'Outlier Blindness': Efficient Coding Generates an Inability to Represent Extreme Values

31 Pages Posted: 29 Mar 2018 Last revised: 17 Dec 2018

See all articles by Elise Payzan-LeNestour

Elise Payzan-LeNestour

University of New South Wales; Financial Research Network (FIRN)

Michael Woodford

Columbia University, Graduate School of Arts and Sciences, Department of Economics; National Bureau of Economic Research (NBER)

Date Written: December 15, 2018

Abstract

How do people perceive outliers? Building on a well-established theory from neuroscience, we conjecture that people are inherently hampered in the way they perceive outliers because the human brain has been designed to devote neural activity to representing the most probable values at the expense of the improbable ones. We find support for this conjecture in a series of controlled laboratory experiments.

Keywords: Neuroeconomics, Tail Risk, Efficient Coding, Normalization Theory, Adaptation, Decision-Making Under Uncertainty

JEL Classification: C91, D87

Suggested Citation

Payzan-LeNestour, Elise and Woodford, Michael, 'Outlier Blindness': Efficient Coding Generates an Inability to Represent Extreme Values (December 15, 2018). Available at SSRN: https://ssrn.com/abstract=3152166 or http://dx.doi.org/10.2139/ssrn.3152166

Elise Payzan-LeNestour (Contact Author)

University of New South Wales ( email )

Australian School of Business
Sydney, NSW 2052
Australia

HOME PAGE: http://www.elisepayzan.com/

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Michael Woodford

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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