
Literature review
Relevant Data
Demography
Literature review
Relevant Data
Income / economic growth
Literature Review
Relevant Data
Interest rates/ monetary policy
Literature Review
Relevant Data
Rent
Literature Review
Relevant Data
Substitutional goods
Literature Review
Relevant Data
Psychology/expectation
Literature review
Relevant Data
Result and conclusion
Bibliography
Acknowledgement
First, my utmost gratitude goes to prof. Dmitri Boreiko for his invaluable support. In addition, this dissertation would not have been possible without the help and motivation of several individuals, such as my friends, family and university colleagues, who have all in one way or another supported me during this time.
Abstract (English)
Latterly the capital of Germany alludes to a potential real estate bubble. Does the strong price increase of 73 % on average between 2007 and 2013 really rely on speculative market behaviour or is the trend rather determined by fundamental factors? In order to find this out, the following paper examines several determinants of demand for residential objects through a qualitative analysis. Relevant determinants such as supply of credit, demographic aspects, income and economic growth, real long term interest rates and monetary policy, rent prices, substitution goods as well as the factor of expectations of the future house price development were investigated by means of empirical analysis. Anyways, the unclear result argues in favour of a price increase mainly caused by the fundamental factors.
Key words: Real estate, bubble, Berlin
Abstract (Deutsch)
In der Hauptstadt Deutschlands wird letzthin von einer möglichen Immobilienblase gesprochen. Beruht der starke Preisanstieg von durchschnittlich 73 % für Wohnimmobilien zwischen 2007 und 2013 in Berlin wirklich auf der Basis von spekulativem Marktverhalten oder ist der Trend, hingegen, auf fundamentale Faktoren zurückzuführen? Die folgende Abhandlung untersucht dies durch eine qualitative Analyse der Nachfragefaktoren für Wohnimmobilien. Zugang zu Baukrediten, demografische Aspekte wie der Bevölkerungszuwachs, Einkommen mit Wirtschaftswachstum, langfristige Zinsen mit Geldpolitik, Mietpreise, Substitutionsgüter sowie die Erwartungshaltung hinsichtlich der zukünftigen Preisentwicklung wurden mithilfe von empirischen und aktuellen Daten untersucht. Das nicht eindeutige Ergebnis spricht jedenfalls gegen eine Preisblase im Berliner Immobilienmarkt.
Schlüsselwörter: Real estate, Blase, Berlin
Abstract (Italiano)
Negli ultimi tempi nella capitale germanica si sta parlando di una potenziale bolla immobiliare. Il forte aumento dei prezzi pari al 73% per gli immobili residenziali tra il 2007 e il 2013 a Berlino è veramente dovuto a speculazioni di mercato oppure tale tendenza è, invece, riconducibile a fattori fondamentali? L'analisi riportata qui di seguito esamina questa situazione mediante un'analisi qualitativa dei fattori che determinano la domanda per immobili residenziali. L'accesso ai crediti, lo sviluppo demografico, il reddito, la crescita economica, i tassi di interesse a lungo termine, la politica monetaria, i prezzi degli affitti, i beni sostitutivi nonché le aspettative riguardanti lo sviluppo dei prezzi sono stati analizzati sulla base di dati empirici e attuali. Ad ogni modo, il risultato evidenzia in buona parte la non sussistenza di una bolla nel mercato immobiliare di Berlino.
Parole chiave: Real estate, bolla, Berlino
Introduction
Personal motivation and aim
During the last years I got more and more fascinated by characteristics of the real estate market - At the one hand, every household needs an accomodation to live in, at the other hand, a home often constitutes the most expensive investment a person ever makes. These two facts combined together provide requirements of a huge market with interesting investment oportunities.
The fact that there was no subject in my bachelor program which covers the issues of real estate and my intention to probably start a career in real estate one day, brought me to the conclusion that the degree thesis would be a good fit to engage myself a little more in this topic.
