Time Series Simulation with Quasi Monte Carlo Methods
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.
Volume (Year): 21 (2003)
Issue (Month): 1_2 (02)
|Contact details of provider:|| Web page: http://www.springerlink.com/link.asp?id=100248|
More information through EDIRC
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.:
- Neil R. Ericsson & Jaime Marquez, 1998.
"A framework for economic forecasting,"
International Finance Discussion Papers
626, Board of Governors of the Federal Reserve System (U.S.).
- 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.
When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:21:y:2003:i:1_2:p:23-43. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.