Experimental Design Details

The experiment will consist of four treatments, varying the observability of experimentation and whether subjects invest in the same or separate projects.

The strategic treatments (UnobsStrategic and ObsStrategic) closely follows a two-stage variant of the model by Bonatti & Hörner (2017). This two-stage model is specified as follows: There are two agents i = 1,2 that can choose to invest effort x_(i,t )∈[0,1] at t = 1,2 in a project with unknown quality. Doing so entails a private cost of c(x_(i,t )), with c′(x_(i,t )) > 0 and c′′(x_(i,t )) > 0. Both agents get a payoff of Y from that project if a breakthrough occurs. A breakthrough terminates the project. Whether a breakthrough occurs depends on the quality of the project, which can be high or low, and on the effort the two agents invest in that project. p is the common prior that the project is of high quality. Conditional on the project being of high quality, the probability that a breakthrough occurs in period t is given by (x_(1,t )+x_(2,t ))/2 and thus increasing in the effort invested. If the project is of low quality, there will never be a breakthrough. Second-period payoffs are discounted by a common discount factor δ. In UnobsStrategic, agents do not observe their partner’s invested share in the first period. In ObsStrategic, this is observable.

The non-strategic treatments (UnobsNonStrategic and ObsNonStrategic) differ from the strategic treatments, as the two agents work on two different projects. Both agents get a payoff of Y if at least one of the two projects has a breakthrough. This means that agents have the same payoff externality as in the strategic treatments. Conditional on the project being of high quality, the probability that a breakthrough occurs in period t is given by x_(i,t )/2 for the project i is working on. This ensure that the marginal expected payoff from investing is also constant between treatments.

For the experiment, the following parameterization is chosen for all treatments: Y=13, δ=1, c(x_(i,t ))= 2x_(i,t)^2