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.
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).
Table of Contents
1. Introduction
1.1 Personal motivation and aim
1.2 House price development in Berlin
1.3 Definition of bubble and structure
2. Analysis
2.1 Credit supply
2.1.1 Literature review
2.1.2 Relevant Data
2.2 Demography
2.2.1 Literature review
2.2.2 Relevant Data
2.3 Income / economic growth
2.3.1 Literature Review
2.3.2 Relevant Data
2.4 Interest rates/ monetary policy
2.4.1 Literature Review
2.4.2 Relevant Data
2.5 Rent
2.5.1 Literature Review
2.5.2 Relevant Data
2.6 Substitutional goods
2.6.1 Literature Review
2.6.2 Relevant Data
2.7 Psychology/expectation
2.7.1 Literature review
2.7.2 Relevant Data
3. Result and conclusion
Objectives and Core Topics
The thesis aims to assess whether the significant increase in Berlin's residential property prices between 2007 and 2013 indicates a speculative bubble or is driven by fundamental economic factors. The research investigates demand-side determinants and their correlation with observed house price dynamics.
- Analysis of housing market demand drivers in Berlin.
- Evaluation of credit supply and lending conditions.
- Impact of demographic shifts and income growth.
- Influence of monetary policy, interest rates, and rent prices.
- Assessment of psychological factors and market expectations.
Excerpt from the Book
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 (Sjoling, 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).
Summary of Chapters
Introduction: Outlines the personal motivation, the context of the Berlin housing market, and the research aim to identify potential bubble risks.
Analysis: Provides a comprehensive investigation into seven key determinants, comparing theoretical literature with empirical data from the Berlin market.
Result and conclusion: Synthesizes the findings, suggesting that the price increase is primarily driven by fundamental factors rather than speculative bubbles, while acknowledging the limitations of data.
Keywords
Real estate, Berlin, housing bubble, demand determinants, credit supply, demography, income growth, monetary policy, interest rates, rent prices, substitutional goods, market expectations, fundamental value, property prices, speculation.
Frequently Asked Questions
What is the primary focus of this thesis?
The work examines the residential real estate market in Berlin, specifically analyzing whether the sharp price increase observed between 2007 and 2013 constitutes a speculative bubble.
What are the central thematic fields covered?
The study focuses on fundamental drivers of housing demand, including demographic trends, credit availability, economic growth, interest rate policies, rent price developments, and investor psychology.
What is the core research question?
The thesis asks whether the 73% average price increase in Berlin's housing market between 2007 and 2013 is based on speculative market behavior or is supported by fundamental economic drivers.
Which scientific method is employed?
The author uses a qualitative analysis approach, investigating relevant determinants through the synthesis of existing academic literature and empirical data related to the Berlin real estate market.
What is covered in the main body of the work?
The main body systematically analyzes seven key determinants of real estate prices, presenting both the theoretical background and the relevant data for each, to determine their impact on Berlin's market.
Which keywords characterize the work?
Key terms include Real estate, Berlin, housing bubble, demand determinants, and fundamental factors.
Why did the author choose to study Berlin instead of Germany as a whole?
The author argues that house price dynamics are local phenomena and that national-level data often mask significant economic differences between specific urban centers.
What conclusion does the author reach regarding the Berlin market?
The author concludes that there is no clear evidence of a housing bubble, arguing instead that price increases are largely justified by fundamental factors such as population growth and economic development.
What role does the "Taylor Rule" play in the analysis?
The Taylor Rule is used as a benchmark to assess whether the interest rate environment in Germany/Berlin was "too low" during the study period, which could potentially fuel a bubble.
- Arbeit zitieren
- Simon Sparber (Autor:in), 2014, Real estate market in Berlin. Is there any bubble?, München, GRIN Verlag, https://www.grin.com/document/314881