At the same time, I was thinking about a specific research question where it is possible to really learn something practical. In other words, given all the studied theory during those three years of university, I wanted to seize the chance to do something 100 % related with the real world. Moreover, a criteria was to find a topic which matters now and tomorrow and less in the past. Another useful point I found out during the work was that I could be able to review several university subjects from the previous years like financial analysis, macroeconomics and microeconomics.
Aim of the thesis is to get a better knowledge on the assessment of bubble existence in housing markets. According to mainstream economics, the process itself is considered relatively difficult. However, an advantage of such a work is that I can eventually use the gained information to implement a real project in the future. In addition, this kind of problem approach could then be used for other markets as well: proving a price increase, finding out how it came about, discovering if its factors consist in a bubble risk or not. Aim of the thesis isn't neither to determine if, how and when a possible bubble will burst, nor examining its effects on the overall economy. From the point of view of a relatively risk averse investor, namely, already the fact that a bubble may exist should be enough reason not to go for an investment in such a market. The reason why I look at a single region instead of an entire country is that plenty of past housing bubbles began to arise in single parts of lands and then eventually expanded to the whole country or even to a whole continent like it happened in the case of the US in 2007. House price dynamics are a local phenomenon, and national-level data conceal crucial economic differences among cities (Himmelberg et al., 2005). This thesis refers to residential properties and not to commercial properties such as office buildings, industrial, retail or restaurants. However, I'm going to put prices of existing properties and new properties together since new buildings only account for a little part in this market (Sparber, 2014).
House price development in Berlin
Berlin, Germany's capital since 1990 with 3.5 million inhabitants, was a divided city between 1961 and 1989. Western Berlin was considered as an island in the centre of the soviet orient bloc at this time. In 1989, though, the Berlin Wall fell and under euphoric circumstances of the reunification the year after, it was thought that the reborn demand of Eastern Berlin citizens would have created a huge upswing in real estate. This was accompanied with a boom of construction and huge investments in housing supported by consistent government incentives. This forecast, however, turned out to be wrong. The economic situation did not contribute positively and the optimism definitely disappeared. The absorption costs of the ex eastern Berlin inhabitants who worked for parastatal firms that vanished over night were enormous. The damaged economy of eastern Berlin was not able to offer sufficient support at those neo- occidental citizens and without the creation of new jobs, they simply abandoned Berlin in large part and went to other German or European cities, that did offer more job opportunities. Thousands of properties now being vacant lead to a price collapse - between 1994 and 2004 prices of Berlin real estate lost 30 %. The economic policy of Berlin took 15 years to manage the issue, to provide new jobs and to stop the emigration (Eichholtz and Lindenthal, 2011). In the mean while, property prices in the rest of Europe continued to rise in this time period. Exactly this has to be seen as the big peculiarity (and opportunity) of Berlin, because prices - even though they have been rising for the last approximately 7 years, are still low compared to other towns. Today the city counts to most attractive investment areas for residential real estate in Europe. The city today has got a young population and its growing impact as a European media and technology hub, has makes it to a hotspot ( Hage et al., 2014). So, for instance, prices for similar objects are on average 30% lower than in Munchen currently. This gap gets even higher compared to any other capital city in Western Europe: 60 - 80 % (Globalimmobili). On average, a 90 square meter apartment actually costs 139.500 euros in standard areas and 184.500 euros in preferred/ luxury areas. Prices of apartments rose to 73 % since January 2007, which comes almost up to 10 % per year. In Hamburg and Munchen this rates were 7.3 % and 5.6 % respectively (Baake et al., 2013).
Worth mentioning is that this percentage is not inflation adjusted. However, since inflation was relatively low during the period of 2007 - 2013 (on average 2% yearly) in Berlin, there is to infer that depreciation of money is not the reason for the heavy price increase in house prices (Statistik Berlin - Brandenburg, 2014). Anyways it is to say that this cycle is likely one of the least documented house price developments (Eichholtz and Lindenthal, 2011). Because prices stagnated for a long time in Germany, regions simply had no incentives to plot their data (Kholodilin and Mense, 2012).
