Abstract
Natural resources such as water, for which the availability to users is random, are often shared according to predefined rules. What determines users’ choice of a sharing rule? To answer this question, we designed an experiment in which subjects: (1) vote on sharing rules; (2) choose the technology that transforms the resource into payoffs; and (3) respond to a survey on their adhesion to principles of fairness. We find that although subjects tend to vote for the sharing rule that is aligned with their self-interest, they become more egalitarian if they report their views on the fairness principles before voting. Furthermore, the adhesion to fairness principles affects the subjects’ votes not directly but rather indirectly through the choice of technology.
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Notes
Other examples of successful collective management include agriculture (see Bennett et al. (2010) for an example of land management), forestry (see Cronkleton et al. 2012 for an example with timber extraction) and fisheries (see McCay et al. (2014) for an example with allocation of shares of fish resources).
Our common pool resource game corresponds to a situation in which agents have to share a common resource available in a limited quantity (i.e., farmers sharing a stock of water). It could also represent some more general situations such as a set of households facing scarce jobs and outputs, therefore necessitating the implementation of rationing rules, see Fenig and Petersen (2017).
In Andalusia (southern Spain), Calatrava and Garrido (2006) provide an example of a crop-based water allocation rule where farmers growing horticultural crops (called “social crops” because they demand more labor) receive a larger amount of water compared to farmers growing extensive crops such as cereals.
Hopfensitz et al. (2018) have also studied catch uncertainty instead of stock uncertainty.
Some studies in the social choice literature have sought to test Harsanyi’s approach to the construction of social utility (Amiel et al. 2009), or whether differences in individuals’ productivity impacts decisions on fair distribution (Konow 2000; Schokkaert and Devooght 2003; Faravelli 2007; Bosmans and Schokkaert 2009).
Note that Fig. 1 was not part of the instructions.
Four different group compositions were possible: three subjects with technology A; two subjects with technology A and one with technology B; one subject with technology A and two with technology B; and three with technology B.
In homogeneous groups, both rules lead to the same ex ante payoff for a given technology, and to approximately the same individual payoff between the two technologies.
Note that subjects vote after choosing their technology - or having one imposed on them - and not prior to doing so. This is because our main objective is precisely to understand subjects’ preferences for a sharing rule when they already know what their technology is. In particular, how being able to choose the technology influences the choice of a sharing rule. Asking subjects to collectively decide on a sharing rule before choosing their technology, or being assigned one, would answer a different research question, related to their preference for a technology (knowing the type of sharing rule that would be implemented).
For the equality of payoff principle, the performance of each rule depends on scarcity. It seems that payoffs are more equal with R2 (priority to B) when the resource is scarce while the reverse holds when it is abundant.
To help subjects digest payoff information, we graph the payoffs for all group compositions in term of technology for both sharing rules (see instructions in Appendix A in ESM). We also provided them with two examples of possible payoffs. We acknowledge that our payoff structure is not strictly monotonic with respect to the CPR game outcomes, but rather weakly monotonic. We discuss this point in Appendix B in ESM.
This amount corresponds to 5.37 euros (as of January 24\(\mathrm{th}\), 2019).
We used oTree to program the experiment (Chen et al. 2016).
Note that, controlling for multiple hypothesis testing (List et al. 2019), we do not detect significant differences between treatments anymore regarding the level of adhesion to these principles (see end of Appendix E in ESM).
Answers to questions 6 and 9 that are affected by the position of the survey have not been included. Questions 4 and 5 and 10 are correlated, and only question 4 has been kept.
We cannot conclude that a causal relationship exists between the adhesion to egalitarian principles and the choice of technology. To prove such a relationship, one possibility could be to consider an instrumental variable approach. It has been shown, for instance, that risk attitudes and social preferences are correlated (Teyssier 2012). In our case, however, we do not have appropriate instruments to implement such an approach.
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We would particularly like to thank Timo Goeschl and Astrid Hopfensitz for their comments on the protocol of the experiment, as well as Alban Thomas. We also thank the participants at the ISUSTCON workshop (Toulouse, 2019), the NAERE conference (Copenhagen, 2019), the ASFEE conference (Toulouse, 2019) and the EAERE conference (Manchester, 2019) for their feedback. This work was carried out under the ATCHA project, funded by the French ANR (ANR-16-CE03-0006), and the C4EAU project (https://c4eau.wordpress.com/), funded by the Région Occitanie. Financial support from the Région Occitanie and the ANR is acknowledged. We also acknowledge funding from ANR under the grant ANR-17-EURE-0010 (Investissements d’Avenir program).
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Ouvrard, B., Ambec, S., Reynaud, A. et al. Sharing rules for a common-pool resource in a lab experiment. Soc Choice Welf 59, 605–635 (2022). https://doi.org/10.1007/s00355-022-01400-y
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DOI: https://doi.org/10.1007/s00355-022-01400-y