Disentangling Device and Observability Effects in Dishonesty: Evidence from Probability-Equivalent Randomization Tasks

The study consists of a series of incentivized laboratory experiments in which participants observe realizations from randomization devices and report the outcome for monetary compensation. The objective is to study how the structure and implementation of the randomization device affect dishonest reporting, holding constant the probability distribution of outcomes and the associated payoffs.

Participants are assigned to one of several experimental conditions that vary along three main dimensions. First, we compare binary and multi-outcome environments by implementing coin-based and die-based tasks with equivalent winning probabilities. Second, we vary the cognitive complexity of the randomization process by contrasting simple devices with composite mechanisms that generate identical distributions through sequential steps. Third, we manipulate the format of the randomization device. The latter distinguishes between conditions in which participants generate outcomes themselves (e.g., by flipping a coin or rolling a die) and conditions in which outcomes are generated by the computer within the experimental software.

When outcomes are generated by the participant, only reported values are observed, and dishonesty can be inferred only from aggregate deviations from the theoretical distribution. When outcomes are generated by the computer, the realization is recorded by the software, allowing the researcher to compare realized and reported outcomes at the individual level. Although all decisions remain anonymous and unsupervised, the computer-generated implementation may affect participants’ perception of privacy.

Each participant completes multiple independent rounds of the task within a single session, and monetary payoffs depend on reported outcomes. The design does not involve deception and maintains identical incentives across comparable treatments.

2026-03-30

2026-04-30

The primary outcomes are the reported outcome in each round. At the aggregate level, we analyze mean reported values and distributional deviations. In treatments with observable outcomes, we additionally construct individual-level measures of misreporting, including indicators for any misreporting, upward misreporting, and maximal misreporting.

The reported outcome constitutes the fundamental behavioral variable and is recorded either as a binary indicator (in coin-based tasks) or as a numerical value (in multi-outcome tasks). Aggregate dishonesty is constructed by comparing the empirical distribution of reported outcomes with the theoretical distribution implied by truthful reporting. This includes differences in mean reported outcomes relative to the expected value under honesty and formal distributional comparisons.

In treatments where outcomes are generated and recorded by the computer, individual-level dishonesty is directly observed. A binary indicator of dishonesty is defined as whether the reported outcome differs from the realized outcome. In addition, the magnitude of dishonesty is measured as the difference between reported and true outcomes, allowing for an analysis of the frequency, intensity and motives of misreporting.

Secondary outcomes include measures related to the cognitive and individual correlates of reporting behavior. These comprise response times during the reporting decision, individual characteristics such as gender, measures of cognitive ability, and survey-based measures capturing moral attitudes, risk preferences, and background characteristics (including field of study and demographics).

Response times are recorded for each reporting decision and will be used as a proxy for the cognitive effort associated with reporting. In particular, longer response times may reflect the additional cognitive cost of manipulating a reported outcome relative to truthfully reporting the realized value.

Individual characteristics are used to study heterogeneity in dishonest behavior. Gender will be included as a pre-specified dimension of heterogeneity, given its relevance in the literature on ethical decision-making. Cognitive ability measures collected in the post-experimental questionnaire will be used to examine whether the propensity to misreport varies with participants’ ability to process probabilistic or sequential tasks.

Survey-based measures of moral attitudes will be constructed from questionnaire responses and used to analyze whether individual differences in moral views are associated with reporting behavior. Risk preferences and field of study will be included as additional covariates in heterogeneity analyses.

These secondary outcomes are not the primary focus of the study but are intended to provide complementary evidence on the mechanisms underlying dishonest reporting and to explore potential sources of heterogeneity across participants.

The study employs a between-subjects experimental design in which participants are randomly assigned to one of eight treatments. Each participant takes part in a single experimental session and is exposed to only one treatment condition. Within each session, participants complete five independent repetitions of a reporting task in which they observe the realization of a randomization device and report the outcome for monetary compensation.

The treatments vary along two key dimensions. The first dimension concerns the structure of the randomization device. Participants are assigned either to binary-outcome tasks or to multi-outcome tasks, and within each category, the randomization process is implemented either through a simple device or through a sequential composite mechanism that generates an equivalent probability distribution. The second dimension concerns the mode of implementation of the randomization device. In some treatments, the outcome is generated by the participant using a physical device (such as a coin or die), while in others the outcome is generated by the experimental software (z-Tree).

In all treatments, the probability distribution of outcomes and the associated payoff structure are held constant across comparable conditions. This ensures that any differences in reporting behavior can be attributed to the structure or implementation of the randomization device rather than to differences in expected monetary incentives.

Participants receive monetary payoffs based on their reported outcomes in one randomly selected round. The experimental design does not involve deception, and all decisions are made anonymously and without direct supervision by the experimenter.

Not available

Participants are randomly assigned to treatments through a computerized randomization process that ensures that each participant has an equal probability of being allocated to any of the treatment conditions. Randomization is performed independently for each participant and does not depend on participant characteristics or on the behavior of other participants.

The unit of randomization is the individual participant. Each participant is assigned to exactly one treatment and remains in that treatment throughout the session.

No

480 participants

Each of the 480 participants completes five independent rounds of the reporting task, resulting in a total of 2,400 observations at the decision level.

The sample is evenly distributed across the eight treatments, with 60 participants assigned to each treatment condition. Since each participant completes five rounds, each treatment yields 300 observations at the decision level.