The hidden potential of cognitive biases to destroy economic welfare : a study of cognitive biases and their connection to economic bubbles

Josef Springl

Bachelor Thesis

Economics and Business, Business Studies Faculty of Economics and Business

Supervisor:

Rob van Hemert

The hidden Potential of

Cognitive Biases to

destroy Economic Welfare

A study of cognitive biases and their connection

to economic bubbles

Statement of Originality

This document is written by the student Josef Springl, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Abstract

Despite of the potential, economic bubbles have to destroy economic welfare, the

causes of economic bubbles have not been fully established yet. Current discussions and

frameworks on the emergence of economic bubbles leave out to a large extent the

involvement of human behavior. As human behavior is subject to cognitive biases, the

relationship of cognitive biases with the emergence of economic bubbles needs to be

manifested in the literature. This research therefore uses overoptimism and

overconfidence as the two most robust cognitive biases and analyses their presence

among stakeholders in the last two economic bubbles, the dot.com bubble and the US

housing bubble. The findings give rise to the assumption that overoptimism was

prevalent among stakeholders during the two bubbles and hence, play a role in the

emergence of economic bubbles. Overconfidence is likely to play a role in the emergence

of economic bubbles as well but needs further scrutiny. These findings may shed more

light on the underlying drivers of economic bubbles and strengthen the importance of

human behavior in the emergence of economic bubbles.

Table of Contents

1. Introduction

2. Literature review of relevant components of economic bubbles

2.1 Definition, characteristics and consequences of economic bubbles

5

2.2 Economic bubbles in historic context………...….6

2.3 Causes of economic bubbles……….……7

2.3.1 Governmental approach to economic bubbles

7

2.3.2 Behavioral approach to economic bubbles………..…8

3. Conceptual framework

12

4. Research Design

5. Analysis of the dot.com bubble

5.1 Introduction of the dot.com bubble

17

5.2 Non-behavioral aspects of the dot.com bubble………18

5.3 Behavioral aspects of the dot.com bubble………..………19

5.3.1 Overoptimism during the dot.com bubble...19

5.3.2 Overconfidence during the dot.com bubble……….…………25

6. Analysis of the housing bubble 2006

27

6.1 Introduction of the housing bubble 2006………27

6.2 Non-behavioral aspects of the housing bubble 2006

28

6.3 Behavioral aspects of housing bubble

30

6.3.1 Overoptimism during the housing bubble……….………30

6.3.2 Overconfidence during the housing bubble

36

7. Conclusion

Acknowledgement

1. Introduction

In recent decades, the emergence of economic bubbles drew much attention among economic scholars, policy makers and ordinary people who have been affected by them.

Economic bubbles involve the principle of trading assets which have prices that strongly deviate from its intrinsic value (Diba & Grossman, 1988). The recent increased attention to bubbles can be contributed to the harmful effects they can have on society. According to economists, economic bubbles cause a misallocation of resources, destroy large amounts of wealth and cause continuing economic malaise (Roubini, 2006). The most recent economic bubble, the US housing bubble, triggered the financial crisis in 2008 that still has negative repercussions on society.

Despite the importance of the topic, there is little consensus among scholars about the causes of economic bubbles and ways to prevent them from occurring (Girdzijauskas, Štreimikiene, Čepinskis, Moskaliova, Jurkonyte & Mackevičius, 2009).

On the one hand, some scholars argue that underlying rational market conditions, such as increased money supply and government interventions, are the chief culprits for forming bubbles (Camerer, 1989). On the other hand, some scholars name irrational behavior of individuals as possible reasons for the emergence of economic bubbles. Such irrational behavior can grow its roots from various cognitive biases that individuals exhibit (Daniel & Titman, 1999). However due to the complex nature of bubbles and the relatively new field of behavioral economics (focusing on the behavioral aspect of economic decisions making) the behavioral approach in explaining the emergence of economic bubbles is not yet properly manifested in the literature. The complexity of economic bubbles and the lack of

manifestation of behavioral aspects in the conceptual framework of the emergence of economic bubbles lead to the following question:

To what extent can cognitive biases affect the emergence of economic bubbles as displayed in the dot.com bubble in the 1990s and the recent US housing bubble in 2006?

This thesis aims to shed light on the complex issue of economic bubbles by developing a solid conceptual framework which explains the emergence of economic bubbles from a behavioral perspective. By adding the aspect of cognitive biases to the conceptual framework, stakeholders gain a more holistic view on the topic which may help to prevent future bubbles.

2. Literature review of relevant components of economic bubbles

The following paragraphs will give a summary of the existing literature regarding economic bubbles, its interplay with the concept of rational decision making and eventually reveal the existing literature gap, briefly outlined in introduction.

2.1 Definition, characteristics and consequences of economic bubbles

To understand the different facets, attributes and implications of economic bubbles, it is crucial to first develop a profound knowledge base on economic bubbles. Economic bubbles, sometimes referred to as asset bubbles, speculative bubbles, market bubble and price bubble incorporate the same underlying principle. The price for which the asset is traded in the marketplace deviates from its intrinsic value (Diba & Grossman, 1988). The intrinsic value of an asset, stock or any other commodity is derived from

fundamental analysis without reference to its market value. The fundamental analysis is conducted via asset pricing models stating that today’s price of an asset should equal the expected value of the asset of a stochastic discount factor and the payoff of the asset one period ahead (Cochrane, 2009). The expected value of an asset can be derived from its expected future cash flow and also from its perceived future potential of being valuable. Furthermore, economic bubbles is a commonly used term when referring to the notion of economic cycles, which are characterized by rapid expansion followed by a contraction (Barlevy, 2007).

Characteristics of bubbles are therefore, a strong rise in assets prices in a relatively short period of time, followed by a strong price correction (commonly referred to as bursting of the bubble) (Jiménez, 2011). Additionally, a significant concurrent inflow and eventually outflow of money to generate and respectively burst the bubble, is needed (O'Hara, 2008).

The consequences of economic bubbles are multifaceted. Economic bubbles can lead to a reduction of social welfare and impose an ongoing economic malaise on societies (Roubini, 2006). According to Grossman and Yanagawa, bubbles impede the growth of the economy after the bubble appears (1992). That is due to bubbles attracting capital which could have been allocated more efficiently to other assets. Furthermore, bubbles can result in the redistribution of wealth, potentially adversely affecting the middle class (Jiménez, 2011); the recent financial crisis (triggered by the US housing bubble) is a good example of this phenomenon. Middle class citizens increased their debt by almost 50 per cent compared to the ruling elite (Jiménez, 2011). Middle class citizens closed mortgage contracts in order to finance their homes and once the housing bubble bursted, were left with increased amounts of debt. Despite having mostly negative aspects, bubbles can bring positive contributions to society. Rapid

economic sector expansions, despite being unsustainable and short lived, encourage developments of ventures which society can benefit from (Jiménez, 2011). The dot.com bubble (explained in depth in section 4) promoted the proliferation of the internet to virtually all countries. It is debatable whether such proliferation would have occurred in the long run regardless of the bubble but it is undeniable that the bubble helped to accumulate excessive capital needed for such venture (Jiménez, 2011).

