Analysis of Numerical Errors

Manuel Santos and Adrian Peralta-Alva ()

No 2012-6, Working Papers from University of Miami, Department of Economics

Abstract: This paper provides a general framework for the quantitative analysis of stochastic dynamic models. We review convergence properties of some numerical algorithms and available methods to bound approximation errors. We then address convergence and accuracy properties of the simulated moments. Our purpose is to provide an asymptotic theory for the computation, simulation-based estimation, and testing of dynamic economies. The theoretical analysis is complemented with several illustrative examples. We study both optimal and non-optimal economies. Optimal economies generate smooth laws of motion defining Markov equilibria, and can be approximated by recursive methods with contractive properties. Non-optimal economies, however, lack existence of continuous Markov equilibria, and need to be computed by other algorithms with weaker approximation properties.

Keywords: Stochastic Dynamic Model; Markov Equilibrium; Numerical Solution; Approximation Error; Accuracy; Simulation-Based Estimation; Consistency (search for similar items in EconPapers)
JEL-codes: C60 C63 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2012
New Economics Papers: this item is included in nep-cmp, nep-dge, nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Forthcoming: Under Review

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https://www.herbert.miami.edu/_assets/files/repec/WP2012-06.pdf First version, 2012 (application/pdf)

Related works:
Working Paper: Analysis of numerical errors (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:mia:wpaper:2012-6

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