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Department of Economic and Financial Sciences, University of Torino and IRES Piemonte, Italy
Today the research field which overlaps economics, psychology and neuroscience seems to be very promising and one of the most growing. It gets a lot of attention by funding agencies and the media, and, although a young research field, its findings have already challenged a relevant part of the previously existing knowledge about decision making.
Although its immediate usefulness for social simulation is disputable, neuroeconomics surely is a rich source of inspiration for everyone interested in modelling human behaviour. Social simulation, in fact, always starts from individual behaviour and goes up, and sometime the starting point has neither to be realistic nor to contain any explanation. Nevertheless, the knowledge about how and why individual decisions are taken can often mean a significant improvement in the evaluation of model outcomes and in the authors' confidence about them.
But is such a field of research easily accessible by the social simulation community? The answer is, in my opinion, negative and that happens mostly because of the distance between the two communities. In order to critically read a neuroeconomic paper in fact there is the need for, at least, three kinds of knowledge which, perhaps, are not so common in the readership of this journal: they are the knowledge about neuroanatomy, brain functions and pathologies; the knowledge of the tools used in neurosciences, both from the bio-physical (e.g., knowledge about how tools like fMRI and EEG scanners work) and technical viewpoint (e.g., knowledge about statistical procedures on fMRI data for noise reduction), and on the methodological procedures adopted for conducting experiments with such tools; and, finally, the knowledge of the research agenda which determined the perspective as well as the methods.
Unfortunately there are neither simple answers to such issues nor exhaustive references. Just as a short example of the complexity at work here, consider that the research agenda of neuroeconomics is not one, but many. There is, for instance, a part of that community that starts from solid roots in the neoclassical paradigm and extends it inside the brain (see for instance Glimcher 2003). There are some who, starting from the inspiring work of Damasio (1994), focus on the role of emotions and on the somatic marker hypothesis and aim at measuring the relevance of affective processes in different economic settings. Others instead prefer to start from findings developed in behavioural sciences and they explicitly aim at opening the black box implied by the as-if principle (see for instance Rustichini 2005 and Camerer et al. 2007).
Although the contact between social simulation and neuroeconomics is difficult, that does not mean that the attempt is not worth. A good starting point for the interested reader can be represented by the two books presented below: perhaps they do not provide information for building a better social simulation, even if they both present interesting, useful and innovative results, but they surely give the intuition on how neuroeconomic research works are conducted, on the kind of knowledge developed and on the relevance of the consequences in modelling behaviour.
The two books, besides, have some other points in common. As the very largest part of neuroeconomics they adopt a behaviourist approach that is also something very useful if we want to get back to social simulation. Moreover, they both deal with an empirical pattern observed in behavioural sciences that is the presence of hyperbolic discounting in intertemporal choices that can lead to preference reversal as time passes.
The book, although presented as a guidebook to neuroeconomics, actually is more appropriately described as the presentation of an abstract scheme of interpretation of research agendas, approaches and results in neuroeconomics.
Such a scheme is the main original contribution of the book and its main components are presented in chapter 2 after a short introduction to the different waves of neuroeconomics (in chapter 1). The scheme proposed by the author outlines the basic elements of a new choice theory built upon neuroeconomic results. Its two main concepts are derived from economic theories and are the ones of "efficacy" and "effectiveness".
Chapter 3 is devoted to the investigation of the efficacy of evaluations of rewards and risks. Several different economic models for dealing with such an issue (e.g., multiattribute utility, subjective expected utility, models of discounting, etc ...) are presented with their underlying neurobiology and pathologies.
The presentation, in each paragraph in which the model of a phenomenon is presented, of sub paragraphs dedicated to the related neurobiology and pathologies is exploited throughout the book and it is a very useful and clarity-enhancing characteristic of the book.
The following chapter (chapter 4) concerns the effectiveness of evaluations. Several models, coming largely from behavioural economics, are presented (e.g., prospect theory, quality adjusted life minutes, and so forth) together with the neuroeconomic results that matter.
