In recent years, several authors have reconstructed the relationship between 20th-century economic theory and neuro-psychological research in terms of a three-stage narrative of initial unity, increasing separation, and ongoing reunification. In this article, I draw on major developments in economic theory and neuro-psychological research to provide a descriptive and normative critique of this reconstruction. Moreover, I put forward a reconstruction of the relationship between economics and neuro-psychology that, I claim, better fits both the available empirical evidence and the methodological foundations (...) of these disciplines. In doing so, I argue that recent calls to develop a unified interdisciplinary framework for modeling choice are premised on disputable presuppositions concerning both the domain of economic theory and the relationship between this theory’s axiomatic foundations and empirical findings about the neuro-psychological substrates of choice. (shrink)

Over the last decade, neuroeconomic research has attracted increasing attention by economic modellers and methodologists. In this paper, I examine five issues about neuroeconomic modelling and methodology that have recently been subject to considerable controversy. For each issue, I explicate and appraise prominent neuroeconomists' findings, focusing on those that are claimed to directly inform economic theorizing. Moreover, I assess often-made assertions concerning how neuroeconomic research putatively advances the economic modelling of choice. In doing so, I combine review and critical arguments (...) to provide a methodological evaluation of neuroeconomists' contributions. (shrink)

There continues to be significant confusion about the goals, scope, and nature of modelling practice in neuroeconomics. This article aims to dispel some such confusion by using one of the most recent critiques of neuroeconomic modelling as a foil. The article argues for two claims. First, currently, for at least some economic model of choice behaviour, the benefits derivable from neurally informing an economic model do not involve special tractability costs. Second, modelling in neuroeconomics is best understood within Marr’s three-level (...) of analysis framework and in light of a co-evolutionary research ideology. The first claim is established by elucidating the relationship between the tractability of a model, its descriptive accuracy, and its number of variables. The second claim relies on an explanation of what it can take to neurally inform an economic model of choice behaviour. 1 Introduction2 Neurally Informed Models of Choice: A Case Study2.1 A case study on risk-sensitive choice2.1.1 Target and modelling framework2.1.2 Research question and hypotheses2.1.3 Competitive models of risk-sensitive behaviour2.1.4 Model-based fMRI: from economics to brains and back2.2 Neurally informed modelling3 Tractability: When Does Size Matter?4 Neural Integration and the Co-evolutionary Research Ideology5 Conclusion. (shrink)

Choice modellers are frequently criticized for failing to provide accurate representations of the neuro-psychological substrates of decisions. Several authors maintain that recent neuro-psychological findings enable choice modellers to overcome this alleged shortcoming. Some advocate a realistic interpretation of neuro-psychological models of choice, according to which these models posit sub-personal entities with specific neuro-psychological counterparts and characterize those entities accurately. In this article, I articulate and defend three complementary arguments to demonstrate that, contrary to emerging consensus, even the best available neuro-psychological (...) models of choice cannot be justifiably given this realistic interpretation. Moreover, I explicate what challenges will continue to hamper neuro-psychological modellers’ attempts to substantiate a realistic interpretation of their models. In doing so, I draw on the literature on scientific modelling to advance the ongoing philosophical discussion concerning the ontological status of the sub-personal entities posited in distinct decision sciences, the resemblance relations that supposedly connect choice models and the neuro-psychological substrates of decisions, and what conditions these models must satisfy to be regarded as realistic representations of their target systems. (shrink)

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

Proponents of neuroeconomics often argue that better knowledge of the human neural architecture enables economists to improve standard models of choice. In their view, these improvements provide compelling reasons to use neural findings in constructing and evaluating economic models. In a recent article, I criticized this view by pointing to the trade-offs between the modeling desiderata valued by neuroeconomists and other economists, respectively. The present article complements my earlier critique by focusing on three modeling desiderata that figure prominently in economic (...) and neuroeconomic modeling. For each desideratum, I examine findings that neuroeconomists deem to be especially relevant for economists and argue that neuroeconomists have failed to substantiate their calls to use these findings in constructing and evaluating economic models. In doing so, I identify methodological and evidential constraints that will continue to hinder neuroeconomists’ attempts to improve such models. Moreover, I draw on the literature on scientific modeling to advance the ongoing philosophical discussion regarding the prospects of interdisciplinary models of choice. (shrink)

In a recent article in this Journal, Fumagalli argues that economists are provisionally justified in resisting prominent calls to integrate neural variables into economic models of choice. In other articles, various authors engage with Fumagalli’s argument and try to substantiate three often-made claims concerning neuroeconomic modelling. First, the benefits derivable from neurally informing some economic models of choice do not involve significant tractability costs. Second, neuroeconomic modelling is best understood within Marr’s three-level of analysis framework for information-processing systems. And third, (...) neural findings enable choice modellers to confirm the causal relevance of variables posited by competing economic models, identify causally relevant variables overlooked by existing models, and explain observed behavioural variability better than standard economic models. In this paper, I critically examine these three claims and respond to the related criticisms of Fumagalli’s argument. Moreover, I qualify and extend Fumagalli’s account of how trade-offs between distinct modelling desiderata hamper neuroeconomists’ attempts to improve economic models of choice. I then draw on influential neuroeconomic studies to argue that even the putatively best available neural findings fail to substantiate current calls for a neural enrichment of economic models. (shrink)