Computational Economics

, Volume 53, Issue 1, pp 315–342 | Cite as

Solving Deterministic and Stochastic Equilibrium Problems via Augmented Walrasian

  • Julio DerideEmail author
  • Alejandro Jofré
  • Roger J-B Wets


We described a method to solve deterministic and stochastic Walras equilibrium models based on associating with the given problem a bifunction whose maxinf-points turn out to be equilibrium points. The numerical procedure relies on an augmentation of this bifunction. Convergence of the proposed procedure is proved by relying on the relevant lopsided convergence. In the two-stage versions of our models, deterministic and stochastic, we are mostly concerned with models that equip the agents with a mechanism to transfer goods from one time period to the next, possibly simply savings, but also allows for the transformation of goods via production.


Walras equilibrium Stochastic equilibrium Lopsided convergence Epi-convergence Augmented Walrasian Progressive hedging algorithm 



This material is based upon work by Julio Deride and Roger Wets supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office under grant numbers W911NF-10-1-0246 and W911NF-12-1-0273.


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of California DavisDavisUSA
  2. 2.DavisUSA
  3. 3.Ingeniería MatemáticaUniversidad de ChileSantiagoChile

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