Quasi - Monte Carlo Methods in Stochastic Simulations
AbstractDifferent stochastic simulation methods are used in order to check the robustness of the outcome of policy simulations with a macroeconometric model. A macroeconometric disequilibriummodel of the West German economy is used to analyze a reform proposal for the tax system. The model was estimated with quarterly data for the period 1960 to 1994, the presently possible margin. Because of nonlinearities confidence intervals for the simulation results have to be obtained by means of stochastic simulations. The main contribution of this paper consists in presenting the simulation results. The robustness of these results is analyzed using different approaches to stochastic simulation. In particular, different methods for the generation of uniform error terms and their conversion to normal variates are applied. These methods include standard approaches as well as quasi - Monte Carlo methods. --
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research in its series ZEW Discussion Papers with number 98-03.
Date of creation: 1998
Date of revision:
policy simulation; macroeconometric disequilibrium model; stochastic simulation; random number generation; quasi - Monte Carlo methods;
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.:
- Sterbenz, Frederic P & Calzolari, Giorgio, 1990. "Alternative Specifications of the Error Process in the Stochastic Simulation of Econometric Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 137-50, April-Jun.
- Gilli, Manfred & Pauletto, Giorgio, 1997. "Sparse direct methods for model simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1093-1111, June.
- Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-43, March.
- Beck, Martin & Winker, Peter, 2004. "Modeling spillovers and feedback of international trade in a disequilibrium framework," Economic Modelling, Elsevier, vol. 21(3), pages 445-470, May.
- Peter Winker & Jenny Li, 2000.
"Time Series Simulation With Quasi-Monte Carlo Methods,"
Computing in Economics and Finance 2000
151, Society for Computational Economics.
- Jenny X. Li & Peter Winker, 2003. "Time Series Simulation with Quasi Monte Carlo Methods," Computational Economics, Society for Computational Economics, vol. 21(1_2), pages 23-43, 02.
- 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.
- Li, J.X. & Winker, P., 2000. "Time Series Simulation With Quasi Monte Carlo Methods," Papers 9-00-1, Pennsylvania State - Department of Economics.
- Dobrescu, Emilian & Pauna, Bianca, 2007. "Stochastic simulations on the Romanian macroeconomic model," MPRA Paper 35723, University Library of Munich, Germany.
- Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Society for Computational Economics, vol. 31(1), pages 21-43, February.
- Okten, Giray & Eastman, Warren, 2004. "Randomized quasi-Monte Carlo methods in pricing securities," Journal of Economic Dynamics and Control, Elsevier, vol. 28(12), pages 2399-2426, December.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics).
If references are entirely missing, you can add them using this form.