2.2 Economic bubbles in historic context

In order to acquire a profound knowledge on economic bubbles, it is important to highlight the difficulty of identifying bubbles and then put them in historic context. One key obstacle in the

abovementioned definition of bubbles is, that bubbles can only be detected in retrospect (Bhattacharya & Yu, 2008). It is scientifically unsound to prove the existence of a bubble while it is actually occurring. The core problem in this dilemma is determining whether an economic cycle can be attributed to

unjustifiable price increases of the underlying assets, or to the natural cycle of technological development (Brenner, 2003). Asset price increases can be due to the heightened expected future value potential of an asset, which is inherently difficult to foresee. Technological development is cited by most economists as the main driver for economic expansion and increased welfare (Brenner, 2003). The dot.com bubble, explained in detail in Chapter 4, is allegory for this identification dilemma. People assumed, due to the emergence of new technologies, predominantly the internet, hikes in stock prices of technology companies were justified and represented the new area of development. The dot.com bubble and other major occurrences of bubbles can only be scientifically proven with the help of hindsight.

The first uniformly agreed on economic bubble was the “Tulip Mania”, which took place in Holland around 1600 to 1637. It involved the trading of tulips, imported to Amsterdam, for horrendous amounts of money. At its peak, one single Tulip changed hands for 6000 Florins, while the average annual salary at the time was 150 Florins (Jiménez, 2011). By putting this in equivalent $US prices of today, one single Tulip could cost up to $1.8 million. In 1637, people realized how overvalued tulips had become. People sold off their tulips rapidly, by the end of the year one tulip was worth the same as an onion.

Another significant bubble happened in Britain around 1720 and centered on the South Sea Company. It had maintained a strong market position in trading goods around the globe and had strong ties to the British government, therefore many people perceived the South Sea Company as a perfect company to hold shares in. Influenced by positive announcements from both the company and the government about the future importance of the South Sea Company, its stock price rose from 130 pounds

to a 1000 pounds within a few months (Jiménez, 2011). As in the “Tulip Mania” the realization of the overvalued commodity kicked in and people sold off their shares which led to a collapse in price.

Further prominent historic bubbles are the “Railway Mania” in Britain in the 1840s, the Stock Market bubble in the United States in the 1920s, the asset price bubble in Japan in the 1980s, the dot.com bubble in the 1990s and the recent real estate bubble 2006 leading to the financial crisis in 2008. This historic context of bubbles shows that they can occur everywhere and manifest in multivariate different contexts. Its characteristics can be reflected in a variety of assets and commodities, ranging from tulips to stocks to real estate and others. (Jiménez, 2011).

2.3 Causes of economic bubbles

Whilst the definition of economic bubbles and its presence in history is mostly agreed on among scholars, what actually drives such rapid expansion, is highly disputed. The two main opposing views are the governmental approach and the behavioral approach in explaining the emergence of economic bubbles. The next section explains the emergence of economic bubbles first from a governmental approach perspective.

2.3.1 Governmental approach to economic bubbles

As mentioned briefly in the introduction, scholars argue that economic and political decisions undertaken by government, affect the emergence of bubbles. The embodiment of the governmental approach in explaining the creation of economic bubbles, is the economist Douglas French (classical-liberal economist). According to Douglas French, the main culprit for creating economic bubbles are governments (French, 1992). Governments print money and increase the money supply to stimulate growth. Due to this action, interest falls below its natural rate and entices entrepreneurs and investors to invest in ways they would otherwise not. Additionally, yields on bonds are low, making investment in government bonds an unprofitable option. Thus, stakeholders seek investment in higher order goods e.g. factories, machineries, commodities (French, 1992). The increased investment demand in higher order goods lead to an increase in higher order goods prices.

Increased money supply initiated by the government is also the focal point of the monetary overinvestment theories developed by Joseph Schumpeter (1934) and Friedrich August von Hayek (1976). According to Schumpeter and Hayek, the suitable balance between actual amount of investment and desirable amount of investment can be distorted (1934). Reasons for this are the low interest rates caused by surges in available capital; overinvestment caused by private savings or enterprise

investments into capital good industries are the consequence and have the potential to start an economic bubble (Schumpeter, 1934). Kindleberger, also reaches these conclusion as increased money supply makes hyperbolic investments into assets more likely (2000).

The governmental approach in explaining the bubble phenomenon, once ubiquitous draws criticism recently as it does not incorporate the effect of human behavior, motives and abilities on the emergence of bubbles. To investigate this further, the next sections describe the behavioral approach to economic bubbles.

2.3.2 Behavioral approach to economic bubbles

As mentioned, the governmental approach in explaining bubbles is disputed by the behavioral and psychological approaches. At the forefront is the Keynesian perspective on economic bubbles, coined by the early 19th economist John Maynard Keynes. This perspective challenges the assumption that recessions and depressions are unavoidable and that governments can only try to mitigate fluctuations in the business cycle. The root of bubbles is attributed to the behavior (predominantly human emotions) of all stakeholders involved (Akerlof & Shiller, 2010). Human behavior, affecting economic decision making of individuals and institutions is split up between rational or irrational aspects. A few decades ago, economic agents in theoretical macroeconomic and financial models were designated with a label of being rational value maximizing individuals (De Bondt & Thaler, 1994). In the financial industry, this notion is embedded in the Efficient Market Hypothesis (EMH), stating that asset prices fully reflect all available information (Fama, 1998). Eugene Fama, developer of the EMH, argues with his theory that stocks only trade at their fair value, making it impossible to sell stocks for inflated prices (Fama, 1998). Due to these market mechanisms irrational and speculative behavior of investors should not be possible.

With the emergence of behavioral economics however, arguing that behavioral, psychological and cognitive factors affect the economic decisions of individuals and institutions, the perspective of irrationality gains more and more acceptance among scholars. Most prominent is the theory of bounded rationality, stating that rationality of individuals is limited by their cognitive abilities, the information available and the finite amount of time they have to make decisions (Kahneman, 2003). In order to make decisions, individuals resort to reasoning shortcuts (heuristics) to make decisions, which leads to

suboptimal decision making. Suboptimal decision making can result as heuristics, apart from being often ill conceived, are also often riddled with irrationality. For example, heuristics are prone to the anchoring

effect, a human tendency to base its judgement heavily on initial information acquired on a subject and use this information for further decision making (Tversky & Kahneman, 1974).

The second well established component explaining irrational human behavior is cognitive biases which can account for nonoptimal decision making among individuals (Kahneman, 2003). At its core is the individual's creation of their own subjective social reality (Bless, Fiedler & Strack, 2004). Individuals act according to their own reality, which can be biased and therefore act irrational. Most consistent, prevalent, and robust biases documented in psychology and behavioral economics are the concepts of overconfidence and overoptimism (Van den Steen, 2004).

