Experimental Design

People are randomly matched into pairs and assigned one of two roles: Sender and Receiver (Called persons A and B in the experiment). Each player observes two boxes on their screen. One of the boxes is red, the other box is blue. It is common knowledge that each one of these two boxes contains 10 identical cards. Each card gives a certain amount of points to the Sender and a certain amount of points to

the Receiver. Importantly, the Sender can observe what points are written on the cards in the two boxes while the Receiver cannot.

In the instructions, we explain to both players that the two boxes can contain the following cards:

"With a probability of 75%, i.e., on average in 3 of 4 cases,

one of the boxes contains 10 cards that each give

10 points to person A and 10 points to person B,

and the other box contains 10 cards that each give

15 points to person A and 15 points to person B.

With a probability of 25%. i.e., on average in 1 of 4 cases,

one of the boxes contains 10 cards that each give

10 points to person A and 10 points to person B,

and the other box contains 10 cards that each give

20 points to person A and 0 points to person B."

First, person A will be asked to recommend to person B one of the two boxes to pick 10 cards from. They can either recommend the blue or the red box.''

The Sender is asked which one of the two boxes to recommend to the Receiver. The recommendation of the Sender is not binding and is displayed to both players for the remainder of the experiment. The Receiver then has to choose how many cards to pick from which box. They are aware that they will pick 10 cards in total.

TREATMENTS.

We have a between-subject design with two treatments: NOCOMM and COMM.

In both treatments, the Sender recommends one of the boxes to the Receiver. The Receiver observes the recommendation and makes their choice of 10 cards (from all cards from the red box to all cards from the blue box, with any possible integer combination in between).

In COMM, both matched participants additionally enter an open chat *after* the Sender has made the recommendation and *after* the Receiver has made their first (preliminary) choice. The Sender is not informed about the Receiver's choice of cards. The Receiver thus makes their second choice during/after the communication. Both players are informed that the Receiver will have the opportunity to revise their choice. This experiment aims to compare how participants' suspicion changes with and without communication. We include the first choice in COMM to have additional information on what *exact aspects* of communication affect suspicion: the anticipation (i.e., the fact) of communication versus the contents thereof. In COMM, only the second choice is incentivized.

TIMELINE.

1. Participants read general instructions and answer control questions.

2. The Sender recommends one of two boxes.

3. The Receiver observes the Sender's recommendation.

4 The Receiver enters in integers how many cards to pick from which box. This choice is not revealed to the Sender.

5 (COMM). Participants enter an open chat. On the same screen, the Receiver enters in integers how many cards to pick from which box.

6. We elicit beliefs. Belief elicitation for the Sender is "How many cards do you think the other person has drawn from the red (blue) box?" based on whether they recommended a red (blue) box. Belief elicitation for the Receiver is

"Based on your subjective estimation - what points do you think were in the two boxes?" and "Please tell us, how likely you think it is that the other person has recommended the box with cards giving each one of you 10 points per card."

7. Participants fill out the questionnaire.

HYPOTHESES.

We formulate the following hypotheses.

First of all, we need to establish:

Hypothesis 1 (Suspicion). Without communication, Receivers significantly deviate from the Senders' recommendations, i.e., display significant levels of suspicion.

The focus of the paper is the impact of communication on suspicion. Two possible countervailing effects may play a role. On the one hand, communication might be beneficial, i.e., increase Senders' trustworthiness such that suspicion decreases. On the other hand, communication might result in more suspicion by making Senders' potentially misaligned incentives more salient and leading Receivers to think more about Senders' motives. Alternatively, the Sender might communicate in a way that raises suspicion, e.g., by making contradicting statements or by not giving satisfactory answers to questions by the Receiver. We, therefore, formulate a two-sided hypothesis on the difference between suspicion in NOCOMM and suspicion in COMM in the second, final decision of the Receiver.

Hypothesis 2 (Communication effect on suspicion). With communication, Receivers deviate more or less from the Senders' recommendations.

To disentangle these effects, we will use the within-subject differences in the Receivers' level of suspicion before and during/after the chat. Furthermore, we will analyze the communication content. We expect that a high level of suspicion/negativity in the chat will correspond to higher levels of suspicion in terms of the Receivers' choices and vice versa.

PREPARATION.

In preparation for this experiment, we conducted a pretest where in 100% of cases one box contains (10,10) payoffs and the other box contains (12,12) payoffs. The pretest ensures us that the noise generated by subjects' confusion and/or misunderstanding of the instructions is minimal and hence the Receivers' deviations from the Senders' recommendations indeed capture suspicion. We collected 15 independent observations (30 subjects). On average, Receivers deviated by less than one card out of ten. Importantly, 73.3% of Receivers did not deviate at all. We specifically invited newly recruited subjects who never participated in the experiments before to document the upper bound of noise in participants' behavior.

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Due to the independent data structure, we will rely on two-sided Mann-Whitney U tests and regression analyses to test the hypotheses described above. For the non-parametric tests, we will use a matched pair of subjects as the unit of observation. We will analyze communication content to shed further light on communication effects on suspicion in humans. We plan to use (unsupervised) machine learning methods to analyze chat data. The specific computation method depends on the characteristics of actual data (e.g., length of the messages, number of topics within the messages, variance across the messages, etc.). Furthermore, we plan to use the regression analysis to account for the communication characteristics.