Reclamation of a Resource Extraction Site Model with Random Components
Ekaterina Gromova (),
Anastasiia Zaremba and
Nahid Masoudi
Additional contact information
Ekaterina Gromova: Transport and Telecommunication Institute, LV-1019 Riga, Latvia
Anastasiia Zaremba: Faculty of Applied Mathematics and Control Processes, St. Petersburg State University, 199034 St. Petersburg, Russia
Mathematics, 2022, vol. 10, issue 24, 1-15
Abstract:
We compute the cooperative and the Nash equilibrium solutions for the discounted optimal control problem in a two-player differential game of reclamation of a resource extraction site, where each firm’s planning horizon presents the period that extraction of the resources from their site is economically viable. Hence, the planning horizon is defined by a random duration determined on the infinite time horizon. The comparison of the cooperative and Nash solutions and also the comparative statics are provided numerically. We also define the concept of “normalized value of cooperation” and explain how this concept could help us to better characterize the losses the players will face if they continue to refrain from cooperation.
Keywords: differential game; random time horizon; open-loop strategies; resource extraction; reclamation; clean-up of extraction site (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2227-7390/10/24/4805/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/24/4805/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:24:p:4805-:d:1006460
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().