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Computing the Distributions of Economic Models via Simulation

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  • John Stachurski
  • Vance Martin

Abstract

We study a Monte Carlo algorithm for computing marginal and stationary densities of stochastic models with the Markov property, establishing global asymptotic normality and O(n^(1/2)) convergence. Asymptotic normality is used to derive error bounds in terms of the distribution of the norm deviation. Copyright The Econometric Society 2008.

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File URL: http://hdl.handle.net/10.1111/j.0012-9682.2008.00839.x
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Bibliographic Info

Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 76 (2008)
Issue (Month): 2 (03)
Pages: 443-450

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Handle: RePEc:ecm:emetrp:v:76:y:2008:i:2:p:443-450

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References

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  1. Deaton, A. & Laroque, G., 1989. "On The Behavior Of Commodity Prices," Papers 145, Princeton, Woodrow Wilson School - Public and International Affairs.
  2. A. S. Hurn & K. A. Lindsay & V. L. Martin, 2003. "On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 45-63, 01.
  3. Johnson, Paul, 2003. "A Continuous State Space Approach to “Convergence by Parts”," Vassar College Department of Economics Working Paper Series 54, Vassar College Department of Economics.
  4. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
  5. Elerian, O. & Chib, S. & Shephard, N., 1998. "Likelihood INference for Discretely Observed Non-linear Diffusions," Economics Papers 146, Economics Group, Nuffield College, University of Oxford.
  6. Nishimura, Kazuo & Stachurski, John, 2005. "Stability of stochastic optimal growth models: a new approach," Journal of Economic Theory, Elsevier, vol. 122(1), pages 100-118, May.
  7. Giorgio Valente & Lucio Sarno, 2004. "Comparing the accuracy of density forecasts from competing models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(8), pages 541-557.
  8. Hansen, Bruce E., 2005. "Exact Mean Integrated Squared Error Of Higher Order Kernel Estimators," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1031-1057, December.
  9. Esteban Rossi-Hansberg & Mark L. J. Wright, 2006. "Establishment size dynamics in the aggregate economy," Staff Report 382, Federal Reserve Bank of Minneapolis.
  10. Nishimura, Kazuo & Rudnicki, Ryszard & Stachurski, John, 2006. "Stochastic optimal growth with nonconvexities," Journal of Mathematical Economics, Elsevier, vol. 42(1), pages 74-96, February.
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Citations

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Cited by:
  1. Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CARF F-Series CARF-F-181, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  2. António Antunes & Tiago Cavalcanti & Anne Villamil, 2006. "Computing General Equilibrium Models with Occupational Choice and Financial Frictions," SCAPE Policy Research Working Paper Series 0611, National University of Singapore, Department of Economics, SCAPE.
  3. Vance Martin & Yoshihiko Nishiyama & John Stachurski, 2011. "A Goodness Of Fit Test For Ergodic Markov Processes," KIER Working Papers 787, Kyoto University, Institute of Economic Research.
  4. R. Anton Braun & Huiyu Li & John Stachurski, 2011. "Generalized Look-Ahead Methods for Computing Stationary Densities," ANU Working Papers in Economics and Econometrics 2011-558, Australian National University, College of Business and Economics, School of Economics.
  5. 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.

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