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Behavioural Economics and Finance Online Course

Behavioural Economics and Finance

Behavioural Economics and Finance

Behavioural economics and behavioural finance are rapidly expanding fields that are continually growing in prominence. While orthodox economic models are built upon restrictive and simplifying assumptions about rational choice and efficient markets, behavioural economics offers a robust alternative using insights and evidence that rest more easily with our understanding of how real people think, choose and decide.

This insightful textbook introduces the key concepts from this rich, interdisciplinary approach to real-world decision-making.

This new edition of Behavioural Economics and Finance is a thorough extension of the first edition, including updates to the key chapters on prospect theory; heuristics and bias; time and planning; sociality and identity; bad habits; personality, moods and emotions; behavioural macroeconomics; and well-being and happiness.

It also includes a number of new chapters dedicated to the themes of incentives and motivations, behavioural public policy and emotional trading. Using pedagogical features such as chapter summaries and revision questions to enhance reader engagement, this text successfully blends economic theories with cutting-edge multidisciplinary insights.

This second edition will be indispensable to anyone interested in how behavioural economics and finance can inform our understanding of consumers’ and businesses’ decisions and choices. It will appeal especially to undergraduate and graduate students but also to academic researchers, public policy-makers and anyone interested in deepening their understanding of how economics, psychology and sociology interact in driving our everyday decision-making.

Michelle Baddeley is a behavioural economist and applied economist based at the Uni- versity of South Australia’s Institute for Choice in Sydney. She is an Honorary Professor with University College London’s Institute for Global Prosperity, Associate Researcher with the Cambridge Energy Policy Research Group and Associate Fellow with the Centre for Science and Policy, University of Cambridge. She has also worked with policy-makers across a diverse range of themes and her research brings economic insights from applied economics, behavioural economics, behavioural finance and neuroeconomics to multi- disciplinary studies.

 

Chapter 1
Introducing behavioural economics

What is behavioural economics?

With the award of the 2017 Nobel Prize in economics to behavioural economist Richard Thaler – one of the pioneers in developing behavioural public policy “nudging” – behavioural economics is very much in the news. There are, however, many misconceptions about behavioural economics, which raises the question: what is behavioural economics?

This is a question that many behavioural economists have worked on answering, for example see Hargreaves-Heap (2013) versus Thaler (2016) for some contrasting perspectives. To give a quick and simple answer: behavioural economics is a fascinating and fashionable subject, of increasing interest to policy-makers and business, as well as to a range of academic researchers and teachers.

But, because it is such a broad field, it can be difficult precisely to define. Some would argue that all economics is behavioural economics because economics is about behaviour, albeit in a restricted context. Others would define behavioural economics very narrowly as the study of observed behaviour under controlled conditions, without inferring too much about the underlying, unobservable psychological processes that generate behaviour.

Overall, the clearest way to describe it is as a subject that brings together economic insights about preferences and decision-making with broader principles of behaviour from a range of other social, behavioural and biological sciences. In this, behavioural economics relaxes economists’ standard assumptions to give models in which people decide quickly, often using simple rules of thumb rather than rigorously but robotically calculating the monetary benefits and costs of their decisions.

Behavioural economics also explores how quick thinking leads people into systematic mistakes but also explains how people can learn from their mistakes. In behavioural economic models, people look to others when making decisions and when seeking happiness. Their decisions are affected by skills and personalities and also by moods and emotions.

People aren’t necessarily good at planning systematically for future events and particularly when immediate pleasures tap into emotional and visceral influences. This means that people will be susceptible to impulsive decision-making which may be detrimental to their long-term welfare, for example smoking and eating unhealthy food. So overall, behavioural economics develops more traditional economic models to explore in more depth and detail the balancing acts that we go through every day when we choose and decide.

For the purposes of this book, behavioural economics will be defined broadly as the subject which attempts to enrich economic analyses of behavior – grounded as it is in theories about preferences, incentives, decision-making and strategy – with insights from psychology, sociology, cognitive neuroscience and evolutionary biology.

 

Behavioural economics: what’s new?

Now that we have explored some of the history of behavoural economic thought, we can turn to modern economics to explore how and why behavioural economics is different from standard approaches – specifically the dominant approach associated with neoclassical economics – which focuses on the role played by rational agents in market economies. Neo-classical economics is sometimes notorious for its focus on unrealistic behavioural assumptions about humans’ capacity for rationality.

This translates into theories that are founded on mathematical principles – reinforcing the idea that economics treats people as if they are mathematical machines. Nonetheless, economic theory has the distinct advantage that it is analytical and relatively objective. The power of behavioural economics comes in combining more realistic behavioural assumptions – which we shall introduce in this book – with some of the analytical rigour of economic theory.

