International Society of Dynamic Games

Dynamic Games and Applications Seminar

Assessing the impact of carbon quota allocation on emission reduction and advertising efforts in supply chain

Apr 10, 2025   11:00 AM — 12:00 PM (Montreal time)

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We analyze carbon quota allocation (grandfathering vs. benchmarking) in cap-and-trade systems on supply chain dynamics. Differential game models reveal benchmarking amplifies emission reduction and advertising efforts, accelerating product goodwill growth. Rising permit prices incentivize decarbonization but unevenly affect profits. Per-unit benchmarking fosters collaboration, benefiting all members, whereas grandfathering traps less eco-friendly firms in low-investment cycles.

Dynamic Games and Applications Seminar

Investment in Abatement Capacity when Consumers Value the Environmental Performance of the Supply Chain

Mar 20, 2025   11:00 AM — 12:00 PM (Montreal time)

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In this paper, we examine abatement investment and pricing in a supply chain where consumers value environmental performance. The product’s green reputation depends on its pollution rate relative to a declining industry standard. The manufacturer manages abatement investment, with optional cost-sharing by the retailer. Cost-sharing achieves a Pareto-optimal outcome but may increase total emissions by boosting demand. Faster declines in the industry standard reduce abatement investment. Firms with lower initial green reputation – “brown firms” – struggle to catch up, while firms with higher initial states benefit from a cycle of increased investment, enhanced abatement capacity, reduced emissions, and greater goodwill gains.

(With Elena Parilina and Georges Zaccour.)

Dynamic Games and Applications Seminar

Optimal Policies in Large Population Games with Applications to Epidemic Control

Mar 13, 2025   11:00 AM — 12:00 PM (Montreal time)

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COVID-19 pandemic showed that while designing policies to mitigate an epidemic, regulators should consider the response of large number of interacting agents to these policies. To address this, we propose a Stackelberg mean field game (MFG) model between a government who optimizes mitigation policies and many non-cooperative individuals who chooses their socialization levels to control their jumps between different health states. Nash equilibrium response to the policies is approximated with an MFG. We will give equilibrium characterization and introduce a numerical approach based on machine learning tools. Finally, we will discuss an extension where an underlying network among individuals is implemented via graphon game.