The term overconfidence, which will be referred to throughout this paper, is encompassed by three distinct phenomena: overestimation, overplacement and overprecision (Merkle, 2011).

Overestimation is about overstating their absolute ability or performance in a domain. Secondly, overplacement or “better than average effect” describes the tendency of people to assess themselves above average in many domains. Finally, overprecision is observed when people are asked to specify ranges in which an unknown value will fall with a certain probability. To put it into a nutshell,

overconfidence is miscalibration of subjective probability. This miscalibration comes partially from the illusion of knowledge. Illusion of knowledge brings about a tendency for people to believe that the accuracy of their forecasts increases with more information (Peterson & Pitz, 1988). Probabilities of outcomes are however not positively influenced by more information, only the perception of your ability to determine probabilities is. Another decisive contributor to overconfidence is the self-attribution bias (Daniel, Hirshleifer & Subrahmanyam, 1998). Success will be attributed to our internal characteristics and adverse events to external factors, fueling the perception of confidence. In the financial industry,

overconfidence in investors behavior and its correlation with excessive trading volume is well established (Odean, 1998). Overconfident investors form judgments about the value of a stock that put excessive weight on their own views and insufficient weight on the views of other investors (as reflected in the share price) (Daniel, & Hirshleifer, 2015). As a consequence, overconfident investors expect high profits from trading on their opinions and engage inevitably in more trading (Daniel, & Hirshleifer, 2015). Furthermore the abnormal high trading volume during economic bubbles can be attributed to the life cycle of a bubble. At the initial stage of the bubble, when asset prices are ‘normal’, also usual trading volume persists. However as asset prices increases during the middle stage of a bubble’s life cycle, the past price increases start to be noticed by more investors who then engage in speculative or feedback trading (Scherbina, 2013). The last instance of high trading is the time most investors realize that assets are overvalued and therefore try to sell the assets. When the selloff of assets reduces the price drastically, trading volume also stalls as investors then rather hold on to the assets to avoid certain losses (Scherbina, 2013).

Overoptimism, the second most robust bias documented, deals with the notion of what will happen to stakeholders in the near or long future (Sharot, 2011). The bias states that people consistently overestimate the likelihood of positive events and understate the likelihood of negative events (Sharot, 2011). Most people underrate for example their chances of being affected by adverse circumstances (car accident, cancer etc.). Overoptimism bias can be therefore defined as the difference between a person's expectation on a situation and the consequent outcome of the situation (Sharot, 2011). One aspect of overoptimism is the comparative optimism, inducing people to believe only themselves are likely to experience favorable events. It also incorporates unrealistic optimism, which is rooted in the firm belief that the future will be favorable for us. This optimism translates for example into the belief that the stock market or housing market will continue to rise. In practice, optimistic investors assess the the future cash flow potential of assets too favorably and create additional demand for these assets. As a consequence, the increased price cause by the heightened demand does not reflect the underlying fundamental value of the assets (Ofek & Richardson, 2003). Price distortions are in particular adverse once many stakeholders in a society share the same optimistic belief on an assets. Optimistic momentum among stakeholders can arise and induce other stakeholders to share the same optimistic beliefs and act accordingly, fueling the

economic bubble (Antoniou, Doukas & Subrahmanyam, 2013).

In economic bubble literature, overconfidence and overoptimism plays a role in the emergence of a bubble and are anchored in three generic theories.

Firstly, the greater fool theory, stating that investors buy overvalued assets on purpose as they are sure they find “greater fools” they can sell the asset to for an even higher price (Ross, 1995). To have a cumulative effect on markets, enough investors must be overconfident about their pricing acumen, believing that it is better than others (Levine & Zajac, 2007). Due to this belief, investors engage in trading assets more frequently to take full advantage of their perceived superiority. Underlying to this notion is that investors believe that not enough other participants realize the overpriced assets and they can sell the commodity for a premium. Self-serving belief bias exacerbates the effect as people assess themselves to be skilled above average (Levine & Zajac, 2007). The notion of superiority and self-serving bias are consolidated in the greater fool theory and are therefore connected to overconfidence among investors.

Secondly, extrapolation theory, revolving around unjustifiable extrapolation of past returns of stocks into future predictions of stock performances (Ooi, Webb & Zhou, 2007). Extrapolation theory is closely linked to the representativeness heuristic, which describes the notion of investor extrapolating past return and growth too much into the future (Tversky & Kahneman, 1983). Investors are overly optimistic that past stock trends will prevail in the future. At the core of both theories is the intent of investors to maintain a profitable portfolio of stocks and therefore will engage in overbidding and over commitment.

In the case of underperforming stocks, investors tend to hold on to them for too long and extrapolate the inverse of the past stock trend into the future, betting on the idea that past losers will be future winners (Jegadeesh & Titman, 1993). Given this, a contrarian investment strategy (buying past losers and selling past winners) to achieve abnormal returns is a well-established strategy in the financial industry. Given the extrapolation of past results into the future and the representative heuristic, both incorporated by the extrapolation theory, the theory can be linked to overoptimism among investors.

Thirdly, the theory of stories, developed by Shiller and Akerlof is manifested in the literature to have impact on the emergence of economic bubbles. According to both scholars, the human mind (brain) seems to be organized around narratives (Akerlof & Shiller, 2010). Underlying to their propositions is that humans tend to base their thinking, especially thinking that motivates people and excites them, in terms of stories. These stories have a contagion effect and can create a collective consciousness, that makes whole nations or groups of investors behave in the same way (Akerlof & Shiller, 2010). When certain stories revolve around the prosperous future outlook of the economy or assets, a so called “confidence multiplier" emerges and affects the economy just like an ordinary consumption multiplier. This enables speculative bubbles, feeding on the optimism, to emerge (Akerlof & Shiller, 2010). This view is closely aligned to the theory of irrational exuberance, stating that unsustainable investors’ enthusiasm is the main driver for asset prices to rise (Schiller, 2000). Governments can play a decisive role as their policy announcements and general statements on the economic situation can create powerful stories (Thompson & Hickson, 2006). Government announcements are widely perceived to be true and therefore serve as building block of contagious stories and enthusiasm among stakeholders. Given the building blocks of the theory of stories, it becomes evident that this theory can be linked to overoptimism among all stakeholders.

In explicit regard to normal households, the interplay between overoptimism and representative heuristics is prevalent. Households can be overoptimistic about the future economic situation for example and engage in activities, which would be adverse if such positive economic trend would not unfold. In order to judge the representativeness of their situation, they focus too much on the similarity with comparable situations of other persons or historical times (Tversky & Kahneman, 1974). Such similarity heuristic can propel households to engage in activities fueling economic bubbles if their decisions are ill advised.

