Foundations of Neuroeconomic Analysis</Italic>

Journal of Economic Literature 2013, 51(4), 1155–1182 http://dx.doi.org/10.1257/jel.51.4.1155 A Review Essay about Foundations of Neuroeconomic Analysis by Paul Glimcher † Colin F. Camerer* Neuroeconomics aims to discover mechanisms of economic decision, and express them mathematically, to predict observed choice. While the contents of neuroeconomic models and evidence are obviously different than in traditional economics, (some of the) goals are identical: to explain and predict choice, the effects of comparative statics, and perhaps make interesting new welfare judgments that are defensible. To this end, Paul Glimcher’s important book carefully describes how economics, psychological, and neural levels of explanation can be linked (a structure which has been successful in visual neuroscience). As Glimcher shows, the neural evidence is quite strong for a process of learning valuations through prediction error, and a simple model of neural valuation and comparison that corresponds to random utility (though subject to normalization, which produces menu effects). There is also rapidly growing evidence for more complicated constructs in behavioral economics, including prospect theory’s account of risky choice, hyperbolic time discounting, level-k models of games, and social preferences corresponding to internal reward based on what happens to other agents. ( JEL D01, D03, Y30) 1. Introduction of economists working extra hard, and inge- niously, to infer unobservables—such as he splashy attention and criticism of beliefs, utilities, thinking costs, and more— Tneuroeconomics is a referendum on from observable choices. Other scientific dis- how curious economists are about how ciplines take an easier route by simply trying the brain makes economic decisions and to measure the unobservables directly as best whether new insights can tweak old models they can, as well as inferring unobservables or inspire new ones. statistically. At one extreme is aggressive disinterest in At the other extreme is a conviction that brain activity. This disinterest is motivated by progress will certainly be made in under- the methodological history and convention standing the biological basis of economic choice, that such progress will inform “standard” economic concerns (such as predict- * California Institute of Technology. † Go to http://dx.doi.org/10.1257/jel.51.4.1155 to visit ing choice responses to policy variables), the article page and view author disclosure statement(s). that progress is certainly facilitated by direct 1155 1156 Journal of Economic Literature, Vol. LI (December 2013) collaboration and by shared scientific literacy Rustichini (2004) nicely put it, the goal is between economists and neuroscientists, a theory that is mechanistic, mathematical, and that this is an historically good time to and behavioral. Traditional economic mod- start that collaboration. els are both mathematical and behavioral. The extremely skeptical approach fore- Typical neuroscience models are mechanis- casts the time at which neural data is useful tic and behavioral, but rarely mathemati- as “never.” The progressive approach says cal. The shared goal of neuroeconomists, the time is “someday.” Which do you think is whether from neuroscience or economics, is likely to prove correct in your lifetime? to have models with all three properties. This review essay is about the motives, Some neuroeconomists are interested in methods, and tentative early findings in neu- the mechanistic details for their own sake, roeconomics, and where they are between or for practical purposes, such as associating the two extremes. The review part is moti- computational mistakes with mental health vated by the 2011 book Foundations of disorders (e.g., Kishida, King-Casas, and Neuroeconomic Analysis, by Paul Glimcher. Montague 2010). Others, like myself, hope The title is apparently a (perilous?) hom- that understanding the neural mechanisms age to Paul Samuelson’s monumental will actually improve our ability to under- Foundations of Economic Analysis. stand choice in order to better accomplish Glimcher’s book presents a helpfully clear traditional goals in economics—predicting vision of one part of the progressive approach choices, predicting responses to changes in to neuroeconomics. The titled “foundation” prices and other variables, designing insti- that dominates the book is a simple value- tutions that are robust to imperfections and-compare model in which neural circuits in neural implementation, and perhaps in compute random utility for choice objects, understanding more about welfare. then compare them and pick the best one. Please note that all economists who are Glimcher argues that there is actually a interested in neuroscience are perfectly natural correspondence between elements aware that the study of brain activity during of these neural mechanisms and “as if” con- choice is a radical departure from current structs in standard theory (i.e., utilities and standard economic practice. The agnostic maximization). disinterest in mechanistic details is very obvi- The book is not intended to be either an ously a traditional part of modern revealed overall, balanced introduction to a rapidly- preference theory (although not of earlier growing field, nor a comprehensive textbook. economic thought).1 So this essay will first present a broader The key step for seeing whether neu- vision about all the building blocks of neuroscience can contribute to economics is roeconomics, filling in what readers might distinguishing particular methodological want to know about the many other develop- approaches in economics from the general ments in neuroeconomics that are not cov- ered in the book. Then I will comment, as a book critic, on what is both admirable and 1 It is also noteworthy that many earlier economists imperfect about Glimcher’s book. including Edgeworth, Fisher, and Ramsey were keenly interested in, and wrote fantastically, about “hedonim- 2. Goals and Methods of Neuroeconomics eters” and other then-fictional devices for linking biology and choice (Colander 2007). Thus, the modernized recon- The main goal of neuroeconomics is to struction that “economists were never interested in flesh- and-blood human beings” (Gul and Pesendorfer 2008) is supply a mechanistic account of how eco- wrong (unless Edgeworth et al. are retroactively disbarred nomic choices are made. As Glimcher and from the category “economists” for their speculations). Camerer: A Review Essay about Foundations of Neuroeconomic Analysis 1157 goal of understanding what causes choice. contains no biological concepts of any kind” The proper definition of the scope of eco- (Gul and Pesendorfer 2008). nomics is a broad one: our goal is to under- A class of examples that refute the claim stand the causes of choices and their welfare of independence of economics and neuro- implications. Aggregation across individuals science is the prediction of actual choices and institutions such as firms and govern- from direct recording of neural activity. ments play a special role because those This kind of prediction is useful when past forces produce choice sets, prices, informa- choice data are not likely to predict future tion, and special kinds of constraints (e.g., choices well. Examples include new prod- law). ucts, responses to policy changes that are One way to study the choice process is historically unprecedented (e.g., labor to assume that unobserved preferences are markets upon integration of East and West stable and revealed well by observed past Germany), or when omitted variables in choices. However, there is nothing about the measures of past choices bias estimates. In broader desire to understand and predict these cases, a revealed-preference approach choices that prohibits other attempts to mea- based on inference from past data is subject sure what causes choices by using nonchoice to a variant of the Lucas critique (see Dean data. That is, inference only from revealed 2013). preference is one way to learn about the Some studies have already shown that causes of choices and welfare, but it is not the neural measures during passive viewing of only way. Other ways are certainly conceiv- choice objects can predict, to some extent, able, and might be better in some respects what choices are later made (see Levy et al. (e.g., Bernheim 2009). 2010; Smith et al. forthcoming). Neural Importantly, Glimcher correctly notes subjective value reactions to antismoking that linking economics and neuroscience ads predict whether smokers quit and which first requires “natural kinds” that are under- televised ads draw the most calls to a help stood in their disciplines. Linking them then hotline (Falk, Berkman, and Lieberman requires scientists who understand both 2012; Falk et al. 2011). In fact, neural reac- natural kinds and agree on some of the ways tions to the ads from a small brain-imaged in which the two kinds are related (though sample predicted actual hotline calls (by the empirical details of the relation are likely thousands of callers who see the ads on to be under constant debate and revision). TV) better than subjects’ self-reports of ad Glimcher proposes the term “subjective effectiveness did. What artificial TV-series value” for a neural “kind” and utility—more ideas people choose to forward to others aptly, decision utility—for the associated (a measure of “virality”) are predicted by economic kind. This view has been implicit activity in mentalizing and reward areas in neuroeconomics from the beginning,

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