Neuroeconomics: infeasible and underdetermined

Advocates of neuroeconomics claim to offer the prospect of creating a “unified behavioral theory” by drawing upon the techniques of neuroscience and psychology and combining them with economic theory. Ostensibly, through the “direct measurement” of our thoughts, economics and social science will be “revolutionized.” Such claims have been subject to critique from mainstream and non-mainstream economists alike. Many of these criticisms relate to measurability, relevance, and coherence. In this article, we seek to contribute to this critical examination by investigating the potential of underdetermination, such as the statement that testing involves the conjunction of auxiliary assumptions, and that consequently it may not be possible to isolate the effect of any given hypothesis. We argue that neuroeconomics is especially sensitive to issues of underdetermination. Institutional economists should be cautious of neuroeconomists’ zeal as they appear to over-interpret experimental findings and, therefore, neuroeconomics may provide a false prospectus seeking to reinforce the nostrums of homo economicus

COMMENTS ON THE POTENTIAL SIGNIFICANCE OF NEUROECONOMICS FOR ECONOMIC THEORY

In this short note I speculate about the various ways in which the study of neurological aspects of decision making could be fruitful for economic modelling

Decision-Making: A Neuroeconomic Perspective

This article introduces and discusses from a philosophical point of view the nascent field of neuroeconomics, which is the study of neural mechanisms involved in decision-making and their economic significance. Following a survey of the ways in which decision-making is usually construed in philosophy, economics and psychology, I review many important findings in neuroeconomics to show that they suggest a revised picture of decision-making and ourselves as choosing agents. Finally, I outline a neuroeconomic account of irrationality

Neuroeconomics: Using Neuroscience to Make Economic Predictions

Neuroeconomics seeks to ground economic theory in detailed neural mechanisms which are expressed mathematically and make behavioural predictions. One finding is that simple kinds of economising for life-and-death decisions (food, sex and danger) do occur in the brain as rational theories assume. Another set of findings appears to support the neural basis of constructs posited in behavioural economics, such as a preference for immediacy and nonlinear weighting of small and large probabilities. A third direction shows how understanding neural circuitry permits predictions and causal experiments which show state-dependence of revealed preference – except that states are biological and neural variables

Neuroeconomics: How Neuroscience Can Inform Economics

Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the "black box" of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems ("executive function") interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, "dual-process" models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are "rationally" neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in "theory of mind", correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information

Decision-Making: A Neuroeconomic Perspective

This article introduces and discusses from a philosophical point of view the nascent field of neuroeconomics, which is the study of neural mechanisms involved in decision-making and their economic significance. Following a survey of the ways in which decision-making is usually construed in philosophy, economics and psychology, I review many important findings in neuroeconomics to show that they suggest a revised picture of decision-making and ourselves as choosing agents. Finally, I outline a neuroeconomic account of irrationality.neuroeconomics; decision-making; rationality; ultimatum; philosophy; psychology

Neuroeconomics: A Critique of ‘Neuroeconomics: A Critical Reconsideration’

Some economists believe that neuroeconomists threatens the theory of economics. Glenn Harrison’s paper “Neuroeconomics: A Critical Reconsideration” (2008) provides some support for this view, though some of the points he makes are somewhat disguised. The field of neuroeconomics is barely into its teenage years; and it is trying to do what? Criticize and redesign the field of economics developed over hundreds of years? But that is not what neuroeconomics is trying to do, in spite of all the efforts of some economists trying to place it into that shoebox (see the argument in great detail in Andrew Caplin, Andrew Schotter 2008). Neuroeconomics is a Mendelian-Economics of sort; it is a science that is able to generate data by fixing the environment to some degree, varying a single independent variable for its affects, and is able to see each individual’s choices from initiation of the decision-making process to its outcome. Mainstream (standard) economics, on the other hand, looks at the average of the outcomes of many individuals and proposes how people chose those outcomes, retroactively. The two fields, neuroeconomics and standard economics, are evaluating two sides of the same coin: one with and the other without ceteris paribus; they are not in conflict with one another.Neuroeconomics, Standard Economics, Ceteris Paribus, Hormones

Neuroeconomics of suicide.

Suicidal behavior is a leading cause of injury and death worldwide. Suicide has been associated with psychiatric illnesses such as depression and schizophrenia, as well as economic uncertainty, and social/cultural factors. This study proposes a neuroeconomic framework of suicide. Neuroeconomic parameters (e.g., risk-attitude, probability weighting, time discounting in intertemporal choice, and loss aversion) are predicted to be related to suicidal behavior. Neurobiological and neuroendocrinological substrates such as serotonin, dopamine, cortisol (HPA axis), nitric oxide, serum cholesterol, epinephrine, norepinephrine, gonadal hormones (e.g., estradiol and progesterone), dehydroepiandrosterone (DHEA) in brain regions such as the orbitofrontal/dorsolateral prefrontal cortex and limbic regions (e.g., the amygdala) may supposedly be related to the neuroeconomic parameters modulating the risk of suicide. The present framework puts foundations for ―molecular neuroeconomics‖ of decision-making processes underlying suicidal behavior

From cognitive science to cognitive neuroscience to neuroeconomics

As an emerging discipline, neuroeconomics faces considerable methodological and practical challenges. In this paper, I suggest that these challenges can be understood by exploring the similarities and dissimilarities between the emergence of neuroeconomics and the emergence of cognitive and computational neuroscience two decades ago. From these parallels, I suggest the major challenge facing theory formation in the neural and behavioural sciences is that of being under-constrained by data, making a detailed understanding of physical implementation necessary for theory construction in neuroeconomics. Rather than following a top-down strategy, neuroeconomists should be pragmatic in the use of available data from animal models, information regarding neural pathways and projections, computational models of neural function, functional imaging and behavioural data. By providing convergent evidence across multiple levels of organization, neuroeconomics will have its most promising prospects of success