Given the theoretical framework on economic bubbles, it becomes evident that economic bubbles are omnipresent throughout history and can have adverse effects on society. Despite the disagreement on the causes of economic bubbles, both the governmental approach and behavioral approach proponents agree on the existence of economic bubbles. It is however necessary to mention that there is another significant yet very polarizing view on bubbles: that they do not actually exist. The rational expectations

school is in favor of this view, as according to them all market participants are rational and have perfect information on the future and make optimal decisions (Garber, 1990). Therefore an unjustifiable rise in asset prices due to irrational behavior would not occur. This theory of rational decision making is deeply imbedded in most economic models and thus very prevailing. 20 years ago, this view would have been difficult to refute and absolutely necessary to include in the further analysis. However given the recent surge in literature on irrational human behavior, with solid proofs of irrationality, the rational expectation view on bubbles is highly questionable and is therefore left out in further analysis. Furthermore, the historic context clearly shows the existence of economic bubbles (French, 1992).

The literature review on economic bubbles reveals the disagreement among scholars on what causes economic bubbles. In the subsequent chapters this paper aspires to give clarity and find answer to what extent cognitive biases play a role in the emergence of economic bubbles.

3. Conceptual framework

In order to achieve the research project's objectives, the following paragraph incorporates the conceptual framework, to indicate how ideas and insights gained from the previous literature review are organized and synthesized.

Given the aforementioned literature review, some crucial observations are obvious. The two major perspectives on bubbles seem to contradict each other. The governmental approach (referred to as “non-behavioral approach” in further analysis), with Douglas as its core advocator, state that the

emergence of economic bubbles can be attributed to various actions initiated by governments. Most prominently the government's ability to raise the money supply and serve as a trustworthy spokesperson. The behavioral approach, led by Keynes, attributes economic bubbles to human behavior. However, both sides acknowledge the other as valid contributor to the emergence, but not as the root of bubbles. Douglas admits that investor behavior plays a role in the extent and rapidness in which a bubble unfolds but the starting point is the increased money supply which then drives investors to act irrationally (French, 1992).

Keynesian theory argues that irrationality is imbedded in human behavior, no matter the government actions taken. According to Keynes human behavior drives all economic decision making. Human decision making is in turn made of rational human behavior and irrational human behavior. The notion of rational, value maximizing decision makers is embedded in most neo classical economic models; it is widely used in universities, governments and countries around the world. With the emergence of the field of behavioral economics and valuable research from Kahneman, Schiller and Ariely (to name a few), the irrational component of human behavior gains increasing weight among scholars. Most explanations for irrational human behavior are the aspects of bounded rationality and

cognitive biases. Both aspects revolve around nonoptimal decision making among agents due to cognitive limitations and biases. Cognitive biases seem to have a significant impact upon human behavior as agents create their subjective social reality and act accordingly. The most researched and established areas are the biases of overoptimism and overconfidence. These two biases seem to account for the root cause of irrational human behavior. Notably there is an interplay between overconfidence and self-attribution bias and between overoptimism and representative heuristic. Furthermore in economic bubble literature, overoptimism is explained by the extrapolation theory and the theory of stories. Overconfidence, according to economic bubble literature is expressed by the greater fool theory.

Given the theoretical framework, it becomes evident that integration of different insights (namely behavioral aspect insights) into the theory of economic bubble are needed. Therefore the main focus of this research will be on the behavioral aspects in explaining economic bubbles. The reason for focusing predominantly on the behavioral aspect of the explanation of economic bubbles is the following.

According to the governmental approach (non-behavioral approach), if irrationality is the main driver for the creation of economic bubbles, the world would experience bubbles constantly. As this is not the case they find evidence for their reasoning. However, the governmental approach argumentation which involves money supply is questionable; money supply as depicted in Figure 1 is constantly rising throughout the decades.

Figure 1. Money Supply USA 1982 - 2016

Given his argumentation, the occurrence of bubbles should then also be omnipresent. Due to this complexity it might be sensible to look at the magnitude of money supply shocks and its consequences in regards to the emergence of bubbles. As such approach is beyond the scope of this research and the clear observation that behavioral aspects play a decisive role in the construct of bubbles, we investigate these behavioral aspects further.

Given this conceptual framework, this paper defines two hypotheses which will be tested in subsequent chapters.

H1: Overoptimism plays a role in the emergence of economic bubbles H2: Overconfidence plays a role in the emergence of economic bubbles

Figure 2 puts the conceptual framework into perspective and depicts the theoretical role of overoptimism and overconfidence.

4. Research Design

The following chapter explains the research design used to investigate the two hypotheses. The research design follows a deductive approach, using literature to identify theories and ideas which will be put to the test using to two case studies. The case studies will hopefully reveal additional insights which are not covered in existing literature and new connections between disciplines can be established. The study can be defined as an exploratory study as it aspires to discover what was happening in the two crises in order to gain further insights. Scrutinizing two cases can help to improve theoretical replication.

To put this in concrete actions. Given the conceptual framework, this paper proposes two hypotheses (H1 & H2) to explain the emergence of economic bubbles. To investigate whether these hypotheses hold in the dot.com bubble and the housing crisis 2006, the analysis follows a coherent approach. For each case, a thorough explanation of the crises is given. This provides a knowledge basis to understand further complex constructs. Then each case is split up between non behavioral and behavioral aspects. As established in section two, the emergence of economic bubbles can be explained on the basis of non-behavioral and behavioral aspects. The main focus on the analysis is however on the behavioral aspects, namely overoptimism and overconfidence. In order to test for these biases the main stakeholders to scrutiny are investors and households. This deliberate focus will become justifiable after explaining the key stakeholders propelling the crises in section five. Due to the nature and geographical emergence of the two crises, this paper’s focus is on the Unites States. Both cases, although internationally unfolded, have their roots in the United States.

In order for the behavioral analysis of the crises to gain validity, it is split up in two categories to find evidence for H1 and H2. Firstly, current literature on overoptimism and overconfidence in these crises are evaluated. Secondly, economic data of US investors and US households are used to find evidence for the two biases.

In detail, to investigate overoptimism in investors, the paper uses the investor behavior project at Yale University, under direction of Professor Robert Shiller. Stock market confidence indices are derived from surveys conducted over 25 years on investors and thus are the longest-running effort to measure investor optimism and related investor attitudes. The indices encompass two different survey topics.

1) The percent of the population expecting an increase in the Dow in the coming year 2) The percent of the population expecting a rebound the next day should the market ever

drop 3% in one day.

The outcomes of the survey questions are depicted in graphs. This helps to identify overoptimism of investors during the crises. Access to the data was granted by the International Center of Finance at the

Yale School of Management, which is a strong advocate of making research data widely available to foster reproduction and the extraction of new insights to create social welfare.

Overoptimism among normal households is scrutinized with the help of the consumer sentiment index, conducted by the University of Michigan. The Index of Consumer Sentiment (ICS) seeks to find how consumers view their own financial situation, the short-term general economy and the long-term general economy. The outcome of the Consumer Sentiment Index will be mapped to the dot.com and the 2006 housing crisis. The ICS is derived from the following five questions:

X1 = "We are interested in how people are getting along financially these days. Would you say that you (and your family living there) are better off or worse off financially than you were a year ago?"

