  We present a new Progressive Hedging Algorithm to solve Stochastic
Variational Inequalities in the formulation introduced by Rockafellar and Wets
in 2017, allowing the generated subproblems to be approximately solved with an
implementable tolerance condition. Our scheme is based on Inexact Proximal
Point methods and generalizes the exact algorithm developed by Rockafellar and
Sun in 2019, providing stronger convergence results. We also show some
numerical experiments in two-stage Nash games.