The market has attracted different kinds of investors. The home ownership rate in Berlin is 20 % only. Even if there is an upward tendency, this rate counts to the lowest in industrialized nations (Globalimmobili). Experts say the market is more awake than ever - 40% of all the real estate purchases in big German towns were made in Berlin and 47 % of all the transaction volume accounts for the Germany's capital (Rossbac H. 2014).
Anyways, such dramatic price increases are often hard to explain, reliable media all over the world and names like the Germany's finance minister are talking about the possible existence of a real estate bubble. In this point, though, opinions strongly differ even among experts. Some are talking about no risk at all, others say there are some risks in certain urban areas. Yet the European Central Bank, for instance, thinks there is an overvaluation of 25 % in congested areas of Europe. Jens Weidmann, Chairman of the German central Bank, declares he sees a risk of a real estate bubble in Germany. Wolfgang Schäuble, the federal finance minister of Germany, speaks about dangerous signs in regard to real estate prices in the country. The international monetary fund, instead, indicated a rash of countries with overestimated property prices, but did not mention Germany (Hagen, 2014). When it comes to Berlin itself, „DIW Berlin“ (German Institute for Economic Research) declares there is no bubble right now (Kholodilin and Deger, 2013).
Definition of bubble and structure
Either way, in order to properly analyse the probability of a bubble existence in Berlin, one has to assume a certain definition of a real estate bubble: A strong short-term upward trend in prices which lies above the fundamental value of the asset. The price increase can, instead, rather be explained by psychological effects. This price development is then followed by a drastic price drop, since the price was build on an unsustainable basis (Shiller and Case, 2004).
The length of a bubble usually lasts between one and four and a half years (Kholodilin, 2011). The IMF World Economic Outlook (2003) talks about approximately five years. Even though this definition is considered legitimately, there is no agreement among economists on what precisely defines a bubble (neither in house prices, nor in other assets) (Lyons, 2013). Also, a clear and standardized definition of fundamental value is not available (Sjo ling, 2012). There are various options to assess the fundamental value of a real estate property. An often used possibility is to analyse the price to rent- ratio or the price to (per capita) income. These metrics, though, represent some weaknesses: They only consider one single factor since rent indicates (in part) the return on the investment and income shows how affordable the investment is. Secondly, the absence of interest rates in such an analysis can lead to false conclusions (Hott and Jokipii, 2012).
Another way is to calculate the discounted cashflow, but here may occur a set of barriers too: First, the difficulty of estimating the returns received over time, which in the case of residential real estate is the rent. In addition, the uncertainty of assessing the terminal value of the property is an issue. Last but not least, there is the problem of deciding upon the discount rates (Stiglitz, 1990).
In the real estate context, fundamentals can also be based on a regression of actual prices on a set of demand and/ or supply variables (Nneji et al., 2013).
This analysis is done by the latter option. In the case of the real estate market in Berlin, an increase in demand has been registered. At the same time, supply of housing in general is slow to react to increases in demand since it takes a long time to build a house, and in highly developed areas like Berlin there is a shortage of land availability as well. For instance, between 2005 and 2011 the number of private households grew at 14.500 per year while the housing stock grew at 3.500 new buildings per year only. This phenomenon is not expected to alter in the future (Kholodilin and Deger, 2013). This undersupply provides compelling rationale for price increases in real estate (Dolphin and Griffith, 2011).
So, to find out if this strong price increase is caused by determinants that fortify a housing bubble, I dig deeper at the demand side since real estate prices get more sensitive to demand factors if housing supply is relatively inelastic (Himmelberg et al., 2005). In order to do this, I'm analysing different data of Berlin and also of Germany in general and look at their correlation with the price development of Berlin's housing market between 2007 and 2013. I analyse the possible correlation between the upswing in prices and several factors which determine demand. To these determinants count:
Income/ economic growth - If income rises, demand for buying a residential property risis.
Interest rates/ monetary policy - If interest rates get lower, demand for buying a residential property rises.
