Brain, Decision, and Debt
Stanford University - Psychology
Gregory R Samanez-Larkin
Yale University - Department of Psychology
In R. Brubaker, R. M. Lawless, & C. J. Tabb (Eds.) A Debtor World: Interdisciplinary Perspectives on Debt (pp. 167–180). New York: Oxford University Press, 2012
In this chapter, we summarize recent findings in neuroeconomics suggesting that emotion (specifically, “anticipatory affect”) can influence financial decisions, and then discuss how individual differences in anticipatory affect may promote proneness to consumer debt. Thanks to improvements in spatial and temporal resolution, functional magnetic resonance imaging (FMRI) experiments have begun to suggest that activation of a brain region associated with anticipating gains (i.e., the nucleus accumbens or NAcc) precedes an increased tendency to seek financial gains, whereas activation of another region associated with anticipating losses (i.e., the anterior insula) precedes an increased tendency to avoid financial losses. By extension, individual differences in increased gain anticipation, decreased loss anticipation, or some combination of the two (plus a third nonreflective factor) might promote proneness to debt (Knutson, Samanez-Larkin, and Kuhnen 2011). Ultimately, neuroeconomic advances may help individuals to optimize their investment strategies, as well as empower institutions to minimize consumer debt. Neuroeconomists seek to explain how brains choose. Thanks to technological advances, scientists can now “open the black box” of the brain, moving below the surface mapping between input and output to identification of mediating neural and psychological processes. Thus, neuroeconomic methods might allow scientists to bridge gaps between neural, psychological, and behavioral levels of analysis. Below, we summarize ongoing attempts to forge links from affective neural circuits to affective experience and, eventually, to decisions that can lead to debt.
Number of Pages in PDF File: 14
Keywords: assets, debt, learning, affect, psychology, neuroscience
JEL Classification: D83, K00, H63, C91Accepted Paper Series
Date posted: September 2, 2012
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