Chapter 5 concludes the book by presenting the research directions of neuroeconomics that seem to be the most promising and by sketching the elements needed for a discussion of the methodology followed by neuroeconomists. The author, in particular, suggests that a neuroepidemiological approach should be adopted as the methodological procedure for neuroeconomics because it allows considering appropriate methods for coping with the several levels of analysis, for population and subjects selection, and for developing experimental tests.
Furthermore, a glossary is available in the concluding part of the book and it provides the reader with an essential tool for understanding the book as well as any neuroeconomic paper.
The book is a case study application of the methodological theses presented by one of the authors in a previous book (Ross 2005). The case study concern disordered gambling and the methodological approach is based upon a revisited version of the rationality usually considered in economics. Such a rationality does not aim at explaining behaviour but just to describe it, thus embracing a strong behaviourist approach.
Authors chose to focus on the "molar" level where they deal with the pathological behaviour on focus but they do not avoid a complex and fruitful relationship with the "molecular" level where the neuroeconomic approach obviously enters the scene.
It is thus quite interesting to read how the authors have been capable of keeping together the interest for a behaviourist approach that does not aim at explaining actual behaviour with the exploitation of empirical sources of information capable of so much richness in details.
The book starts (chapter 1) by discussing the presence of addiction: the focus is on the need for an abstract pattern of behaviour that can allow some degree of generalization. Furthermore, the presence of behavioural patterns is required by an approach that claims to be behaviourist and that is enrooted in behavioural economics too.
Then, the book continues (chapter 2) by presenting reasons for investigating gambling and introducing measures for distinguishing among pathological gambling, problem gambling and disordered gambling.
The third chapter gets to the core of the book argument: considering that behavioural economics has pointed out how widespread is hyperbolic discounting, the approach adopted by authors and labelled "picoeconomics" allows to model a behaviour that mimics phenomena such as preference reversal. Picoeconomics is here, in a few words, the modelling of intertemporal choice as a subpersonal market place where equilibria are found among different interests through bargaining. Picoeconomics thus is not a new branch of economics (as the name could suggest) but a theory for modelling individual choices that extends the neoclassical homo economicus in order to capture a little bit more of empirical salience. The chapter ends by enumerating methods that humans usually adopt for self-control and for avoiding an excessive choice of short term solutions: self imposed personal rules of behaviour are the ones on which the authors focus more extensively and in fact they are the strategies on which, throughout the book, it will be developed the concept that behaviour is an equilibrium in bargaining games among subpersonal interests.
The following four chapters are the ones most interesting for the reader who is looking for empirical salience and for examples on how to link theoretical hypotheses to empirical and experimental knowledge. Chapter 4 presents behavioural and psychological contributions to the studying of disordered gambling, and chapter 5 focuses on the neuroeconomics of addiction (ranging from the neuroanatomy to the neurochemistry of addiction). Chapter 6 deals with the neuroscience of pathological gambling, and the following chapter (chapter 7) deals with results coming from clinical subjects. Chapter 8 concludes by discussing the implications of what has been presented in preceding chapters.
In conclusion, the book is strongly suggested to readers interested in modelling agents facing intertemporal choices in general and gambling in particular. But it is also suggested to everyone who is interested in possible linkages between theories about behaviour and empirical salience: the approach presented by the book can be criticized and it can appear to some social scientists as too much biased by economic theory, but the rigour and the clarity of the presentation allow understanding that such a difficult challenge can be tackled.
DAMASIO A (1994) Descartes' Error. Putnam Publishing: New York, NJ.
GLIMCHER PW (2003) Decisions, Uncertainty, and the Brain. The Science of Neuroeconomics. The MIT Press: Cambridge, MA.
ROSS D (2005) Economic Theory and Cognitive Science, Vol. 1: Microexplanation. The MIT Press: Cambridge, MA.
RUSTICHINI A (2005) Neuroeconomics: Present and future. Games and Economic Behavior 52, 201-212.
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© Copyright Journal of Artificial Societies and Social Simulation, 2009