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Computing the Distributions of Economic Models via Simulation

Author

Listed:
  • John Stachurski
  • University of Melbourne

Abstract

This paper studies a Monte Carlo algorithm for computing distributions of state variables when the underlying model is a Markov process. It is shown that the $L_1$ error of the estimator always converges to zero with probability one, and often at a parametric rate. A related technique for computing stationary distributions is also investigate

Suggested Citation

  • John Stachurski & University of Melbourne, 2006. "Computing the Distributions of Economic Models via Simulation," Computing in Economics and Finance 2006 185, Society for Computational Economics.
    • Handle: RePEc:sce:scecfa:185
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    Cited by:

    1. is not listed on IDEAS
    2. Stephane Verani, 2018. "Aggregate Consequences of Dynamic Credit Relationships," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 44-67, July.
    3. Antunes, António & Cavalcanti, Tiago & Villamil, Anne, 2008. "Computing general equilibrium models with occupational choice and financial frictions," Journal of Mathematical Economics, Elsevier, vol. 44(7-8), pages 553-568, July.
    4. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    5. R. Anton Braun & Huiyu Li & John Stachurski, 2012. "Generalized Look-Ahead Methods for Computing Stationary Densities," Mathematics of Operations Research, INFORMS, vol. 37(3), pages 489-500, August.
    6. John Stachurski & Huiyu Li & Richard Anton Braun, 2009. "Computing Densities in Stochastic Recursive Economies: Generalized Look-Ahead Techniques," 2009 Meeting Papers 975, Society for Economic Dynamics.
    7. Antunes, António & Cavalcanti, Tiago & Villamil, Anne, 2008. "Computing general equilibrium models with occupational choice and financial frictions," Journal of Mathematical Economics, Elsevier, vol. 44(7-8), pages 553-568, July.
    8. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    9. Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CIRJE F-Series CIRJE-F-678, CIRJE, Faculty of Economics, University of Tokyo.
    10. Vance Martin & Yoshihiko Nishiyama & John Stachurski, 2011. "A Goodness of Fit Test for Ergodic Markov Processes," ANU Working Papers in Economics and Econometrics 2011-557, Australian National University, College of Business and Economics, School of Economics.
    11. Stephane Verani, 2018. "Aggregate Consequences of Dynamic Credit Relationships," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 44-67, July.
    12. John Stachurski, 2009. "Economic Dynamics: Theory and Computation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012774, December.

    More about this item

    Keywords

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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