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Quickest Detection of Ecological Regimes for Dynamic Resource Management

Neha Deopa () and Daniele Rinaldo

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Abstract: We study the stochastic dynamics of natural resources under the threat of ecological regime shifts. We establish a Pareto optimal framework of regime shift detection under uncertainty that minimizes the delay with which economic agents become aware of the shift. We integrate ecosystem surveillance in the formation of optimal resource extraction policies. We fully solve the case of a profit-maximizing monopolist and provide the conditions that determine whether anticipating detection of an adverse regime shift can lead to an aggressive or a precautionary extraction policy, depending on the interaction between market and environmental parameters. We compare the monopolist's policy under detection to a social planner's. We apply our framework to the case of the Cantareira water reservoir in S\~ao Paulo, Brazil, and study the events that led to its depletion and the consequent water supply crisis.

Date: 2020-05, Revised 2023-10
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Handle: RePEc:arx:papers:2005.11500