A1 Journal article – refereed

Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice




List of Authors: Halko Marja-Liisa, Lappalainen Olli, Sääksvuori Lauri

Publisher: Elsevier

Publication year: 2021

Journal: Journal of Economic Behavior and Organization

Journal name in source: Journal of Economic Behavior and Organization

Volume number: 188

ISSN: 0167-2681

DOI: http://dx.doi.org/10.1016/j.jebo.2021.04.009


Abstract

We investigate the feasibility of inferring economic choices from simple biometric non-choice data. We employ a machine learning approach to assess whether biometric data acquired during sleep, naturally occurring daily chores and participation in an experiment can reveal preferences for competitive and team-based compensation schemes. We find that biometric data acquired using wearable devices enable equally accurate out-of-sample prediction for compensation-scheme choice as gender and performance. Our results demonstrate the feasibility of inferring economic choices from simple biometric data without observing past decisions. However, we find that biometric data recorded in naturally occurring environments during daily chores and sleep add little value to out-of-sample predictions.


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Last updated on 2021-19-10 at 13:00