Abstract

While single-level Nash equilibrium problems are quite well understood nowadays, less is known about multi-leader multi-follower games. However, these have important applications, e.g., in the analysis of electricity and gas markets, where often a limited number of firms interacts on various subsequent markets. In this paper, we consider a special class of two-level multi-leader multi-follower games that can be applied, e.g., to model strategic booking decisions in the European entry-exit gas market. For this nontrivial class of games, we develop a solution algorithm that is able to compute the complete set of Nash equilibria instead of just individual solutions or a bigger set of stationary points. Additionally, we prove that for this class of games, the solution set is finite and provide examples for instances without any Nash equilibria in pure strategies. Finally, we apply the algorithm to a case study in which we compute strategic booking and nomination decisions in a model of the European entry-exit gas market system.

Highlights

  • In this contribution we consider a class of two-level multi-leader multi-follower games (MLFG)

  • For this class of MLFGs, we develop an algorithm that provably computes the exact set of Nash equilibria

  • We show that the solution set is finite and provide examples for instances without pure strategy Nash equilibria

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Summary

Introduction

In this contribution we consider a class of two-level multi-leader multi-follower games (MLFG). We analyze the case of strategic capacity choices prior to quantity competition (à la Cournot) at several subsequent spot markets, which results in a classical MLFG setup. Several subsequent contributions provide characterizations and algorithms allowing to determine pure strategy Nash equilibria in asymmetric setups of strategic capacity choice prior to Cournot competition; see [69] and, even more recently, [49]. To the best of our knowledge, the present paper is the first contribution to provide a formal framework, which allows to computationally analyze strategic booking and nomination decisions in the context of liberalized gas markets in an entry-exit regime.

Model Description and Main Solution Idea
Analysis of the Lower Level
Analysis of the Upper Level
Derivation of the Algorithm and Proof of Correctness
Numerical Examples
Case Study
Conclusion
Full Text
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