I believe it has the potential to change economics tremendously: rather than treating the brain as a “black box,” it can be investigated to foundationally undergird our notions of “preference,” “value,” “satisfaction,” and so on; such concepts might be more robustly developed or perhaps even abandoned.
As Colin Camerer, George Loewenstein, and Drazen Prelec state,
In what way might neuroscience contribute to economics? First, in the applied domain, neuroscience measurements have a comparative advantage when other sources of data are unreliable or biased, as is often the case with surveys and self-reports. Since neuroscientists are “asking the brain, not the person”, it is possible that direct measurements will generate more reliable indices of some variables which are important to economics (e.g., consumer confidence, and perhaps even welfare).
Second, basic neuroeconomics research will ideally be able to link hypotheses about specific brain mechanisms (location, and activation) with unobservable intermediate variables (utilities, beliefs, planning ahead), and with observable behavior (such as choices). One class of fruitful tasks is those where some theories assume choice A and choice B are made by a common mechanism, but a closer neural look might suggest otherwise. For example, a standard assumption in utility theory is that marginal rates of substitution exist across very different bundles of goods (and, as a corollary, that all goods can be priced in money terms). But some tradeoffs are simply too difficult or morally repulsive (e.g., selling a body part). Elicited preferences often vary substantially with descriptions and procedures (e.g., Ariely, Loewenstein, Prelec, 2003). Neuroscience might tell us precisely what a “difficult” choice or a “sacred preference” is, and why descriptions and procedures matter.
A third payoff from neuroscience is to suggest that economic choices which are considered different in theory are using similar brain circuitry. For example, studies cited above found that insula cortex is active when players in ultimatum games receive low offers, when people choose ambiguous gambles or money, and when people see faces of others who have cooperated with them. This suggests a possible link between these types of games and choices which would never have been suggested by current theory.
A fourth potential payoff from neuroscience is to add precision to functions and parameters in standard economic models. For example, which substances are cross-addictive is an empirical question which can guide theorizing about dynamic substitution and complementarity. A “priming dose” of cocaine enhances craving for heroin, for example (Gardner and Lowinson, 1991). Work on brain structure could add details to theories of human capital and labor market discrimination. The point is that knowing which neural mechanisms are involved tell us something about the nature of the behavior. For example, if the oxytocin hormone is released when you are trusted, and being trusted sparks reciprocation, then raising oxytocin exogeneously could increase trustworthy behavior (if the brain doesn’t adjust for the exogeneity and “undo” its effect). In another example, Lerner, Small and Loewenstein (in press) show that changing moods exogeneously changes buying and selling prices for goods. The basic point is that understanding the effects of biological and emotional processes like hormone release and moods will lead to new types of predictions about how variations in these processes affect economic behavior.
In the empirical contracts literature there is, surprisingly, no adverse selection and moral hazard in the market for automobile insurance (Chiappori et al, 2001) but plenty of moral hazard in health-care use and worker behavior. A neural explanation is that driving performance is both optimistic (everyone thinks they are an above-average driver, so poor drivers do not purchase fuller coverage) and automatic (and is therefore unaffected by whether drivers are insured) but health-care purchases and labor effort are deliberative. This suggests that “degree of automaticity” is a variable that can be usefully included in contracting models.
Will it ever be possible to create formal models of how these brain features interact? The answer is definitely “Yes”, because models already exist (e.g., Bernheim and Rangel, in press; Benhabib and Bisin, 2004; Loewenstein and O’Donoghue, 2004). A key step is to think of behavior as resulting from the interaction of a small number of neural systems—such as automatic and controlled processes, or “hot” affect and “cold” cognition, or a module that chooses and a module that interprets whether the choice signals something good or bad about underlying traits (Bodner and Prelec, 2003). While this might seem complex, keep in mind that economics is already full of multiple-system approaches. Think of supply and demand, or the interaction of a principal and an agent she hires. The ability to study these complex systems came only after decades of careful thought (and false modeling starts) and sharp honing by many smart economists. Could creating a general multiple-system model of the brain really be that much harder than doing general equilibrium theory?
Overall, due to other assumptions (e.g., more often than not, an individual knows his own interests better than others do), I would still advocate anarchism (hence, that is my primary policy).