Time Series Simulation with Quasi Monte Carlo Methods
AbstractThis 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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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 21 (2003)
Issue (Month): 1_2 (02)
Other versions of this item:
- Jenny Li & Peter Winker, 2003. "Time Series Simulation with Quasi Monte Carlo Methods," Computational Economics, Society for Computational Economics, vol. 21(1), pages 23-43, February.
- Peter Winker & Jenny Li, 2000. "Time Series Simulation With Quasi-Monte Carlo Methods," Computing in Economics and Finance 2000 151, Society for Computational Economics.
- Li, J.X. & Winker, P., 2000. "Time Series Simulation With Quasi Monte Carlo Methods," Papers 9-00-1, Pennsylvania State - Department of Economics.
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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