Quickest Detection of Ecological Regimes for Natural Resource Management

Neha Deopa () and Daniele Rinaldo ()
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Neha Deopa: University of Exeter Business School
Daniele Rinaldo: University of Exeter Business School

Environmental & Resource Economics, 2024, vol. 87, issue 5, No 10, 1327-1366

Abstract: 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, study its response to regime shift detection and show the generality of our framework by extending our results to other decision makers and functional forms. We apply our framework to the case of the Cantareira water reservoir in São Paulo, Brazil, and study the events that led to its depletion and the consequent water supply crisis.

Keywords: Regime shifts; Natural resources; Quickest detection; Uncertainty (search for similar items in EconPapers)
JEL-codes: D42 D81 Q20 Q57 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10640-024-00868-9

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