I use a variation of the observed game presented by Gneezy et al. (2018). In my game, two participants play sequentially. In the beginning, the first-mover (P1) click on a box in the computer, and a color (Orange or Black) is revealed. The probability of drawing Orange is 0.2 and black 0.8. After the first-mover observes the draw, they are asked to report the observed color to the second-mover (P2). Once the second-mover learns this report, they are asked to click on a box in the computer that reveals a color; the second mover reports the observed color. The probabilities of drawing each color are the same as for the first-mover.
It is important to mention that the draw is only known by the participant and the experimenter, but not by other participants. Participants' payoffs depend on both the reports of the two members of a dyad. In particular, if any of the two participants report an Orange, both of them get 4 pounds. Otherwise, both gain 0.5 pounds. I use this payoff structure because I am interested in the extensive margin.
In the Baseline, I hypothesized that the first-movers will take advantage of their position and, therefore, will avoid the cost of lying. To attribute truth-telling to the possibility of having another participant lying on their behalf, I make the report of the second mover a random variable instead of a decision made by P2. Specifically, in the treatment No Avoidance, after the second-mover learns the report of P1, he or she clicks on a button that draws a color, and the computer reports the actual value automatically. Thus, in No Avoidance, the first-mover can not rely on second-mover incentives to lie.
In No Avoidance, the only thing that changes compared with the Baseline is the beliefs about the second-mover report. However, I am interested in knowing whether this result will hold even when dropping the positive externality generated by the first-mover’s report. With the previous treatments, I do not know whether the report in No Externalityis purely by the fact that it is not possible to use P2 as an implicit agent or because P1 is using the handy excuse of causing a benefit on P2. In other words, it may be the case that in the Baseline, the first-mover is not using the positive externality as a justification because both participants generate positive externalities and then take full advantage of their position. In contrast, in No Avoidancethe positive impact of P1’s report is more salient.
Hence, in the treatment No Externality, I modify the payoff scheme to eliminate the positive externality generated by P1 in previous treatments. In No Externality, the game sequence and main game features, including the pecuniary payoffs for the first-mover, are identical to those in No Avoidance. However, the payoff for P2 depends only on the color chosen by the computer. Specifically, if Orange, he or she gets 4 pounds; otherwise, he or she gets 0.5 pounds.
In No Avoidance and No Externality, I control for different components that can explain why the first-mover decides to report truthfully in Baseline. However, there is another component that worth ruling out: the fact that participants play sequentially. In this treatment, Simultaneous, participants decide at the same time which color to report. The impact of this treatment on first-mover strategy is similar to No Avoidance. However, it allows me to understand the role of the moral signal that the first mover sends about whether it is correct to lie or not. Thus, this treatment makes it possible to confirm the first-mover’s willingness to avoid the cost of lying and the impact of the moral signal on second-mover behavior.