Loss Aversion and Lying Behavior: Theory, Estimation and Empirical Evidence

Ellen Garbarino (), Robert Slonim and Marie Claire Villeval
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Ellen Garbarino: University of Sydney

No 10395, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We theoretically show that agents with loss-averse preferences facing a decision to receive a bad financial payoff if they report honestly or to receive a better financial payoff if they report dishonestly are more likely to lie to avoid receiving the low payoff the lower the ex-ante probability of the bad outcome. This occurs due to the ex-ante expected payoff increasing as the bad outcome becomes less likely, and hence the greater the loss that can be avoided by lying. We demonstrate robust support for this role of loss aversion on lying by reanalyzing the results from the extant literature covering 74 studies and 363 treatments, and from two new experiments that vary the outcome probabilities and examine lying for personal gain and for gains to causes one supports or opposes. To measure and compare lying behavior across treatments and studies, we develop an empirical method that estimates the full distribution of dishonesty when agents privately observe the outcome of a random process and can misreport what they observed.

Keywords: experimental economics; loss aversion; dishonesty; econometric estimation; lying (search for similar items in EconPapers)
JEL-codes: C81 C91 D03 (search for similar items in EconPapers)
Pages: 67 pages
Date: 2016-11
New Economics Papers: this item is included in nep-cbe
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Forthcoming - revised version published as 'Loss Aversion and Lying Behavior' in: Journal of Economic Behavior and Organization, 2019, 158, 379-393

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Related works:
Working Paper: Loss Aversion and lying behavior: Theory, estimation and empirical evidence (2016)
Working Paper: Loss Aversion and lying behavior: Theory, estimation and empirical evidence (2016)
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