This is a book about ‘unintended consequences of human action’ and the mecha- nisms that bring about these consequences. It investigates the explanatory role of the models that characterise institutions and macro-social structures as unintended consequences of human action.
Many economists argue that certain institutions and/or social structures, such as money, language, rules of the road, fairness, segregated city patterns and locali- sation, are unintended consequences of human action. Similar ideas can be found in other disciplines, such as in philosophy of language (e.g. Lewis 1969), political philosophy (e.g. Nozick 1974), linguistics (e.g. Keller 1994), philosophy of science (e.g. Hull 1988) and sociology (e.g. Merton 1936, Boudon 1982). The above list, which can definitely be extended, illustrates the importance of the problem of ex- plaining unintended consequences in social sciences and in (political) philosophy.
Popper (1962: 342) acknowledged the significance of unintended consequences for social sciences by arguing that the explanation of unintended consequences of human action is ‘the main task of theoretical social sciences’. Yet, unintended consequence is a vague concept and as such it may denote many different things. In this book we will be concerned with a subset of the set of possible unintended consequences; one which is of paramount importance to economics in explaining institutions and macro-social structures. The rough description of this subset is as follows (see Mäki 1991 and Chapters 2 and 5):
- individuals do not intend to bring about a social phenomenon (e.g. a social institution, or a macro-social structure);
- the consequence of their action is a social phenomenon (i.e. an institution or a social structure); and
- one individual alone is not enough to bring about the ‘social’ consequence – that is, independent actions of similar (in the sense that they do not intend to bring about the consequence) agents are needed.
An explanation of unintentionally hurting your hand, or an explanation of the unintended consequences of a government tax plan, does not fall under the above definition and hence are not examined in this book. The former is not examined because the consequence is not a social phenomenon (violates condition (b) – and (c) depending on the case); the latter is not examined because the intention is about a social institution (condition (a) is violated). Given our definition, ‘unin- tended consequence’ is a crucial component of the ‘theory of spontaneous order’, of Adam Smith’s ‘invisible hand’, of Carl Menger’s notion of ‘organic phenom- ena’ and of ‘invisible-hand explanations’. It lies at the core of many contemporary models of institutions and macro-social structures.
The theory of spontaneous order finds its origins in eighteenth-century Scot- tish thought and it is defined with its characterisation of the social order as ‘un- intended consequence of countless individual actions’ (Hamowy 1987: 3). Adam Smith, the founder of modern economics, who was a part of this tradition, pre- sented a metaphorical statement of ‘spontaneous order’ with the ‘invisible hand’. Menger, on the other hand, presented a closely related account of spontaneously created social institutions, where he considered them as being similar to ‘organic phenomena’. Many social scientists and philosophers followed Smith and Menger by trying to answer versions of their questions about institutions and macro-social structures. Their aim was to show how institutions and social structures could emerge (or persist) without any design. Generally, it is believed that neoclassical economists followed Smith’s lead and tried to prove his insights. However, the neoclassical economist’s approach is only one of the possible ways to interpret Smith’s insights. There are at least two different interpretations of the ‘invisible hand’: the one that stresses processes and the other that emphasises end-states (see Chapter 5). The neoclassical economist’s approach is an end-state interpreta- tion: the ‘invisible hand theorem’ in economics stresses the consequences (e.g. optimum allocation of resources), rather than the processes that bring about these consequences.
This book is mainly concerned with what may be called the process interpreta- tion of the invisible hand. Under this interpretation, the ‘invisible hand’ represents causal and structural relationships and processes that may bring about unintended social consequences. Explanations under this particular interpretation can be gathered under the notion of ‘invisible-hand explanations’. An invisible-hand ex- planation aims to show the process that brings about the unintended consequence. Rather than merely focusing on the properties of the end-state (e.g. equilibrium), it explicates the way in which the end-state may be reached (Nozick 1974; Ullmann-Margalit 1978). It is possible to find many examples of such process models in the contemporary literature. The most prominent examples are game- theoretic models of institutions that show how institutions may emerge (or per- sist) as an unintended consequence of human action (e.g. Bicchieri 1993; Sugden 1986; Ullmann-Margalit 1977; Young 1998, etc.). Another area where unintended consequences are important is the emerging field of agent-based computational economics (e.g. Axelrod 1997; Axtell et al. 2001; Epstein and Axtell 1996; Ma- rimon, McGrattan et al. 1990, etc.). The pioneers of the game-theoretic literature acknowledge David Hume, Adam Smith and Carl Menger as their forefathers (see Lewis 1969; Sugden 1986; Ullmann-Margalit 1977; Young 1998) and, similarly, agent-based computational economists generally acknowledge their intellectual debts to Adam Smith and Thomas Schelling (see, for example, Epstein and Axtell 1996; Tesfatsion 2002).
