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)
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- Neil R. Ericsson & Jaime Marquez, 1998.
"A framework for economic forecasting,"
Royal Economic Society, vol. 1(Conferenc), pages 228-266.
- Neil R. Ericsson & Jaime R. 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: An Application to Fiscal Policy Simulations using an Aggregate Disequilibrium Model of the West German Economy," ZEW Discussion Papers 98-03, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. Full references (including those not matched with items on IDEAS)
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