High-dimensional private and social optimal policy valuation model for non-renewable natural resource extraction projects for multivariate public policy decisions

José Carlos Valer Dávila, Vilma Gómez Galarza and Eduardo Court Monteverde

Resources Policy, 2024, vol. 96, issue C

Abstract: We present a model to find the value and sensitivity function associated with the exploitation of a non-renewable natural resource both for the mining company (private optimum) and for the government (social optimum). Improvements over previous studies are achieved by achieving a multivariate model of optimal policy valuation under a Markov decision process with stopping times based on multiple real options, proposing an iterative algorithm of stochastic approximation with supervised dynamic programming decision under Monte Carlo scenarios until obtaining convergence. Applied to a mining project (Tía María) and extended to the total reserves of a country (Peru), it provides additional decision criteria for fiscal public policy, negotiations, concessions, tax levels, community reparations, as well as benefit estimation, discounted from the potential environmental cost in countries abundant in natural resources that wish to achieve sustainability.

Keywords: Valuation of mining projects; Copper; machine learning; Valuation of natural resources; natural resource management; Mining economics; Government policy; Fiscal policy; Sustainable development; Environmental impact assessment; ESG (search for similar items in EconPapers)
JEL-codes: C61 H23 Q32 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:96:y:2024:i:c:s030142072400597x

DOI: 10.1016/j.resourpol.2024.105230

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