Solving Deterministic and Stochastic Equilibrium Problems via Augmented Walrasian

Julio Deride (), Alejandro Jofré () and Roger J-B Wets ()
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Julio Deride: University of California Davis
Alejandro Jofré: Universidad de Chile
Roger J-B Wets: University of California Davis

Computational Economics, 2019, vol. 53, issue 1, No 14, 315-342

Abstract: 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.

Keywords: Walras equilibrium; Stochastic equilibrium; Lopsided convergence; Epi-convergence; Augmented Walrasian; Progressive hedging algorithm (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10614-017-9733-1

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