Many would envisage behavioural economics and neuroeconomics as providing conceptual alternatives to standard neoclassical models which focus on a conception of people as Homo economicus – people are assumed to be clever and well-informed, decision-making is rational and systematic; and economic actions are described as the outcome of mechanical data processing.

A lot has been done to soften the standard approach, especially in microeconomic analysis, for example by recognizing the nature and implications of asymmetric information and other forms of market failure, and by introducing Bayesian models to replace models of rationality based on perfect information. These extensions can explain non-maximizing behaviour by allowing it to be constrained by uncertainty and/or affected by strategic interactions between people and firms.

Behavioural economics is another way to illuminate some of the deeper foundations of sub-optimal behaviour. The degree of divergence between behavioural economic models and standard neoclassical models does vary across behavioural economics. Some would see behavioural economics as basically consistent with standard neoclassical approaches, with some extra psychological variables embedded, for example into utility functions, to increase realism, though at some cost in terms of tractability.

For example, Camerer, Loewenstein and Rabin (2004) argue that behavioural economics

increases the explanatory power of economics by providing it with more realistic psychological foundations … [This] does not imply a wholesale rejection of the neoclassical approach … [which] provides economists with a theoretical framework that can be applied to almost any form of economic (and even noneconomic) behavior.
(Camerer, Loewenstein and Rabin 2004, p. 3).

A further complexity is that behavioural economics does draw on insights from many of the other “tribes” of economic theorists: not all “non-behavioural” economists are neoclassical economists and there are some particularly strong parallels between behavioural economics and evolutionary economics, social economics, institutional economics and heterodox economics.

In drawing on insights beyond neoclassical economics, other behavioural economists take a more radical approach and would argue that the foundations of neoclassical economics are badly flawed and need to be replaced with a more fundamentally psychological approach to analysing economic decision-making. Earl (2005) sets out some axiomatic foundations for psychological economics but emphasizes that these can be expressed “permissively” as tendencies describing what people often do, rather than as “non-negotiable axioms”.

Choices will be fickle, susceptible to random influences and context, for example with fashions and fads. Consumer and workplace behaviours may be pathological to some degree, including dysfunctional strategic decision-making and extreme behaviour including impulsive spending or obsessive-compulsive behaviour. Some may exhibit these behaviours to a large degree; others in a minor way but it will mean that our economic decisions will be affected by irrational obsessions and aversions.

Earl’s axiomatic foundations of psychological economics emphasize the importance of perception and context; the social nature of behaviour; the impacts of non-economic variables; and the importance of bounded rationality – specifically when information is too complex for human cognition. Earl’s foundations also include Herbert Simon’s concept of ‘satisficing’ (that is, finding a satisfactory solution even if it’s not the best solution); attention biases occurring when attention is not allocated optimally leading to inconsistencies; and heuristics and biases shaping perceptions and judgments.

The latter will include temporal biases, for example as seen in models of hyperbolic and quasi- hyperbolic discounting; emotions; impacts of context on decision rules; limited learning constrained by people’s preconceptions about the world. In addition, he includes pathological behaviours, for example impulsive spending; impacts on choices of personalities and attitudes, as well as simple preferences; and altruistic choices (Earl 2005).

Axiomatic foundations unify economics and psychology in psychological economics but Earl argues that economic psychology and psychological economics are different too: the former involves economists taking subjects traditionally in the psychologists’ preserve such as addiction and altruism, and analysing them using economic models and concepts.

Psychological economics comes from the other direction and involves challenging standard economic models by embedding insights from psychology to enhance understand- ing of economic decision-making, for example Frey’s (1997) broad study of motivation (Earl 2005)

 

Key insights from psychology

In taking on the essential assumptions of neoclassical economics, behavioural economists populate their models with people who are far more susceptible to social and psychological influences than Homo economicus. On this point, it is important to note that behavioural eco-nomics is not one coherent and self-contained subject – there is a spectrum of approaches to behavioural economics, reflecting the extent to which key insights from psychology, sociology, neuroscience and evolutionary biology are brought into the frame.

Some behavioural economists develop models in which the neoclassical model is “tweaked” with some socio-psychological insights – such as that people are not always selfish. Other behavoural economists focus much more strongly on the role of personality, emotions and psychological biases in economic and financial decision-making.

Whilst this book takes a broad view of which psychological insights are most relevant and interesting, nonetheless it is important to recognize that behavioural economics, economic psychology and psychological economics are not necessarily the same thing. There are many parallels between them but subtle differences too. Some behavioural economists are interested only in observable and measurable impacts on behaviour and preferences and are less interested in the underlying psychological processes.