X2 = "Now looking ahead--do you think that a year from now you (and your family living there) will be better off financially, or worse off, or just about the same as now?"

X3 = "Now turning to business conditions in the country as a whole--do you think that during the next twelve months we'll have good times financially, or bad times, or what?"

X4 = "Looking ahead, which would you say is more likely--that in the country as a whole we'll have continuous good times during the next five years or so, or that we will have periods of widespread unemployment or depression, or what?"

X5 ="About the big things people buy for their homes--such as furniture, a refrigerator, stove, television, and things like that. Generally speaking, do you think now is a good or bad time for people to buy major household items?"

The Index of Consumer Sentiment (ICS), is computed by the relative scores (the percent giving favorable replies minus the percent giving unfavorable replies, plus 100) for each of the five index questions (see x1 ...x5 listed above). The sum of the five scores is divided by the 1966 base period total of 6.7558, and 2.0 are added (a constant to correct for sample design changes from the 1950s). This gives us a score we can visualize and map to the two bubbles. Data on the ICS was obtained from the University of Michigan website, which can be according to their laws be used for research purpose without written consent by the University of Michigan.

Data on overconfidence in investors is obtained by investigating trading volumes of the Dow Jones. Overconfidence in investors is correlated with the amount of shares investors’ trade on the market. This relationship, as established by prominent scholars serves as a proxy for overconfidence in investors. Data on Dow Jones trading volume was obtained by accessing the Yahoo Finance databank.

The concept of overconfidence among households is difficult to identify and test. Empirical data on questionnaires among households with the appropriate questions would be needed. This complexity makes it difficult to obtain relevant and reliable data on the topic and therefore is left out in the

It is crucial to mention that relative numbers, obtained from the ICS and the stock market confidence indices are in this analysis secondary. The relative numerical magnitude and impact of a decrease and increase for example of consumer sentiment is difficult to assess. More important is the overall trend of the index as this can indicate a prevailing momentum across stakeholders. Such positive or negative momentum can, as explained in section two drive the creation of an economic bubble.

The paper up till now provided a fundamental knowledge base regarding economic bubbles, a theoretical framework to put aspects of the emergence of bubbles into perspective and a research design outlining how subsequent chapters aim to achieve the research objectives. The paper now turns its focus towards the analysis part and aspires to find answer to the research objectives.

5. Analysis of the dot.com bubble

The following section gives a thorough analysis of the dot.com bubble. The analysis proceeds from an introduction to non-behavioral aspects to behavioral aspects of the crisis.

5.1 Introduction of the dot.com bubble

In the late 90’s the emergence of the so called new economy, in which the transition from a manufacturing-based economy to a service-based economy is encompassed, evolved. The creation of the World Wide Web at the time heralded the start of the new economy in which stock markets experienced high growths due to venture capital and initial public offering (IPO) funded companies in the internet sector. The dot.com bubble was a phenomenon situated during this times from 1997 to 2000 in which equity value in the stock market rose significantly, due to the growth from the internet sector, and then fell rapidly (Valliere & Peterson, 2004). During this time internet stock rose six fold and outperformed the S&P 500 by 482% (Fong, Lean & Wong, 2008). NASDAQ 100 Index, incorporating many technology stocks showed similar patterns during this time. A company displaying this trend in an unprecedented manner is e-commerce retailer Amazon. Amazon's stock price rose from 18$ in 1997 to over 106$ in December 1999 and subsequently ended up at a price around 15 $ in December 2001 (Valliere & Peterson, 2004). IPO and venture capital statistics show similar drastic patterns. IPOs peaked in 1999 with a number of 446 offerings and fell to 79 in 2001 (Ritter 2001). VC funds were reported in 1998 to hold 31.1 billion in investment, increasing to 107.7 billion in 2000 and ending up at 5.7 billion in 2002.

Given these observations and the view of most scholars it can be concluded that the dot.com phenomenon was an economic bubble. The tech company's market value deviated strongly from the

corresponding intrinsic market value, evaporating at the end of the bubble over 8 trillion in market value (Jiménez, 2011).

Whereas the existence of the dot.com bubble is widely established, its roots require further scrutiny. Therefore the focus shifts now to identifying the root causes of the bubble.

5.2 Non behavioral aspects of the dot.com bubble

The introduction indicates that the emergence of the new economy, with at its forefront the invention of the internet is connected to the creation of the bubble. As explained in earlier sections, it is difficult to assess whether a rise in assets prices (in this regard, stock prices) is justifiable or not. Kindleberger and Aliber (2005) name technological advancements, which the invention of the internet indisputable is, as a justification for the start of a bubble. The change of expectations about the future are at the core of the new technology introduction and make up a significant part of the initial stage of the creation of economic bubbles (Cassidy, 2002).

These increased expectations about the future, in particular expectations about new forms of employment, made possible by the internet, are incorporated in the prevalent belief of the new economy at the time. The media also played a role as they constantly broadcasted about the new economy and its endless possibilities (Jiménez, 2011).

The interplay between the emergence of a new technology and positive feedback loops initiated by the media and other stakeholders can be attributed to an increased emphasis, hence investment in technology stocks.

Furthermore government actions are named to facilitate the possibilities and likelihood of people investing in the stock market. Once household savings and financial market conditions are in place, they strengthen the conditions to develop an economic bubble (Valliere & Peterson, 2004). The time between 1998 and 2000 is characterized by stimulative low interest rate policies initiated by the FED, with its former head Alan Greenspan. In response to these policies, the additional money created in the market ended up largely in the stock market (Shiller, 2000).

Another significant interference made by the US government was the change of the US pension system, starting in 1981. Most prominently of the pension reforms is the 401(k) plan offering employees the opportunity to a tax deferred retirement account. In order to take this opportunity, employees have to allocate a portion of their retirement allowance among stocks, bonds, and money market accounts (Shiller, 2000). This prompted households to actively engage and participate in the stock market and create more demand for stocks.

As with every other economic bubble, hindsight gives clarity on whether increases in asset prices were justifiable or not. The initial increase in prices seemed justified according to the above mentioned reasons but the magnitude of increase and its subsequent crash gives rise to the behavioral aspects of the bubble which are elaborated on in the next section.

5.3 Behavioral aspects of the dot.com bubble

As established in the theoretical framework, there is the assumption that the dot.com bubble was influenced by cognitive biases, especially overoptimism and overconfidence among various stakeholders. To investigate whether there is enough evidence for H1 and H2 to be true, the next section proceeds with a detailed investigation of the two cognitive biases during the dot.com bubble.

