EconPapers    
Economics at your fingertips  
 

Loss Aversion and lying behavior: Theory, estimation and empirical evidence

Ellen Garbarino, Robert Slonim and Marie Claire Villeval ()
Additional contact information
Ellen Garbarino: The University of Sydney [Sydney]

Working Papers from HAL

Abstract: We theoretically show that loss-averse agents are more likely to lie to avoid receiving a low payoff after a random draw, the lower the ex-ante probability of this bad outcome. The ex-ante expected payoff increases as the bad outcome becomes less likely, and hence the greater is the loss avoided by lying. We demonstrate robust support for this theory by reanalyzing the results from the extant literature and with two new experiments that vary the outcome probabilities and are run doubleanonymous to remove reputation effects. To measure lying, we develop an empirical method that estimates the full distribution of dishonesty

Keywords: experimental economics; lying; loss aversion; dishonesty; econometric estimation (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-exp and nep-hpe
Date: 2016
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01404333v3
References: Add references at CitEc
Citations: View citations in EconPapers (10) Track citations by RSS feed

Downloads: (external link)
https://halshs.archives-ouvertes.fr/halshs-01404333v3/document (application/pdf)

Related works:
Working Paper: Loss Aversion and lying behavior: Theory, estimation and empirical evidence (2016) Downloads
Working Paper: Loss Aversion and Lying Behavior: Theory, Estimation and Empirical Evidence (2016) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:halshs-01404333

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().

 
Page updated 2019-10-16
Handle: RePEc:hal:wpaper:halshs-01404333