Dynamic stochastic optimization for sustainability and management of overconsumption
This paper deals with an intergenerational utility maximization problem for consuming a naturally exhaustible resource. In this context, we are at odds with the unfair standard procedure of applying a time-dependent factor for discounting the utility and introducing a suitable function for penalizing overconsumption. A finite-time horizon dynamic stochastic optimization problem is presented to achieve the desired target. We provide a closed-form solution to the problem which does not lead forcefully to the classical golden rule outcome of not consuming now to save the future. The theoretical findings are validated through extensive numerical experiments, with a parameter set selected based on empirical data. Such experiments highlight that optimal consumption depends strongly on the natural resource regeneration rate and the initial value of the stock. • We study an intergenerational utility maximization problem for resource consumption. • We impose sustainability constraints by penalizing overconsumption. • We adopt a stochastic optimal control approach via Dynamic Programming. • We implement numerical experiments to gain insight into the theoretical results.
Authors
- Rosella Castellano (ORCID: https://orcid.org/0000-0002-4115-8141)
- Roy Cerqueti (ORCID: https://orcid.org/0000-0002-1871-7371)
Institutions
- Unitelma Sapienza University (IT)
- Université d'Angers (FR)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- Communications in Nonlinear Science and Numerical Simulation
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1016/j.cnsns.2025.108960
- Primary Topic
- Climate Change Policy and Economics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Sapienza Università di Roma