Carl Menger’s (1892a) story of the emergence of a medium of exchange, Tho- mas Schelling’s (1969, 1971a, 1978) models of residential segregation, Peyton H.Young’s (1993a, 1996, 1998) model of emergence of the rules of the road and Joshua Epstein’s and Robert Axtell’s (1996) ‘Sugarscape’ (where they grow artificial societies from the bottom up) are well-known examples of such models. These examples range from verbal models (or stories) to formal game-theoretic and computational models. Despite the differences in their methods and research tools there is an important similarity between them. Each shows how institutions and macro-social structures may emerge (or persist) as an unintended consequence of the (inter)actions of individuals. In order to do this, the authors conjecture (in the latter case with the help of computers) about the conditions under which individual actions may lead to the social phenomena in question. The common feature of these examples is that the observed social phenomenon (i.e. institution or macro-social structure) is ‘produced’ within the model world by conjecturing about the initial conditions (e.g. environmental conditions, characteristics of the agents, etc.) that may bring about the social phenomenon in question as an unin- tended consequence of the interactions of the agents. Moreover, these models are typically ahistorical in the sense that historical facts about the social phenomenon in question do not seem to play any role in these models. They are general and, thus, they are supposed to be applicable to all instances of the social phenomenon in question in different times and places. These models illustrate the possible ways in which certain mechanisms may interact (or may have interacted) to produce the types of institutions or macro-social structures in question.
More strikingly, some of these models seem to challenge the common sense and the historical knowledge about these social phenomena. For example, while many believe that money is a matter of design and was issued by central authori- ties in the past, Menger argues that it was brought about by the (inter)actions of individuals who were pursuing their self-interests without the intention to bring about a commonly acceptable medium of exchange. Schelling, on the other hand, shows that if individuals cannot tolerate living as an extreme minority in their neighbourhood, then residential segregation cannot be avoided even if they are happy in a mixed neighbourhood. Of course, this seems to go against our belief that strong discriminatory preferences (e.g. racism) and economic factors (e.g. wealth differences among ethnic groups) are the main causes of residential seg- regation. A more recent example is Young’s model of the rules of the road. He shows that the rules of the road may emerge with the accumulation of the prec- edent as an unintended consequence of the (inter)actions of the individuals. This model also goes against the belief that the rule that specifies on which side of the road one should drive was designed and imposed by central authorities, like other traffic rules. Finally, Epstein and Axtell show how, under certain conditions, fundamental social structures and group behaviours (e.g. institutions, segregation, cooperation) could emerge from the micro level. In this example, social phenom- ena are quite literally grown by the authors.
All of the aforementioned examples pose difficult questions for social sci- entists and philosophers. How could these models explain anything if they are simply speculations about the initial conditions under which social phenomena may be brought about as unintended consequences? In other words, we under- stand that these authors are able to ‘produce’ a certain social phenomenon in their model world as an unintended consequence of the interactions of model agents. However, given that these models are so abstract, ahistorical and speculative, how could they be used to explain something about the real world?
The philosophical and methodological challenges posed by these models cre- ated many debates in related areas. These debates constitute a significant part of the controversies about the role of abstract modelling in social sciences. The related question here is whether we can learn anything about the real world by studying highly abstract models. This is one of the basic questions of philosophy of science. The usual defence of scientific models is the claim that they isolate the relevant parts of the real world and that such realistic representations of the real world give a close to true account of the phenomenon in question when other things are absent or constant. Some economists also use the argument from real- istic representation in defence of their models. For example, Young (1998: 10) argues that the assumptions of his models ‘represent a fairly accurate picture of reality’.
However, the main criticism to these models is that they ignore the relevant facts, such as the history of the social phenomenon in question – and, therefore, they do not realistically represent the relevant parts of the real world. For exam- ple, Menger’s ‘the origin of money’ does not take into account the way in which money was issued and introduced in history. Moreover, Schelling’s model of seg- regation seems to sidestep two of the most important facts about segregation – the presence of strong discriminatory preferences and the role of economic factors. Thus, the argument concerning realistic representation either has to demonstrate why history is irrelevant, or show the complementarity between these models and history.
