Analysis of Numerical Errors

Adrian Peralta-Alva, Manuel S. Santos

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

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.
Pages517-556
Number of pages40
DOIs
StatePublished - 2014

Publication series

NameHandbook of Computational Economics
Volume3
ISSN (Print)1574-0021

Keywords

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

ASJC Scopus subject areas

  • Economics and Econometrics
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Analysis of Numerical Errors'. Together they form a unique fingerprint.

  • Cite this

    Peralta-Alva, A., & Santos, M. S. (2014). Analysis of Numerical Errors. In Handbook of Computational Economics (pp. 517-556). (Handbook of Computational Economics; Vol. 3). Elsevier B.V.. https://doi.org/10.1016/B978-0-444-52980-0.00009-8