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Department ofEconomics


Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models

Serguei Maliar, Kenneth L. Judd, and Lilia Maliar.

Econometrica 85 (3), pp 991-1012, May 2017

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We propose a novel methodology for evaluating the accuracy of numerical solutions to dynamic economic models. It consists in constructing a lower bound on the size of approximation errors. A small lower bound on errors is a necessary condition for accuracy: If a lower error bound is unacceptably large, then the actual approximation errors are even larger, and hence, the approximation is inaccurate. Our lower-bound error analysis is complementary to the conventional upper-error (worst-case) bound analysis, which provides a sufficient condition for accuracy. As an illustration of our methodology, we assess approximation in the first- and second-order perturbation solutions for two stylized models: a neoclassical growth model and a new Keynesian model. The errors are small for the former model but unacceptably large for the latter model under some empirically relevant

LSB Research, ECON, 2017, Serguei Maliar