5.3.1 Overoptimism during the dot.com bubble

One of the main proponents of the view that overoptimism played a role in the dot.com bubble is Professor Shiller. According to him, the bull market (market in which share prices are rising) in the 1990’s and the bear market (market in which share prices are falling) after 2000 are due to changes in investor optimisms in stocks (Shiller, 2000). Investors in the late 90s experienced an ongoing rise in stock market price during the prior decade and thus firmly believed that this trend will prevail in the future. The notion that stocks are the “best investment” and cannot go wrong over the long run was ingrained in investors’ perception (Shiller, 2000). Investors acknowledge the possibility of stock price declines but were overly optimistic that a swift trend reversal would take place. This belief in the resilience of the market seems to stem from a generalized feeling of optimism and reassurance, rather than rational observations (Shiller, 2000). Despite prominent examples of stock markets, not displaying such

resilience (Nikkei index in Japan is nowadays still at half its peak value of 1989). Given the rise of the US stock market since 1982, investors developed a form of intuitive optimism (for example created by looking at ever rising stock prices in newspapers) which left them oblivious to stock market situations around the world (Shiller, 2000). Given this imbalance of stock price movements, persisting for such long time, extrapolative expectations (overoptimistically extrapolating past stock trends into the future)

resulted (Redhead, 2008). Extrapolative expectations, lead to momentum (positive feedback) trading (Redhead, 2008). This positive feedback trading bid up speculative prices further, thereby enticing more investors to do the same, so that the cycle repeats again and again, yielding an amplified response to the original precipitating factors (Shiller, 2000). These findings are in line with the extrapolation theory which has been connected to the emergence of economic bubbles in section two.

The emergence of the internet strengthened the prevailing optimism among investors as they overoptimistically misvalued the future payoff potential of internet related stocks (Ofek & Richardson, 2003). Internet enabling technologies were praised to have the power to transform global and economic development but it is now clear that this was an example of investor misjudgment: investors were

irrationally over-optimistic about the prospects of the, so-called, new technology sector (Wheale & Amin, 2003). Overinvestment in this new technology sector led to investments on an unprecedented scale and far outweighed market demand (Wheale & Amin, 2003). Symbolic for investor misjudgment and

overinvestment in technology stocks are the findings of Cooper, Dimitrov and Rau (2005), stating that companies which added ‘dot.com’ or ‘dot.net’ to their names during the internet stock bubble experienced share price increases of about 74% at the time of the change (despite the same business model in place).

Overoptimism during the 90s was also notable among households. From around 1980 onwards the successful businessperson, embodying the American dream was even more socially admired than accomplished scientists or artists (Shiller, 2000). The idea that investing in stocks brings the working class on the same plateau as successful businesspersons manifested itself in society. Normal households were over optimistic about engaging in the stock market, especially about investing in computer and internet related stocks (Shiller, 2000). The end of the 90s was a time when many US households were familiar with computers and and the internet, experienced their benefits first-handedly and in

consequence, overoptimistically evaluated the future stock market prospects of both phenomena. Thus, many households entered the stock market and increased demand for new technology related stocks in the late 90s.

In order to gain more clarity and validity for the presence of overoptimism at the dot.com bubble, surveys conducted at that time which focus on this bias, are analyzed in this section.

Firstly, to focus on optimism among investors, we look into the findings of the Yale University, stock market confidence indices survey. One part of the survey is the US One year index, which displays the percent of the population expecting an increase in the Dow in the coming year. According to Figure 3 expectations about the stock market rose during the timeline of the dot.com bubble drastically till expectations peaked at 91% in August 2000, right before the bursting of the bubble. This sharp rise in expectations could be tied to the optimistic beliefs investors held about the emergence of the new technology (the internet). With the entrance of an increasing number of internet tech related companies into the US stock market, investors were overly-optimistic about the future potential of the market. This overoptimism could be rooted in, at the time prevailing stories of the new economy and golden dot.com age. Newspapers and business leaders praised the ability of the internet to transform the US economy and create economic welfare (Wheale & Amin, 2003). For example in 1995, Steve Jobs stated “I think the

Web is going to be profound in what it does to our society. The Web is going to be the defining technology, the defining social moment for computing.”

Figure 3. The percent of the population expecting an increase in the Dow in the coming year, 1989 - 2015

Source: Yale School of Management, Stock Market Confidence Indices Study by Robert Shiller

Another crucial aspect of the stock market is investors’ sentiment on the robustness of the market. Declines in the stock market are omnipresent and investors are aware of this. Investors’ perception on the markets ability to rebound from a decline is connected with the outlook investors have on the market. Whether it is an optimistic or a pessimistic outlook. Therefore the second part of the survey investigating the percent of the population expecting a rebound the next day should the market ever drop 3% in one day, is crucial. Figure 4 displays the survey’s findings and depicts a clear trend during the dot.com bubble. Investors were optimistic that, given a drop in the market, a rebound would occur swiftly. This highlights the deep trust investors had in the market and their obliviousness in regard to the looming bubble. This trust in the market among investors could been caused by stories about the soundness of the market. Alan Greenspan, Federal Reserve Board Chairman at that time said in August 1999 that the

market reflects the "judgments of millions of investors, many of whom are highly knowledgeable about the prospects for the specific companies that make up our broad stock price indexes." Various statements as the one from Alan Greenspan were made at that time from multiple influential stakeholders and give rise to the theory of stories and optimism during the dot.com bubble.

Figure 4. The percent of the population expecting a rebound the next day should the market ever drop 3% in one day, 1989 - 2015

Source: Yale School of Management, Stock Market Confidence Indices Study by Robert Shiller

Thirdly the paper investigates signs of overoptimism among households. In order to pursue this, outcomes of the Index of Consumer Sentiment are depicted. This index aspires to gauge the economic expectations of consumers and judge the consumer's level of optimism/pessimism. Given Figure 5 a clear upward trend in the ICS is visible during the build up to the dot.com bubble between 1997 and 2000. The index reached its maximum at 110 points in 1998, dropped in 10 points in the subsequent year and rose again to 110 points right before the bursting of the bubble. This illustrates the overall optimistic attitude of US households but also the volatility at the time. The economic recession which unfolded after the dot.com crash is depicted in the sharp index decline until 2004. It seems that households realized their

misplaced over optimistic beliefs in the new economy and became more cautious and skeptical about their future well-being.

Figure 5. Consumers view on their own financial situation, the short-term general economy and

the long-term general economy, ICS 1960 - 20

Source: University of Michigan, Survey of Consumers

In order for asset prices to increase and deviate from its intrinsic value, a strong influx of money is needed to inflate the bubble. As reasoned in earlier section, household’s engagement (stock

investments) in the US stock market were mounting. The higher demand for stocks boosted stock prices and inflated the bubble. The ICS also incorporates a question related to household’s investments in the stock market. The survey question is: "Do you (or any member of your family living there) have any investments in the stock market, including any publicly traded stock that is directly owned, stocks in mutual funds, stocks in any of your retirement accounts, including 401(K) s, IRAs, or Keogh accounts?"

