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Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species risk

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  • Springborn, Michael R.

Abstract

This article explores adaptive management (AM) for decision-making under environmental uncertainty. In the context of targeting invasive species inspections of agricultural imports, I find that risk aversion increases the relative value of AM and can increase the rate of exploratory action. While calls for AM in natural resource management are common, many analyses have identified modest gains from this approach. I analytically and numerically examine the distribution of outcomes from AM under risk neutrality and risk aversion. The inspection decision is framed as a multi-armed bandit problem and solved using the Lagrangian decomposition method. Results show that even when expected gains are modest, asymmetry in the distribution of outcomes has important implications. Notably, AM can serve to buffer against large losses, even if the most likely outcome is a small loss.

Suggested Citation

  • Springborn, Michael R., 2014. "Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species risk," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 226-242.
  • Handle: RePEc:eee:jeeman:v:68:y:2014:i:2:p:226-242
    DOI: 10.1016/j.jeem.2014.05.004
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    References listed on IDEAS

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    Cited by:

    1. Springborn, Michael R. & Lindsay, Amanda R. & Epanchin-Niell, Rebecca S., 2016. "Harnessing enforcement leverage at the border to minimize biological risk from international live species trade," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 98-112.
    2. repec:spr:annopr:v:261:y:2018:i:1:d:10.1007_s10479-017-2610-4 is not listed on IDEAS
    3. repec:bla:ecorec:v:93:y:2017:i:301:p:277-301 is not listed on IDEAS
    4. repec:oup:renvpo:v:12:y:2018:i:1:p:92-112. is not listed on IDEAS

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