Experimental Design Details
Basic structure and decision task
We will be conducting this experiment online on the Prolific platform. Our exclusion restrictions are UK participants only with an approval rate of >95% on previous submissions and at least 100 minimum submissions.
Participants will be a part of the modified version of the IGG. Each participant will be randomly allocated to a sequence of participants, some participating before them and some (potentially) after them. There is an 80% chance that a participant will play after them and a 20% chance that the sequence stops after them. Each participant’s position in the sequence is random and unknown to participants. We will determine the length of each sequence before the experiment using a random number generator.
On Prolific, we will recruit participants of the next generation for all active sequences in all treatments once all data are collected for the current generation, which will be handled automatically by the software. We will stop recruiting new participants to a sequence when it becomes inactive, i.e. when its maximum length has been reached.
Participants will receive 20 points, and will choose to allocate these points to three different accounts A, B and C. All 20 points must be allocated by participants before continuing. Any points allocated to the participant will be paid as a bonus payment at a rate of 1 point = £0.04. As we describe above, the accounts will differ in who benefits from their allocation, depending on the treatment. In our main condition (BIG-FIG):
Account A: Points allocated to this account will be given to the participant. Points in this account will not be multiplied.
Account B: Points allocated to this account will be multiplied by 3 and then given to the participant directly before this participant in the sequence.
Account C: Points allocated to this account will be multiplied by 5 and given to the participant directly after this participant in the sequence (which occurs with an 80% chance).
Note: The multipliers in each account are the same across all treatments. In CUR, amounts contributed to Accounts B(C) will be given to another participant taking part in the study. In FIG+2, the amount allocated to Account C will be given to a participant taking part two “generations” after the decision-maker.
Depending on the treatment (see above), participants may also receive information about what other participants in the study did prior to submitting their allocations.
First participant’s information
In our experiment, participants do not know their position in the sequence. We inform all participants that they could be the first participant in a sequence. In this case, the information they will see on the information screen will not come from prior participants in their own sequence. Rather we will show information on participants from some additional pre-experiments (seed sequences). These will include the same decision task but will have a fixed length. In total, we will run 50 seed sequences using the BIG-FIG condition with a fixed length of 7. We use the decisions of players in positions 4, 5, and 6 to generate the information shown in the main sequences. For each main sequence, there is a corresponding seed sequence.
In treatments where this is relevant, we also inform participants that if they are in the first position of a sequence, their BIG contribution will still go to a real participant specifically invited for this purpose, and they will receive a FIG bonus originating from this participant. Crucially, we inform participants that they will not be able to infer their position in the sequence from looking at the information/decision screens.
Attention checks and comprehension questions are included on every instruction screen. Participants are only able to proceed to the following screen once they answer the comprehension questions correctly.
After this, the participants make their allocation decisions. (To see how each treatment differs in the allocation space and information space, see the table in the interventions section.)
Before the end of the experiment, participants will be asked several questions about their decisions, and their beliefs. In five of these questions, they will be incentivised to state accurate beliefs, as we will award them 1 bonus point for each correct guess. These include:
How they think the participant before them allocated their points
How they think the participant after them will allocate their points
How they think the participant two steps before them allocated their points
How they think the participant three steps before them allocated their points
The Krupka & Weber social norm coordination task for different allocations.
Further questions pertain to participants' demographics (age, gender, race). Furthermore, we use basic incentives choice paradigms to elicit basic economic preferences
Risk preferences: A version of the Eckel and Grossman (2007) lottery selection task.
Pro-social preferences. We will ask participants to pick a charity from a dropdown list. Then using the elicitation task in Exley (2015), participants will make decisions between them receiving 10 points and the charity receiving some points (where points increase by 2 each progressive row). The row where the participants switch to giving to their preferred charity is an indication of their altruistic preferences, with higher switching points indicating more self regarding preferences.
Other regarding preferences: Adapted survey questions from Falk (2016) for reciprocity, punishment, patience, and altruism.
Basic questions about task comprehension and motivation
An attention check
We will use data collected via the questionnaire as control variables in regressions and for exploratory analysis e.g. to understand heterogenous treatment effects and the roles of beliefs for our results.
Other Notes (Follow-up Treatments):
If we find that contributions to account C (on either the extensive or intensive margins) are significantly different in BIG-FIG full info compared to BIG-FIG+2, then we will consider conducting a follow-up experiment (conditional on funding).
We will run a new treatment (BIG-FIG full info 80% FIG). This treatment is the same as BIG-FIG full info, except there is only an 80% chance that the FIG (Account C) actually gets delivered. Meaning there is only a 64% chance that FIG occurs (80% next generation exists * 80% delivery). This treatment will help allow us to untangle the behavioral differences as to why contributions to account C are lower in BIG-FIG+2 compared to BIG-FIG full info. Whether it is the reciprocity link being broken between generations, or due to a lower chance of FIG (account C) occurring 64%.