"Considering all of your (family’s) investments in the stock market, overall about how much would your investments be worth today?" The results of this survey is aligned with the notion that there was an increased emphasis on stock market investments at the time. The current values of stock markets

investments in Figure 6 shows the influx of investments into the stock market at that time. The median of households investment in the stock market rose from around 50 000 $ in 1998 to nearly 80 000 $ at the end of 2000. This seems to support the notion that the emergence of the internet heralded for most individuals the entry into a new, flourishing economy. A compelling story most people believed in and acted accordingly. Households may have had optimistic beliefs that they also can benefit from

participating in the stock market and invested heavily. This increased demand in stocks in turn, boosted the stock prices further.

Figure 6. Consumer investments in the stock market, including any publicly traded stock that is directly owned, stocks in mutual funds and stocks in retirement accounts, 1998 - 2016

5.3.2 Overconfidence during the dot.com bubble

Overconfidence among investors during the 90s was according to prominent scholars another well-established phenomenon causing the dot.com bubble. As established earlier, overconfident investors believe more strongly in their own assessments of assets’ value than that of others. Such belief is in particular misleading in times of a bull market as a famous expression on Wall Street says: “Do not confuse brains with a bull market”. During the bull market of the 90s investors attributed much of their success to their skills and expertise and became overconfident (Redhead, 2008). According to Ofek & Richardson (2001), especially the internet stocks attracted mostly retail investors (individuals buying and selling securities for personal benefit rather than for an organization) who are prone to be overconfident about their ability to predict future stock prices. Overconfident about their stock-picking skills, investors added risky technologic stocks to their portfolio and even borrowed money to increase their shareholdings (Barber & Odean, 2001).

Overconfidence among investors during the dot.com bubble can also be identified on the basis of the greater fool theory. According to a research conducted by Fisher & Statman (2002), in December 1999 half of the investors surveyed thought the US stock market was in a bubble. Furthermore forty six per cent of respondents thought the stock market is overvalued and despite this, seventy five per cent thought “now is a good time to invest” (Fisher & Statman, 2002). This gives rise to the greater fool theory as investors despite the looming of a bubble and overvalued stocks still buy stocks in order to sell them to other investors (greater fools). Investors were therefore overconfident about their intelligence in

anticipating market movements and outwitting other investors. Shiller (2000), reaches the same conclusion as according to him, rational investors (which made up most of the investors) knew stocks were overvalued but they were overconfident that they could find greater fools they can sell stocks too.

This overconfidence in finding trading partners and the investor’s overconfidence in their ability to form stock portfolios has an effect on how much they trade on the market. As established in the theoretical framework in section 2, investor trading volumes serve as a proxy for overconfidence among investors. Observation of the Dow Jones Index trading volume (Figure 7) shows an increase in trading volume during the wake of the bubble. Despite volatile trading volume movements at that time, a clear upward trend is omnipresent. There was a threefold increase of number of shares traded from 1998 to 2000 (∼100 millions to ∼300 millions). Despite the various reasons such increase can have, investors overconfidence can according to the literature be an asserted contributor. The graph displays the likely existence of overconfidence among investors and the omnipresence of the greater fool theory.

Figure 7. Number of shares traded at Dow Jones Industrial Average, 1990 - 2016

Source: Yahoo Finance, Dow Jones Industrial Average Historical Prices

The sections up to this point give rise to the assumption that overoptimism and overconfidence play a role in creating economic bubbles. The dot.com analysis reveals that overoptimism was prevalent among households and investors. Households were overoptimistic about the future potential of new emerging technologies (computer, internet etc.) and engaged increasingly in the stock market, trying to take advantage of the new technologies. Investors not only extrapolated past ever rising stock markets trends into the future but also shared a common belief of the robustness of the market and engaged heavily in trading according to their optimistic assumptions. Therefore the analysis of the dot.com bubble finds evidence of H1 to be true.

A strong increase in the trading volume of investors also give rise to the greater fool theory and the concept of overconfidence among investors. As trading volume only serves as a proxy for

overconfidence among investors, these findings are subject to criticism as trading volume can be

influenced by many other factors. The research therefore finds only some evidence in the support for H2 and thus further research is needed to clearly specify the role of overconfidence.

In order to create a more differentiated picture of the role of overoptimsim and overconfidence in the emergence of economic bubbles, the paper investigates in the following section another recent economic bubble.

6. Analysis of the housing bubble 2006

The following section gives an analysis of the housing bubble 2006. The analysis proceeds from an introduction to non-behavioral aspects to behavioral aspects of the crisis.

6.1 Introduction of the housing bubble 2006

Commonly referred to as the housing bubble, in 2006 a real estate bubble spanning over most US states unfolded. From 1997 to 2006, US home prices rose by approximately 85 percent, adjusted for inflation, fostering the largest national housing boom in the nation’s history (Shefrin & Statman, 2011). Furthermore the cost of owning houses relative to renting them increased dramatically from 2003 to 2006, indicating the existence of a bubble, where home prices greatly exceeded their intrinsic values (Shefrin & Statman, 2011). From 2006 onwards, housing prices declined and lead to increased foreclosure rates which in turn are the root of the financial crisis taken place in 2008. In order to fully understand the housing bubble of 2006 it is crucial to see its interconnectedness with the financial crisis unfolding simultaneously. Due to the promotion of homeownership from various instances (explained in section 6.2) mortgages were commonly used to finance houses. Questionable mortgage contracts (for example no background checks & no down payments) allowed people with high risk of default on their mortgage to own a house. The financial industry in turn, saw potential in trading and using mortgages to create economic value.

With the help of questionable financial practices, these mortgages were pooled together to asset-backed securities known as collateralized debt obligations (CDO) which were divided into tranches by degree of exposure to default (The Economist, 2013). Rating agencies inadequately determined the inherent risk of these securities and investors engaged in trading such seemingly low risk and high return securities. As the housing market (contrary to common belief) declined in value, a chain reaction exposed the fragile linkages between financial products. Trust among among all counterparties in the financial system began to dissolve in 2007 and the shortage of liquidity of banks and insurers to fulfill their financial commitments they made (through CDOs and credit default swaps), was exposed. In the wake of this interplay between various stakeholders, the financial crisis reached its height in 2008, entailing disastrous consequences for the global economy.

Given this introduction it becomes clear that the reasons leading to the housing bubble are a multifold and complex construct. To investigate the roots of the crisis the paper proceeds with an in-depth analysis of the situation.

6.2 Non behavioral aspects of the housing bubble 2006

In order to identify the non-behavioral aspects of the housing bubble, it is a sensible start to look at the 2006 housing bubble and link major events, economic and political changes to it. According to the literature such exogenous “shocks” help to explain the emergence of the housing bubble. Figure 8 depicts these exogenous shocks in order to find answers for the rising house prices in the US.

Figure 8. Average Sales Prices of New Homes Sold in the USA, 1963 - 2011

Source: US Census Bureau New Sales Residential Index

The constant rise of sales prices of new homes displayed in Figure 8 can be linked to various non behavioral aspects. One of the most widely accepted reasons for the emergence of the housing bubble is deregulation.