Rent prices - If rent prices rise, demand for buying a residential property rises.
Access to credit - If access to credit gets weakened, for buying a residential property rises.
Substitution goods - If substitution goods become less attractive, demand for buying a residential property rises.
Demography trends - If population growths, demand for buying a residential property rises.
Expectations of the future price development - If expectations of a future price increase rise, demand for housing rises.
In the following my work consists of firstly proving by existing literature the upper assumptions and secondly by investigating how these determinants behave in the residential real estate market in Berlin. Then, in case there turns out that a single determinant did not contribute to the price increase because of no correlation, this in turn implies that the correlation between other determinants and the price increase in properties must be stronger.
All of the examined determinants do count to fundamental factors, except the speculative part that counts to the factor of expectations.
Analysis
Credit supply
Literature review
Credit quite always plays a central role in terms of bubbles. Through credit, investors get access to their future income and this is what really can detach prices from fundamentals (Kindleberger, 2011). However, if access to credit is constrained, real estate prices get highly responsive to fundamentals. Due to indivisibility constraints and the magnitude of the investment relative to disposable income, buying a property is amongst other investment oportunities most likely to be affected by severe lending criteria. Relaxation of such lending constraints, then, affects the price of houses. For instance, Stein (1996), or Ortalo-MagnÈ and Rady (2005) introduce theories where this phenomenon occurs (Favara and Imbs, 2010). Many housing bubbles in the past were fuelled by easily accessible credit. In the US, for example, credit standards did actually play the most important role regarding the housing bubble in 2007 (John V Duca et al., 2011), because it can lead to a kind of vicious cycle: Rising house prices improve the value of the mortgage’s collateral so that the asset position of banks get better. As a result, their ability to lend further rises (Taylor A., 2014).
In this analysis the credit supply is mainly measured by the loan to value ratio, or rather the ratio between the mortgage amount and the value of the property. In other words, how heavily the acquisition of a house is leveraged. The higher the leverage a bank allows for its clients to invest in residential property, the more unstable and unnaturally its demand gets built (Sparber, 2014).
Relevant Data
I use data from Germany instead of Berlin since relevant data for the city itself is not available and lending criteria for private households do not alter from region to region either way.
German banks, do act conservatively in regard to lending conditions. Banks go through a rigorous assessment of the buyer's/ borrower's creditworthiness and often require an equity portion of 30% (Kholodilin, 2013). Amongst others, a reason for this stance is the adaption to Basel III (Deutsche Hypothekenbank, 2013). Currently the average loan to value ratio accounts for 77,7 %, whereas it amounted to 80 % in 2009. Thus the own capital contribution slightly increased from 20 % to 22,3 % (Frühauf, 2014). The number of granted mortgages for private households remained the same during our relevant period. The ratio between them and the GDP even went down. According to this, there is no sign of any explosive lending (Kholodilin et al., 2013). In fact, the explanatory contribution of credit growth weighs approximately 7 %, which a quantitative study of Kholodilin and Dreger (2011) shows. Low interest rates and a high supply of liquidity through central banks provide incentives for banks to seek investments with higher returns. German banks, however, do not seek such a strategy at the financial markets (Focus, 2013).
Furthermore, the German Financial Stability Committee (FSC) did not establish any kind of self- propelled spiral of unsustainable price increases, higher debt and an easing of lending criteria. Amongst others, financial innovations such as securitizations and high yielding structured mortgage bonds, which empirically contributed to excessive lending, are on the fringes in Germany (Kholodilin and Dreger, 2013). In addition, the presence of German shadow banking is very low on an international comparison because of of legal frame conditions, so that they do not represent a noteworthy impact on the system (Focus, 2013). Lastly the composition of Berlin real estate investors is worth mentioning in regard to this issue: The percentage of foreign investors in Berlin is really high with 39 %, many coming from southern Europe like Italy, Greece or Spain. They, in turn, tend to be wealthier than the average German investor (Faz,2014). So, finally access to credit seems to be tighten due to overall severe lending criteria in the German banking system.
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