They would argue that these underlying variables are not easily measurable and so cannot form the basis of an objective science.

How do behavioural economists bring psychology into their models? This is a difficult question to answer quickly because psychology encompasses such a large range of ideas and sub-disciplines and such a large number of tools and techniques.

The incorporation of psychology into economics is controversial. For some economists, embedding a deeper understanding of what motivates choices and decisions is an anathema because, for example, in positivist, neoclassical approaches, the focus is on objectively measurable data such as observed choices.

Earl (2005) observes that such criticisms may reflect the fact that psychology as a discipline lacks a grand unifying theory. There are many different psychological approaches but fragmentation within psychology not only discourages economists from making an investment in understanding psychological theories; it also encourages a piecemeal, ad hoc approach to embedding psycho- logical insights into economics (Earl 2005). This selective use of psychological insights in behavioural economics may undermine its credibility for some.

Behavioural psychology has had a profound influence on modern behavioural economics and helps to explain the distinction between it and economic psychology. In contrast to economic psychology, the areas of behavioural economics that are closest to mainstream economic theory adopt the methodology of behavioural psychology by focusing on observed choices and revealed preferences using experimental methods and abstracting from cognitive and emotional processes underlying decision-making.

It could be argued that this approach has in some ways been made obsolete by technology: as the sophistication and precision of neuroscientific tools and techniques has increased, the objective information available to a scientist is no longer confined to studying what people actually do (or don’t do) because it is now possible objectively to measure the physiological responses underlying observed action.

However, as for psychology more generally, the early development of new neuroscientific tools has led to the evolution of neuroeconomic analyses – observable data is no longer confined to what people do; we can also measure what is going on in their brains and nervous systems whilst they do it, as the neuroeconomic studies explored in this book will show.

 

Behavioural tools and methods

Now that we have outlined some of the key insights that behavioural economists take from economics and psychology, we can see how they also combine different methods from economics and psychology – including economists’ traditional econometric and modelling tools, alongside methods from game theory – and also experimental approaches from psychology.

All these sub-disciplines already have their own large and rich literatures and there is not the space to explore them in detail in this book alongside the enormous behavioural economics literature but a quick summary is given below, along- side some reading recommendations in Further Reading.

 

Game theory

Many areas of behavioural economics focus on strategic interactions between people and standard game theoretic tools are used as a starting point in these analyses. Putting game theory together with behavioural insights produces the large, diverse field known as behavioural game theory, surveyed comprehensively by Camerer (2003b) and partly covered here in the chapters on learning (Chapter 5) and sociality (Chapter 6).

In explaining behavioural game theory, Camerer makes a distinction between games, which are strategic situations, and game theory – which gives explanations for choices. In standard game theory, there is a divorce of theory and evidence and limited empirical evidence.

Camerer (2003) cites von Neumann and Morgenstern (1944): “the empirical background of economic science is definitely inadequate. Our knowledge of the relevant facts of economics is incomparably smaller than that commanded in physics at the time when mathematicisation of that subject was achieved”.

Camerer suggests that this gap between theory and evidence seen in standard game theoretic approaches can be remedied to an extent by the inclusion of experimental techniques. This can be achieved by starting with classical game theory – including games that incorporate private information alongside probabilistic information about others’ preferences and/or types.

Behavioural game theory can be used to test the standard economists’ hypotheses by adapting classical game theory (in which people are assumed to be self-interested maximizers, engaging strategically) to allow for additional behavioural forces, for example limits to strategic thinking, and attitudes towards others’ payoffs and learning.

If it leads to rejections of predictions of classical game theory, evidence from behavioural game theory can be interpreted in a number of ways, particularly as much of it is based on experimental evidence: violations could reflect irrationality or weaker versions of rationality (e.g. as explored by Herbert Simon in his analyses of bounded and procedural rationality); “other-regarding” preferences (e.g. for reciprocity, equity, etc.); strategic thinking and/or reputation building.

For the purposes of this book, the reader is assumed to have a basic working knowl- edge of game theory and its key concepts including Nash equilibrium, mixed strategy equilibrium, reaction functions and backward induction. For the learning chapter in par- ticular, it will be useful to know some classic games from standard introductory econom- ics, for example the prisoner’s dilemma, battle of the sexes, buyer-seller and stag-hunt games.

For those who would like to learn more about game theory to enhance their understanding of related areas of behavioural economics, some good introductions are listed in the Further Reading section.

