Understanding more about how the brain functionsshouldhelp us understand economic behaviour. But some would have us believe that it has done this already, and that insights from neuroscience have already provided insights in economics that we would not otherwise have. Much of this is just academic marketing hype, and to get down to substantive issues we need to identify that fluff for what it is. After we clear away the distractions, what is left? The answer is that a lot is (...) left, but it is still all potential. That is not a bad thing, or a reason to stop the effort, but it does point to the need for a serious reconsideration of what neuroeconomics is and what passes for explanation in this literature. I argue that neuroeconomics can be a valuable field, but not the way it is being developed and “sold” now. The same is true more generally of behavioural economics, which shares many of the methodological flaws of neuroeconomics. (shrink)

The goal of neuroeconomics is a mathematical theory of how the brain implements decisions, that is tied to behaviour. This theory is likely to show some decisions for which rational-choice theory is a good approximation, to provide a deeper level of distinction among competing behavioural alternatives, and to provide empirical inspiration for economics to incorporate more nuanced ideas about endogeneity of preferences, individual difference, emotions, endogeneous regulation of states, and so forth. I also address some concerns about rhetoric and practical (...) epistemology. Neuroscience articles are necessarily speculative and the science has proceeded rapidly because of that rhetorical convention. Single-study papers are encouraged and are necessarily limited in what can be inferred, so the sturdiest cumulation of results, and the best guide forward, comes in review journals which compile results and suggest themes. The potential of neuroeconomics is in combining the clearest experimental paradigms and statistical methods in economics, with the unprecedented capacity to measure a range of neural and cognitive activity that economists like Edgeworth, Fisher and Ramsey daydreamed about but did not have. (shrink)

We argue that neuroeconomics should be a mechanistic science. We defend this view as preferable both to a revolutionary perspective, according to which classical economics is eliminated in favour of neuroeconomics, and to a classical economic perspective, according to which economics is insulated from facts about psychology and neuroscience. We argue that, like other mechanistic sciences, neuroeconomics will earn its keep to the extent that it either reconfigures how economists think about decision-making or how neuroscientists think about brain mechanisms underlying (...) behaviour. We discuss some ways that the search for mechanisms can bring about such top-down and bottom-up revision, and we consider some examples from the recent neuroeconomics literature of how varieties of progress of this sort might be achieved. (shrink)

Ever since David Hume, empiricists have barred powers and capacities from nature. In this book Cartwright argues that capacities are essential in our scientific world, and, contrary to empiricist orthodoxy, that they can meet sufficiently strict demands for testability. Econometrics is one discipline where probabilities are used to measure causal capacities, and the technology of modern physics provides several examples of testing capacities (such as lasers). Cartwright concludes by applying the lessons of the book about capacities and probabilities to the (...) explanation of the role of causality in quantum mechanics. (shrink)

In this sequence of philosophical essays about natural science, the author argues that fundamental explanatory laws, the deepest and most admired successes of modern physics, do not in fact describe regularities that exist in nature. Cartwright draws from many real-life examples to propound a novel distinction: that theoretical entities, and the complex and localized laws that describe them, can be interpreted realistically, but the simple unifying laws of basic theory cannot.

This essay introduces the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The central contribution of the essay is to outline a middle course between strict localization on the one hand, and holism on the other, in such a way as to account for the supporting data on both sides of the argument. The massive redeployment hypothesis is supported by case studies (...) of redeployment, and compared and contrasted with other theories of the localization of function. (shrink)

This essay introduces the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The central contribution of the essay is to outline a middle course between strict localization on the one hand, and holism on the other, in such a way as to account for the supporting data on both sides of the argument. The massive redeployment hypothesis is supported by case studies (...) of redeployment, and compared and contrasted with other theories of the localization of function. (shrink)

Neuroeconomics has the potential to fundamentally change the way economics is done. This article identifies the ways in which this will occur, pitfalls of this approach, and areas where progress has already been made. The value of neuroeconomics studies for social policy lies in the quality, replicability, and relevance of the research produced. While most economists will not contribute to the neuroeconomics literature, we contend that most economists should be reading these studies.

