arXiv · 2511.13568
Infinite-Horizon Optimal Control of Jump-Diffusion Models for Pollution-Dependent Disasters
Abstract
This paper is devoted to developing a unified framework for stochastic growth models with environmental risk, in which rare but catastrophic shocks interact with capital accumulation and pollution. The analysis is based upon a general Poisson point process formulation, leading to non-local Hamilton-Jacobi-Bellman (HJB) equations that admit closed-form candidate solutions and yield a composite state variable capturing exposure to rare shocks. We consider cases where disaster risk is endogenized through a pollution-dependent intensity and, in the more general cases, it also accommodates for state-dependent events of varying magnitude. Our formulation captures how environmental degradation amplifies macroeconomic vulnerability and strengthens incentives for abatement. From a technical perspective, it provides tractable jump-diffusion control problems whose HJB equation decomposes naturally into capital and pollution components under power-type value function.
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Daria Sakhanda, Joshué Helí Ricalde-Guerrero. 2025-11-17. Infinite-Horizon Optimal Control of Jump-Diffusion Models for Pollution-Dependent Disasters. https://arxiv.org/abs/2511.13568
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