 

Experimental economics

Empirical testing of behavioural economics models uses a range of data and some data is similar to data used in standard economic analysis. In terms of the methodological tools used by behavioural economists, there have been some innovations and data-based statistical and econometric analyses are increasingly being supplemented by experimental evidence.

In fact, some areas of behavioural economics have emerged from experimental economics. Behavioural models can explain experimental results that, for one reason or another (and there is plenty of controversy about the reasons), do not fit with simple pre- dictions from standard theory.

Vernon L. Smith pioneered the use of experiments in economics and initially used market experiments as a pedagogical device in his principles of economics lectures (Smith 2003a). Experimental methods can be integral to behavioural economics because they enable close observation of actual choices under carefully controlled conditions, thus allowing the experimenter to abstract from ordinary complicating factors. If properly constructed, experiments can allow us properly to control conditions so as to capture the real drivers of behaviour.

The main advantage of an experimental approach is it gives us new types of data to illuminate economic decision-making that will, in some circumstances, be better than the “happenstance” data of conventional economics/econometrics.

Experimental methods are also used in neuroeconomic studies particularly when the tight analytical structure of game theoretic methods can be used to complement a wide range of neuroscientific techniques (to be explored in more detail in Chapters 11 and 12). This enables the construction of neuroeconomic experiments that can be conducted quickly, efficiently and neatly to test neuroeconomic hypotheses clearly.

Experimental investigations can however be fraught with problems, as explored by Smith (1994), Binmore (1999) and others. Experimental designs must be “clean” with proper controls, clear and simple instructions and clear incentives. Results in experimental context can be conflated with impacts from methodological variables (e.g. repetition, anonymity); demographic factors (gender, age, socioeconomic group, etc.); cultural factors; game structure and/or labelling and context. Designing a clean, uncomplicated experiment is not easy to achieve and needs a lot of careful thought.

One aspect of experimental design that attracts strong views from economists is the issue of deception. Is it a methodological problem? In principle, incorporating deception into experiments conflicts with the focus in experimental economics on truthful- ness as an essential element in “clean” experiments.

On the other hand, particularly in neuroeconomic experiments where the experimental environment necessarily is highly constrained, it is often impossible to avoid some limited deception. Sanfey et al.’s (2003) fMRI study of social emotions (explored in Chapter 8) used a contrived offer algorithm in which the experimental subjects were told that they were responding to decisions from real people when in fact they were responding to offers generated by the experimenters. Sanfey et al. argued that their deception was necessary, given the “heavy logistic demands” of fMRI studies and did not affect/confound the interpretation of results.

The use of limited deception, and only where essential, is increasing in neuroeconomic studies, especially imaging studies, because the experimental context is so restricted by technical, logistical and financial considerations. Psychologists sometimes have a more flexible attitude to deception and will incorporate carefully constrained deception when necessary. It is possible that the issue of deception in experiments is a question of experimental norms rather than objective limitations from deception.

In addition to the challenge of designing a clean experiment, it is also important to recognize the limitations of experimental evidence. These limitations are likely to be less for natural and field experiments where researchers are observing real behavior in which real choices drive real-world consequences for the people being studied. DellaVigna and Malmendier’s (2004) study of gym membership, explored in Chapter 10, is an example of a natural experiment.

Aside from these types of natural/field experiments, results from experiments may suffer from hypothetical bias – experimental subjects may behave in a very different way when they know that they are not making a real-world decision. Results may have limited external validity and may not be generalizable to the world outside the lab.

This may reflect the selection of experimental subjects, especially as experimental subjects are often university students whose behaviour may not represent the behaviour of people outside an academic environment, such as a university. Results from behavioural experiments have been generalized mainly by increasing the size of payoffs.

Richer, more sophisticated, experiments do need to be designed if insights from behavioural experiments are to be applied more widely. Some experiments do have inherent external validity, including natural experiments in which people’s ordinary behaviour is already controlled by the situation in which they find themselves. In natural experiments, the experimenter is not interfering and distorting decisions.

Field experiments are used frequently in behavioural development economics – often via the adoption of randomized controlled trials incorporating techniques developed for med- ical/pharmaceutical testing. Randomised controlled trials are used to capture the impact of different “treatments” or policy interventions. They are constructed by randomly selecting some groups for an intervention.

Other groups are used as control groups. Comparing the behaviour of treatment groups and control groups enables quantification of treatment effects. There are potential ethical problems with randomized controlled trials because some groups get access to potential beneficial interventions whilst others do not. This issue is addressed in medical trials by abandoning the random allocation of people into treatment groups versus control groups as soon as strongly significant impacts from interventions are identified.

