dsGameSolver: A Python Program for Computing Markov Perfect Equilibria of Dynamic Stochastic Games
50 Pages Posted: 31 Jan 2019
Date Written: January 16, 2019
dsGameSolver is based on the homotopy method developed in Eibelshaeuser and Poensgen (2019). It is the first program capable of computing a Markov perfect equilibrium of any finite dynamic stochastic game -- subject to the usual restrictions on numerical accuracy and working memory. dsGameSolver supports general games with state-player-specific numbers of actions and individual discount factors, covering virtually any game of complete information. Furthermore, it is remarkably performant and able to handle games with thousands of state-player-actions. Finally, dsGameSolver allows users with basic programming skills in Python to formulate complex games with ease and to directly use the results for subsequent illustration and analysis.
Keywords: Equilibrium computation, Homotopy continuation, Quantal response, Logit choice, Limiting equilibrium
JEL Classification: C63, C73
Suggested Citation: Suggested Citation