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Time Series Simulation with Quasi Monte Carlo Methods

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Author Info
Jenny X. Li ()
Peter Winker ()

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Abstract

This paper compares quasi Monte Carlo methods, in particular so-called (t, m, s)-nets, with classical Monte Carlo approaches for simulating econometric time-series models. Quasi Monte Carlo methods have found successful application in many fields, such as physics, image processing, and the evaluation of finance derivatives. However, they are rarely used in econometrics. Here, we apply both traditional and quasi Monte Carlo simulation methods to time-series models that typically arise in macroeconometrics. The numerical experiments demonstrate that quasi Monte Carlo methods outperform traditional ones for all models we investigate.

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Publisher Info
Article provided by Springer in its journal Computational Economics.

Volume (Year): 21 (2003)
Issue (Month): 1_2 (02)
Pages: 23-43
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Handle: RePEc:kap:compec:v:21:y:2003:i:1_2:p:23-43

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Web page: http://www.springerlink.com/link.asp?id=100248

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Neil R. Ericsson & Jaime Marquez, 1998. "A framework for economic forecasting," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C228-C266.
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  2. Franz, Wolfgang & Göggelmann, Klaus & Schellhorn, Martin & Winker, Peter, 1998. "Quasi - Monte Carlo Methods in Stochastic Simulations," ZEW Discussion Papers 98-03, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer, vol. 31(1), pages 21-43, February. [Downloadable!] (restricted)
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This page was last updated on 2009-12-10.


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