Experimental economics is also limited by problems with experimental incentive structures. In real-world situations people face complex but often very salient incentives and it can be hard for an experimenter to identify meaningful incentive structures, particularly if subjects initially motivated by intellectual curiosity, for example, are then distracted and de-motivated by (perhaps insultingly) small experimental payments.

Gneezy and Rustichini (2000a, 2000b) have explored this problem in arguing that extrinsic motivations such as money and other concrete rewards crowd out intrinsic motivations, including intellectual curiosity and a desire to be helpful. De-motivated experimental subjects can distort experimental results.

The behavioural economics literature on its own is vast and so there is not the space for a detailed account of experimental economics too. There are however already a few comprehensive accounts of experimental economics and for those interested to find out more, some readings are suggested in Further Reading.

 

The structure of Behavioural economics and Finance

Behavioural Economics and Finance provides a broad introduction to key debates and a range of behavioural principles will be explored. The literature is already enormous and is growing rapidly so it would be impossible to cover in one book all the interesting things that behavioural economists are doing.

So, the following chapters focus on aspects of behavioural economics and finance that are relatively well-established and/or have received a lot of attention. This book is sub-divided into three key sections. In the first section, we will explore a range of insights that offer behavioural alternatives to the microeconomic principles usually embraced by economists – focusing on different behavioural approaches to motivations and incentives; heuristics and bias; behavioural theories of risk, including prospect theory and its alternatives; learning; and inconsistencies in the way that people deal with time (“time inconsistency”) and addictive behaviour.

Cognitive neuroscience is bringing additional innovative insights and tools that are transforming behavioural economic analysis and so the Microeconomic Principles section will include two chapters dedicated to theoretical insights and empirical tools from neuroeconomics – an exciting new sub-discipline which combines economic theory with cutting-edge neuroscientific tools to unravel the economic, psychological and social influences on our economic decision-making.

The second section, focuses specifically on behavioural finance – starting with an outline of some key principles from behavioural finance and in particular a number of behavioural anomalies that Nobel Prize-winner Richard Thaler and others have identified specifically in the context of financial decision-making.

This section will also explore how behavioural economic theory can be applied specifically in the context of corporate finance and investment. The other behavioural finance chapters will explore how personality and emotions drive financial trading and speculation, how these factors contribute to financial instability and – to complement the chapters on neuroeconomics – how neuroscientific tools have been used specifically to test a range of assumptions about socio-psychological influences on financial decision-making, as explored in the sub-discipline of neurofinance.

The third and final section of the book will look at behavioural influences from broader perspectives and will include chapters on behavioural macroeconomics, happiness and well-being, and behavioural public policy.

 

A note on mathematics

Mathematical exposition characterizes modern economics and this is not necessarily a bad thing if mathematical and intuitive explanations complement each other. Sometimes it is easier to explain things using simple equations than dense text, and many behavioural economists have set their models out using some (often quite straightforward) mathematics. Other times it is more meaningful to express things in words than in equations – especially as the human brain is not always well built to process mathematical analysis.

Given the wide range of attitudes towards mathematical analysis, in the interests of presenting the material in a way which is engaging to as many readers as possible, the main text is written in non-mathematical language. Where it is relevant and to cater for those who prefer the simplicity of mathematical analysis, the essential principles and models are separated into chapter Appendices. The essential intuition of all models will be covered in the main text of each chapter and so readers can ignore the mathematical translations if they prefer.

 

Chapter summary

  • Behavioural economics is a wide discipline that draws on a range of other subjects from the social and natural sciences – including psychology, sociology, neuroscience and evolutionary biology.
  • Whilst it has only recently developed a critical mass within economic theory and pub- lic policy-making, behavioural economics draws on long traditions in economics – from Adam Smith and Jeremy Bentham through to John Maynard Keynes, George Katona and Hyman Minsky.
  • Behavioural economists rethink what economists usually assume about behaviour – not by assuming that behaviour is irrational, but by providing a more realistic analysis of how real people decide and choose, replacing the models associated with modern mainstream economics, which assume that people decide as if they are mathematical maximizers.
  • Behavioural economics draws on a wide range of insights from economics more generally – including ideas about strategic decision-making from game theory, in- sights from theories of learning and some themes from information economics and labour economics.

 

Revision questions

  1. How does behavioural economics differ from other areas of economics? How is it similar?
  2. How do behavioural economists’ descriptions of how people choose and decide differ from the descriptions of behaviour highlighted in mainstream economics?
  3. From the different economists introduced in this chapter, who do you think has had the most influence on modern behavioural economics and why?
  4. Can insights from behavioural economics help ordinary people to decide and choose more effectively in their everyday decision-making? If so, how and why? Illustrate with examples.

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