Solving Deterministic and Stochastic Equilibrium Problems via Augmented Walrasian

Julio Deride, Alejandro Jofré, Roger J.B. Wets

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)315-342
Number of pages28
JournalComputational Economics
Volume53
Issue number1
DOIs
StatePublished - 31 Jan 2019

Keywords

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

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