Upper Bounds on Numerical Approximation Errors

This paper suggests a method for determining rigorous upper bounds on approximationerrors of numerical solutions to infinite horizon dynamic programming models.Bounds are provided for approximations of the value function and the policyfunction as well as the derivatives of the value function. The bounds apply to moregeneral problems than existing bounding methods do. For instance, since strict concavityis not required, linear models and piecewise linear approximations can bedealt with. Despite the generality, the bounds perform well in comparison with existingmethods even when applied to approximations of a standard (strictly concave)growth model.