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Behavioral and Neuroeconomics of Environmental Values

Author

Listed:
  • Phoebe Koundouri
  • Barbara Hammer
  • Ulrike Kuhl
  • Alina Velias

Abstract

Identifying mechanisms of real-life human decision-making is central to inform effective, human-centric public policy. Here, we report larger trends and synthesize preliminary lessons from behavioral and neuroeconomic investigations focusing on environmental values. We review the currently available evidence at different levels of granularity, from insights of how individuals value natural resources (individual level), followed by evidence from work on group externalities, common pool resources, and social norms (social group level), to the study of incentives, policies, and their impact (institutional level). At each level, we identify viable directions for future scientific research and actionable items for policy-makers. Coupled with new technological and methodological advances, we suggest that behavioural and neuroeconomic insights may inform effective strategy to optimize environmental resources. We conclude that the time is ripe for action, to enrich policies with scientifically grounded insights, making an impact in the interest of current and future generations.

Suggested Citation

  • Phoebe Koundouri & Barbara Hammer & Ulrike Kuhl & Alina Velias, 2022. "Behavioral and Neuroeconomics of Environmental Values," DEOS Working Papers 2227, Athens University of Economics and Business.
    • Handle: RePEc:aue:wpaper:2227
    as

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    References listed on IDEAS

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    1. Alpizar, Francisco & Carlsson, Fredrik & Naranjo, Maria A., 2011. "The effect of ambiguous risk, and coordination on farmers' adaptation to climate change — A framed field experiment," Ecological Economics, Elsevier, vol. 70(12), pages 2317-2326.
    2. Hunt Allcott & Todd Rogers, 2014. "The Short-Run and Long-Run Effects of Behavioral Interventions: Experimental Evidence from Energy Conservation," American Economic Review, American Economic Association, vol. 104(10), pages 3003-3037, October.
    3. Ruben Durante & Louis Putterman & Joël Weele, 2014. "Preferences For Redistribution And Perception Of Fairness: An Experimental Study," Journal of the European Economic Association, European Economic Association, vol. 12(4), pages 1059-1086, August.
    4. Nikos K. Logothetis & Jon Pauls & Mark Augath & Torsten Trinath & Axel Oeltermann, 2001. "Neurophysiological investigation of the basis of the fMRI signal," Nature, Nature, vol. 412(6843), pages 150-157, July.
    5. Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Machine Learning Methods for Demand Estimation," American Economic Review, American Economic Association, vol. 105(5), pages 481-485, May.
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