Estimating the extent of deceitful behaviour using crosswise elicitation models

Abstract

ABSTRACT Eliciting deceitful behaviour is a daunting task. Respondents oftentimes conceal wrongdoings and refrain from truthfully responding to sensitive questions. In this work, we employ advancements in randomized response techniques to overcome the neglect of respondents to truthfully reveal deceitful behaviour. Our results report that the studied crosswise elicitation model reveals high levels of deceitful behaviour (around 60% admitted deceit by respondents). If respondents can be convincingly assured of their anonymity, the crosswise models (CMs) outperform several variants of elicitation techniques such as direct questioning and item-sum. We also emphasize the use of CMs to generalize findings from laborious experiments to larger populations.