Analysis of Numerical Errors

Adrian Peralta-Alva, Manuel S. Santos

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations


This paper provides a general framework for the quantitative analysis of stochastic dynamic models. We review the convergence properties of some numerical algorithms and available methods to bound approximation errors. We then address the convergence and accuracy properties of the simulated moments. 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 simulated by numerical methods with weaker approximation properties.

Original languageEnglish (US)
Title of host publicationHandbook of Computational Economics
PublisherElsevier B.V.
Number of pages40
StatePublished - 2014

Publication series

NameHandbook of Computational Economics
ISSN (Print)1574-0021


  • Accuracy
  • Approximation error
  • Consistency
  • Dynamic stochastic economy
  • Markov equilibrium
  • Numerical solution
  • Simulation-based estimation

ASJC Scopus subject areas

  • Economics and Econometrics
  • Computer Science Applications


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