Deregulation, depicted in Figure 8 with the Housing Urban Development Act, Tax Reform Act and Commodity Futures Modernization Act led to a situation in which multiple stakeholders acted with shortsightedness. Most deregulation promoted homeownership as the decision on whether to own a home or not shifted towards each individual. The financial prerequisites to own a home were decreased and

enabled more individuals to decide whether to own a home or not. Mortgages criteria (credit standards in U.S. mortgage lending) were reduced and formerly mandatory security checks abandoned (Shefrin & Statman, 2011). As a result people took on mortgages they could not afford in the long run and defaulted on their mortgages (yielding foreclosures), which triggered the bursting of the bubble in 2007.

Furthermore the promotion of homeownership was triggered by various events and stakeholders. The Tax Return Act for example increased investment incentives in owner-occupied housing relative to rental housing by increasing the Home Mortgage Interest Deduction (Auerbach & Slemrod, 1997). In wake of these actions, the demand for houses as well as the price for houses increased.

Deregulation also took place in the securitization market (Commodity Futures Modernization Act). Securitization revolves around the pooling of loans and issuance of securities backed by the cash flow from those loans (Levitin & Wachter, 2012). As they provided the source of financing for vast majorities of mortgages in the United States, an unregulated market gave legitimacy to financial

institutions to invent new securities in order to make profits (Levitin & Wachter, 2012). CDOs are one of their prime inventions at that time.

Another aspect used in explaining the emergence of the housing bubble are misguided monetary policies. In particular, monetary policies revolving around interest rates seem to be most decisive. Scholars argue that the Federal Reserve held interest rates too low for too long, resulting in artificially cheap mortgage credit and stoked housing demand (Levitin & Wachter, 2012). These assumptions are in line with the overinvestment theory developed by Schumpeter and Hayek. Low interests also affected the aforementioned deregulation, explicitly the banks own regulations regarding mortgages. When interests are low, the financial sector can create additional demand for mortgages best when easing credit

conditions (Schnabl & Hoffmann, 2008). Competition between mortgages issuer lead to so called “Ninja loans” (to people with No Income, No Job or Assets) (Schnabl & Hoffmann, 2008). Again, this resulted in more people pursuing homeownership and driving up house prices. Setzer & Greiber investigated the correlation between monetary actions taken by the FED and the housing crisis (2007). According to them, there is causality between the low interests (2003-2004, 1%) and the housing market developments.

As deregulation and expansion oriented monetary policies are an observable phenomenon in the historical context of the USA, it gives rise to the question whether there are additional factors accounting for the emergence of such disastrous housing bubble. To investigate this, the next section will describe the behavioral aspects of the crisis.

6.3 Behavioral aspects of housing bubble

As established in the theoretical framework, there is the assumption across scholars that the housing bubble was influenced by cognitive biases, especially overoptimism and overconfidence. To investigate whether there is enough evidence for H1 and H2 to be true, the following section investigates the behavioral aspects of the housing bubble in detail.

6.3.1 Overoptimism during the housing bubble

In retrospect of the housing crisis in 2006, most scholars mention the widespread existence of exuberant optimism among households and investors at that time. Central to this argumentation is the deep ingrained belief of ever rising house prices in the US.

Households and people aspiring to hold property focused on past ever rising household price trends (depicted in Figure 7) and perceived this to be a sound assumption, if not fact (Grosse, 2011). This over-extrapolation of past instances, initiated by representative heuristics, influenced stakeholders to be over optimistic about the future value of their home (Barberis, 2011). As this happened on a large scale, Shiller describes this phenomenon as social optimism contagion (2008). The story of the ever rising house prices was deeply ingrained in people's minds. Premiums for houses were seen as justifiable as due to the rising prices, the property could always be sold off afterwards for a profit (Shiller, 2008). This vicious circle propelled people to keep on buying for higher prices, and thus drive up the house prices even further.

Most scholars conclude therefore that the housing boom was a bubble phenomenon driven primarily by the overoptimism about the "new era" in which home prices would only rise across the globe (Kemme & Roy, 2012).

However, since most homes at that time were purchased with the help of outside financing (e.g mortgages), it seems fair to assume that people involved in the provision of the outside financing were also over optimistic about future home prices (Barberis, 2011). Therefore the focus shifts in the following paragraphs on overoptimism among investors and bankers (mortgage lenders).

Overoptimism among investors and bankers played according to proliferate scholars a major role in the emergence of the US housing bubble. One role revolves around the overoptimistic beliefs of investors and bankers that homeowners are able to repay their mortgages (Grosse, 2010). As established earlier, in the wake of the housing boom, many individuals resorted to mortgage financing (low mortgage requirements and therefore high risk of default). Professionals on the supply side of the mortgages were sure people would repay their mortgages and even if not, rising house prices would give them ample

opportunities to sell the house again. Houses were seen as tangible and lucrative investment option and investors and bankers optimistically tried to capitalize on this situation by enabling an increasing amount of individuals to realize their American dream of owning a house (Grosse, 2010). As the situation of rising house prices was omnipresent before the crash in 2007, lenders just as households

overoptimistically extrapolated past house price trends too far into the future (Barberis, 2011). These findings are aligned with the extrapolation theory, explaining the emergence of economic bubbles.

However, such extrapolation and overoptimism among lenders differs in one regard drastically from homeowners. The nature of investors and bankers profession induces them to sell securities in an excessive way in order to make profits. Such behavior does not necessarily have to be aligned with their personal beliefs about the securities and the future economic prospects. Cheng, Raina & Xiong (2012) investigated this issue by looking into the house buying behavior of middle managers in financial and mortgage related companies. Their aim was to establish whether managers only engaged in promoting homeownership for clients (thus being aware of the crisis) or truly overoptimistically believed in ever rising home prices and exposing themselves on a private level to this. The researchers find little systematic evidence that these middle managers were aware of the looming crisis. Housing transaction actually reveal that these managers excessively capitalized on the optimistic belief of home prices and bought houses themselves. This gives rise to the notion of overoptimism among investors and bankers during the housing bubble.

In order to gain more clarity and validity for the presence of overoptimism during the housing bubble, the following part investigates surveys conducted at that time, which focus on this bias. As used in section five, the CSI is analyzed in order to find evidence for overoptimism. Given the nature of the index, which displays consumer expectations and optimism, Figure 9 displays volatile movements around that time. After the recession caused by the dot.com bubble in 2002, individuals were more pessimistic about their future. In the built up to the collapse of the housing bubble in 2006, individuals exhibit a more positive outlook.

Figure 9. Consumers view on their own financial situation, the short-term general economy and the long-term general economy, ICS 1960 - 2016

Source: University of Michigan, Survey of Consumers

As the housing bubble revolves unavoidably around houses and in particular on how individuals assess the current situation to buy houses, it is essential to look into this specific aspect in more detail. One question in the consumer sentiment survey deals explicitly with this issue.

The question was: "Generally speaking, do you think now is a good time or a bad time to buy a house?” Figure 10 displays the outcome of this survey question.