Participatory Economic Models Through the Lens of Behavioral Economics
Creating a successful strategy for group economic behavior is relatively straightforward. This strategy should fairly distribute benefits among all participants while considering their unique traits and the context in which the group operates.
However, in real life, many of these strategies fail because not everyone follows the rules. Even in short-term experiments, participants may not comply, whether intentionally or due to unforeseen circumstances.
Let’s consider an ideal scenario where all participants agree to rules that promise improvements for both themselves and the group. Here are some possible problems that can occur at this initial stage:
- A participant may pretend to agree to the rules while planning to break them later. They hope to gain benefits without putting in extra effort, even if it means risking exclusion from the group.
- A participant might agree to the rules without fully understanding the possible downsides for themselves. When they encounter these downsides, conflicts can arise.
- The model may not fully consider the unique traits of participants, leading to disagreements later. This issue can occur not only during participant selection but also when individuals assess their own abilities before joining.
- Monitoring adherence to the rules can be challenging. If monitoring isn’t automated, it might require a control group, which can create tension and potentially harm the team, even if rotation systems are used.
In practice, some issues are less critical in open-source development groups or small social systems. These environments often have a large pool of potential volunteers, so losing some participants doesn’t significantly impact the overall strategy. This allows for a stable and adaptable system, even if it’s not always the most effective for everyone involved.
Themes to discuss/implement in “participatory” framework
- Behavioral Economics and Collective Decision-Making
- Monitoring and Compliance in Group Settings
- Understanding Participant Dynamics in Collective Models
- The Role of Trust and Agreement in Economic Models
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Hi Roman, are you essentially referring to behavioural mechanism design?
Yes, any interesting links on topic in context of “participatory”?
Most “Papers” prefer to describe some abstract model and play math games in it
https://arxiv.org/pdf/1406.1790
http://www.arpitaghosh.com/papers/participation.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9779.2012.01561.x
…
or there are some not so formalized “psychological” models discussions.
But probably really interesting will be good combination of both plus analysis of results of real world expirements (some cases from history of humankind review)
No… I don’t know whether there are links on topic in context of “participatory”. Maybe this is a new research field.
Anyway, there is a paper discussing the formalization of Peer-Review-Based Distribution Menchanism. This is a mechanism design paper related to distribution in ParEcon, but not that “behavioural”.
A Formalization of Peer-Review-Based Distribution Menchanism - Articles - Participatory Economy Forum
Author of article itself made right conclusion that it is just another abstract model:
We implicitly assumed that agents are not participating in
collusive agreements. However, there are many reasons why
an agent may lie to benefit a peer. For example, in exchange
for misreporting its evaluation, which may lead to a lower
share for itself, a liar agent may receive a side-payment from
the agent who benefits from the misreporting. Thus, an
exciting direction for future research work is to study which
kinds of collusive behavior may arise and how to avoid them.
However in some fields (when agents cannot make a “conclusion” or there are automatic work measurement or combination part-auto - part-manual estimation) that can be used.
Collusion can be avoided by another mechanism provided that decision makers are all Bayesian risk-neutral expected utility maximisers:
Sharing Rewards Among Strangers Based on Peer Evaluations | Decision Analysis
in reality “utility maximisers” heavily depends on “truth”
by the way - better to put link on researchgate this article free there https://www.researchgate.net/publication/262364795_Sharing_Rewards_Among_Strangers_Based_on_Peer_Evaluations
and it refers to work of some Google employees on “truth and crowds”
https://arxiv.org/pdf/1401.3451
thank you, interesting direction…
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Yes this is an interesting direction, if you want to develop a behavioural mechanism design model related to ParEcon, this topic is importantly relevant. If you have any ideas on this topic (or other topics you think are relevant to ParEcon), please feel free to contact me. I am also interested in these topics.