As mentioned above, these models start with the problem (e.g. that there is residential segregation) and try to produce the conditions under which this prob- lem may emerge as an unintended consequence of human (inter)action. This methodology invites criticism for the following two reasons. First, it seems to be one-sided, for it tries to construct a model that shows something that the author wishes to see (e.g. residential segregation as an unintended consequence). Second, it may be argued that if one devotes enough time and energy it should be possible to construct a reasonable model that is able to show whatever we wish.
Given the focus of this book, the relevant place to start seeking solutions to these problems is the literature on ‘invisible-hand explanations’. It is argued in this literature that invisible-hand explanations are valuable independently from their truth for they explicate the process that may have brought about the social phenomenon at hand (Ullmann-Margalit 1978). This suggests that these models are valuable even if they are false, or even if they do not get the facts right. It is argued that explication of a hypothetical process that is sufficient to bring about the social phenomenon in question is valuable for its own sake. However, it is not explained why this explication would be valuable, or in what sense it would help us understand the real world. Simply, this argument does not help us much unless it is explicated. This is merely a statement of the author’s intuition about the value of these ‘explanations’. Economists use these models because they believe that they are valuable. For example, Robert Sugden (2000) argues that the reason we believe that these models are conveying a true message about the real world is that we find them ‘credible’ – by way of examining Schelling’s segregation model. He argues that these models are credible like a good story or a novel. Sugden’s basic argument boils down to the statement that we think these models are valuable because we find them plausible. This argument cannot demonstrate the value of these models unless it explains why they are plausible and in what sense plausibil- ity of a conjectural process sheds light on the real world.
Another type of justification comes from computer simulations. It is argued that artificial environments (models, computer models) are used to gain insights about the social phenomenon in question (see, for example, Gilbert and Doran 1994a; Liebrand et al. 1998) or that models and computer simulations are like experiments where we test our ideas (see, for example, Drogoul and Ferber 1994) or that they are similar to thought experiments (e.g. Liebrand 1998; Liebrand et al. 1998). Briefly, it is argued that models and simulations help us in finding out the necessary conditions under which certain results (e.g. segregation) are brought about (within the computer model) and in easily exploring the properties of these model environments. In this account these models are not for explanation but for exploration. However, this does not answer our question about moving from the model world to the real world. Specifically, a satisfactory defence of these models would have to tell us how to translate the results of the model in order to interpret the real world.
The discussions about the interpretation of game theory are also relevant in this respect. As mentioned above, some economists, such as Young, use the argu- ment from realistic representation to justify game-theoretic models. Yet not every game theorist would agree with this. One of the most prominent scholars of this field, Robert Aumann (1985) (also see van Damme 1998), argues that realistic- ness of the models does not matter that much. According to him, the conclusions are much more important: if the model is applicable to many situations and is productive, then it is a good model. He also argues that game theory (and other sciences, in his opinion) ‘is not a quest for truth, but a quest for understanding’. He says, ‘science makes sense of what we see, but it is not what is “really” there’ (van Damme 1998: 181, 182). Aumann basically argues that game-theoretical models help us in putting together what we observe in a coherent framework, that they help us in fitting things together. He also argues that they lead to prediction and control. However, if we accept Aumann’s interpretation of game theory (and science) we are still faced with the following questions: firstly, if the models of institutions and macro-social structures do not represent the reality, how could they lead to prediction and control, and most importantly to understanding? Sec- ond, Aumann emphasises the productiveness and applicability of the models. Yet the current state of the modelling of institutions and macro-social structures (as unintended consequences) cannot be considered to have many real-world applica- tions or satisfactory predictive power. Should we then conclude that these models are not valuable?
It is the argument of this book that all of the interpretations expressed above convey justifiable intuitions about these models. That is, ‘realisticness’, ‘expli- cation’, ‘credibility’, ‘exploration’ and ‘fitting things together’ are all parts of a framework that would help us in making sense of these models. However, there is no existing framework where these things are presented coherently and satisfac- torily. It is the main task of this book to develop such a framework and to use it to gain new insights into the contemporary literature that characterises institutions and macro-social structures as unintended consequences of human action.
Source: Aydinonat N. Emrah (2008), The Invisible Hand in Economics: How Economists Explain Unintended Social Consequences, Routledge; 1st edition.