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Forward-Looking Belief Elicitation Enhances Intergenerational Beneficence

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Abstract

One of the challenges in managing the Earth’s common pool resources, such as a livable climate or the supply of safe drinking water, is to motivate successive generations to make the costly effort not to deplete them. In the context of sequential contributions, intergenerational reciprocity dynamically amplifies low past efforts by decreasing successors’ rates of contribution. Unfortunately, the behavioral literature provides few interventions to motivate intergenerational beneficence. We identify a simple intervention that motivates decision makers who receive a low endowment. In a large online experiment with 1378 subjects, we show that asking decision makers to forecast future generations’ actions considerably increases their rate of contribution (from 46% to over 60%). By shifting decision makers’ attention from the immediate past to the future, the intervention is most effective in enhancing intergenerational beneficence of subjects who did not receive a contribution from their predecessors, effectively neutralizing negative intergenerational reciprocity effects. We provide suggestive evidence that the attentional channel is the main channel at work.

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Data Availability

Data used in this study are accessible at https://data.mendeley.com/datasets/ycstzykj58/2. Further information regarding the code used and the data produced are available from the corresponding author upon request.

Notes

  1. Another effective nudge in the related literature is to set the sustainable option as default (Böhm et al. 2020).

  2. Studies that explored donations in a dictator game with different α /d ratios find that, when α /d = 2, the average contribution increases to somewhat above 50%, from 27% in the case of α = d (Andreoni and Vesterlund, 2001). In a field experiment on matching in a charitable contribution (Karlan and List, 2007), the effect of the multiplier appears to asymptote at about 2.

  3. A closely related practice in the literature is to keep the endowment of the decision maker constant after generous and non-generous predecessors to provide decision makers with the same ability to leave money for the future (Bang et al. 2017; Wade-Benzoni, 2002). To achieve this, the generous and non-generous predecessors have different endowments and contribute different proportions but the same amount (e.g., a generous predecessor contributes $6 out of $8 while a non-generous one contributes $6 out of $24). This practice keeps the same endowment for decision makers while the endowments differ between generations ($9 vs. $8 or $24) and differ between predecessors of different decision makers ($8 vs. $24). Our setting has the same two levels of endowments, high and low, in all generations to increase comparability across generations and decision makers. To limit the impact of the endowment on the decision maker’s ability to contribute, we set the contribution to be a dichotomous decision with a modest amount.

  4. The labels in the brackets were not shown to the subjects, the same for (b) and (c).

  5. The implementation of simulated decisions was not communicated with our subjects. The acceptability of such a practice of providing incomplete information has been discussed (Charness et al. 2021; Colson et al. 2016; Hey, 1998). Our simulation aimed to mimic what would have happened if the subjects had made decisions in a predetermined order. We do not consider this practice problematic because the subjects were not misled to make sub-optimal decisions. Trying one’s best to forecast is always in the best interest of the subjects, knowing or not knowing the unrevealed details regarding our implementation.

  6. The proportion of contribution is greater if the belief elicitation is not incentivized though the difference is not statistically different (Chi-square = 1.15, p = 0.28).

  7. Assuming the expected contribution rate of generation \(i\) being \({P}^{i}\), then \({P}^{i+1}={P}^{i}\times {p}_{B}+\left(1-{P}^{i}\right)\times {p}_{A}={P}^{i}\times \left({p}_{B}-{p}_{A}\right)+{p}_{A}\), and the contribution rate of generation \(i+k\) is \({P}^{i+k}={P}^{i}\times {\left({p}_{B}-{p}_{A}\right)}^{k}+\sum_{1}^{k}[{p}_{A}\times {\left({p}_{B}-{p}_{A}\right)}^{k-1}]\). The long-run proportion can be obtained by \(\underset{\mathrm{k}\to \infty }{\mathrm{lim}}{P}^{i+k}={p}_{A}/(1-({p}_{B}-{p}_{A}))\).

  8. Please see Table S7 in Appendix III for results and discussion regarding how the reported relevance correlates with the contribution decision.

  9. This finding is consistent with a previous study (Wade-Benzoni, 2002), showing that information suggesting decision norms has little impact when the decision maker is not materially affected by the decisions disclosed in the information.

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Acknowledgements

The study protocol of this paper was approved by the Institutional Review Board at Columbia University (protocol number IRB-AAAB1301). The research leading to these results received funding from the European Research Council under the European Community’s Programme “Ideas”—Call identifier: ERC-2013-StG/ERC Grant Agreement No. 336703—project RISICO “RISk and uncertainty in developing and Implementing Climate change pOlicies”, the Global Thinking Foundation, Yale NUS College through grant number R-607-264-235-121, National Natural Science Foundation of China (Grant 72103015), the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement No. 336155—Project COBHAM" The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies", and US National Science Foundation (Grant SES-DRMS 2049796). We thank the editor and two anonymous reviewers for their constructive comments and queries that considerably improved the paper. We thank Matthew Sisco for his technical support.

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V.B., F.D., N.L., M.T., and E.U.W. designed the experiment. V.B., N.L., and M.T. carried out the experiments. N.L. and V.B. analyzed the results. V.B., F.D., N.L., M.T., and E.U.W. wrote the paper.

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Correspondence to Ning Liu.

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Bosetti, V., Dennig, F., Liu, N. et al. Forward-Looking Belief Elicitation Enhances Intergenerational Beneficence. Environ Resource Econ 81, 743–761 (2022). https://doi.org/10.1007/s10640-022-00648-3

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