Herding in Financial Behaviour: A Behavioural and Neuroeconomic Analysis of Individual Differences

Michelle Baddeley, Christopher Burke, W. Schultz and Philippe Tobler

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: Experimental analyses have identified significant tendencies for individuals to follow herd decisions, a finding which has been explained using Bayesian principles. This paper outlines the results from a herding task designed to extend these analyses using evidence from a functional magnetic resonance imaging (fMRI) study. Empirically, we estimate logistic functions using panel estimation techniques to quantify the impact of herd decisions on individuals' financial decisions. We confirm that there are statistically significant propensities to herd and that social information about others' decisions has an impact on individuals' decisions. We extend these findings by identifying associations between herding propensities and individual characteristics including gender, age and various personality traits. In addition fMRI evidence shows that individual differences correlate strongly with activations in the amygdala – an area of the brain commonly associated with social decision-making. Individual differences also correlate strongly with amygdala activations during herding decisions. These findings are used to construct a two stage least squares model of financial herding which confirms that individual differences and neural responses play a role in modulating the propensity to herd.

Keywords: herding; social influence, individual differences, neuroeconomics, fMRI, amygdala (search for similar items in EconPapers)
JEL-codes: D03 D53 D70 D83 D87 G11 (search for similar items in EconPapers)
Date: 2012-05-09
New Economics Papers: this item is included in nep-exp and nep-neu
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:1225

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