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Abstract:
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This paper suggests a method for determining rigorous upper bounds on approximation
errors of numerical solutions to infinite horizon dynamic programming models.
Bounds are provided for approximations of the value function and the policy
function as well as the derivatives of the value function. The bounds apply to more
general problems than existing bounding methods do. For instance, since strict concavity
is not required, linear models and piecewise linear approximations can be
dealt with. Despite the generality, the bounds perform well in comparison with existing
methods even when applied to approximations of a standard (strictly concave)
growth model.
KEYWORDS: Numerical approximation errors, Bellman contractions, Error bounds |
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