For an economist, ultimate goals of neuroeconomic research include improving economic policy analysis. One path toward this goal is to use neuroeconomic data to advance economic theory, and productive efforts have been made towards that end. Equally important, though less studied, is how neuroeconomics can provide quantitative evidence on policy, and in particular the way in which it might inform structural econometric inference. This paper is a first step in that direction. We suggest here that key forms of preference (or (...) decision strategy) heterogeneity can be identified by brain imaging studies and, consequently, linked stochastically to observable individual characteristics. Then, recognizing that brain-imaging studies are substantially costly, we derive conditions under which the probabilistic link between observable characteristics and type, a quantity critical to policy analysis, can be estimated more precisely by combining data from traditional and brain-based decision studies. (shrink)

Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...) Pauling's work involved modeling; much of Darwin's and Mendeleev's did not. In order to capture this distinction, I consider two examples of theory construction in detail: Volterra's treatment of post-WWI fishery dynamics and Mendeleev's construction of the periodic system. I argue that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis. This differentiation between modelers and non-modelers is one component of the larger project of understanding the practice of modeling, its distinctive features, and the strategies of abstraction and idealization it employs. (shrink)

Despite their best efforts, scientists may be unable to construct models that simultaneously exemplify every theoretical virtue. One explanation for this is the existence of tradeoffs: relationships of attenuation that constrain the extent to which models can have such desirable qualities. In this paper, we characterize three types of tradeoffs theorists may confront. These characterizations are then used to examine the relationships between parameter precision and two types of generality. We show that several of these relationships exhibit tradeoffs and discuss (...) what consequences those tradeoffs have for theoretical practice. (shrink)

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

Roald Hoffmann and other theorists claim that we ought to use highly idealized chemical models (“qualitative models”) in order to increase our understanding of chemical phenomena, even though other models are available which make more highly accurate predictions. I assess this norm by examining one of the tradeoffs faced by model builders and model users—the tradeoff between precision and generality. After arguing that this tradeoff obtains in many cases, I discuss how the existence of this tradeoff can help us defend (...) Hoffmann's norm for modelling. (shrink)

In our 1993 paper, “A Critical Look,‘ Elliott Sober and I concluded that the famous claim about model formulation and constraints made by Richard Levins in his influential 1966 article on model building in population biology is neither true nor normative. Here, I comment upon the claim of Odenbaugh that the conclusions of “A Critical Look‘ are incorrect. My conclusions remain that Levins’ claim about the tradeoff between model properties lacks logical coherence, generates an arbitrary model classification, and lacks normative (...) utility. Accordingly, I view his claim as providing no useful insight into the nature of models and model building in population biology. (shrink)

Neuroeconomics is examined critically using data on the response times of subjects who were asked to express their preferences in the context of the Allais Paradox. Different patterns of choice are found among the fast and slow responders. This suggests that we try to identify types of economic agents by the time they take to make their choices. Nevertheless, it is argued that it is far from clear if and how neuroeconomics will change economics.

I distinguish between two styles of research that are both called . Neurocellular economics (NE) uses the modelling techniques and mathematics of economics to model relatively encapsulated functional parts of brains. This approach rests upon the fact that brains are, like markets, massively distributed information-processing networks over which executive systems can exert only limited and imperfect governance. Harrison's (2008) deepest criticisms of neuroeconomics do not apply to NE. However, the more famous style of neuroeconomics is behavioural economics in the scanner. (...) This is often motivated by complaints about conventional economics frequently heard from behavioural economists. It attempts to use neuroimaging data to justify arguments for replacing standard aspects of microeconomic theory by facts and conjectures about human psychology. Harrison's grounds for unease about neuroeconomics apply to most BES, or at least to its explicit methodology. This methodology is naively reductionist and illegitimately assumes that economics should not do what all successful science does, namely, model abstract aspects of its target phenomena instead of would-be complete and fully ecologically situated facsimiles of them. (shrink)

The following is a set of reading notes on, and questions for, the Neuroeconomics enterprise. My reading of neuroscience evidence seems to be at odds with basic conceptions routinely assumed in the Neuroeconomics literature. I also summarize methodological concerns regarding design, implementation, and statistical evaluation of Neuroeconomics experiments.

Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since (...) Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

Ecologist Richard Levins argues population biologists must trade-off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail since (...) Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

The problem of idealization in empirical sciences is very rarely taken up in works concerned with the methodology of those sciences. It seems to be common knowledge that in advanced natural sciences references are made to concepts such as “perfectly rigid body,” “material point,” “perfect gas,” etc., but it remains a fact that the most important methodological concepts, concepts which have determined the present-day form of the philosophy of science, have been advanced without regard to the peculiarities of the procedure (...) mentioned above. And yet a moment's consideration suffices to raise doubts as to Carnap's physicalism and/or Popper's falsificationism if we just realize the trivial and commonly known truth that empirical sciences resort to idealizationism. For how are we to imagine a reduction of idealizational concepts to observation terms? And how are we to imagine that theorems which include idealizational concepts imply observation statements which refute, or at least are at variance with, those theorems? But it is a fact that such doubts have neither been raised by the authors of the conceptions mentioned above, nor have they been raised against them. (shrink)

We briefly describe ways in which neuroeconomics has made contributions to its contributing disciplines, especially neuroscience, and a specific way in which it could make future contributions to both. The contributions of a scientific research programme can be categorized in terms of (1) description and classification of phenomena, (2) the discovery of causal relationships among those phenomena, and (3) the development of tools to facilitate (1) and (2). We consider ways in which neuroeconomics has advanced neuroscience and economics along each (...) line. Then, focusing on electrophysiological methods, we consider a puzzle within neuroeconomics whose solution we believe could facilitate contributions to both neuroscience and economics, in line with category (2). This puzzle concerns how the brain assigns reward values to otherwise incomparable stimuli. According to the common currency hypothesis, dopamine release is a component of a neural mechanism that solves comparability problems. We review two versions of the common currency hypothesis, one proposed by Read Montague and colleagues, the other by William Newsome and colleagues, and fit these hypotheses into considerations of rational choice. (shrink)

Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.

Nobody in this debate questions the point that neuroeconomics remains full of potential, and little else as yet. If so, that really is progress of sorts. I was getting afraid that we would have to open nominations for the Captain Ahab Award for obsessive work on the promotion of neuroeconomics.

Nobody in this debate questions the point that neuroeconomics remains full of potential, and little else as yet. If so, that really is progress of sorts. I was getting afraid that we would have to open nominations for the Captain Ahab Award for obsessive work on the promotion of neuroeconomics.

Models as Mediators discusses the ways in which models function in modern science, particularly in the fields of physics and economics. Models play a variety of roles in the sciences: they are used in the development, exploration and application of theories and in measurement methods. They also provide instruments for using scientific concepts and principles to intervene in the world. The editors provide a framework which covers the construction and function of scientific models, and explore the ways in which they (...) enable us to learn about both theories and the world. The contributors to the volume offer their own individual theoretical perspectives to cover a wide range of examples of modelling, from physics, economics and chemistry. These papers provide ideal case-study material for understanding both the concepts and typical elements of modelling, using analytical approaches from the philosophy and history of science. (shrink)

When economists have to choose between competing theories, they evaluate not only the theories’ empirical relevance, but also qualities like their simplicity, tractability, parsimony and unifying power. These are called the epistemic virtues of a theory. The present paper proposes a formal definition for some epistemic virtues and investigates their role for theory choice in economics.

sides of the argument. MRH is supported by some case studies of redeployment, and an empirical review of 135..