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Analysis of numerical errors

Listed author(s):
  • Adrian Peralta-Alva
  • Manuel S. Santos

This paper provides a general framework for the quantitative analysis of stochastic dynamic models. We review convergence properties of some numerical algorithms and available methods to bound approximation errors. We then address convergence and accuracy properties of the simulated moments. Our purpose is to provide an asymptotic theory for the computation, simulation-based estimation, and testing of dynamic economies. The theoretical analysis is complemented with several illustrative examples. We study both optimal and non-optimal economies. Optimal economies generate smooth laws of motion defining Markov equilibria, and can be approximated by recursive methods with contractive properties. Non-optimal economies, however, lack existence of continuous Markov equilibria, and need to be computed by other algorithms with weaker approximation properties.

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File URL: http://research.stlouisfed.org/wp/2012/2012-062.pdf
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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2012-062.

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Date of creation: 2012
Handle: RePEc:fip:fedlwp:2012-062
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  12. Manuel S. Santos & Adrian Peralta-Alva, 2003. "Accuracy of Simulations for Stochastic Dynamic Models," Levine's Bibliography 666156000000000264, UCLA Department of Economics.
  13. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
  14. Zhigang Feng & Jianjun Miao & Adrian Peralta-Alva & Manuel S. Santos, 2009. "Numerical simulation of nonoptimal dynamic equilibrium models," Working Papers 2009-018, Federal Reserve Bank of St. Louis.
  15. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
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  24. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Manuel Santos, 2005. "Convergence Properties of the Likelihood of Computed Dynamic Models," Levine's Bibliography 122247000000000822, UCLA Department of Economics.
  25. Grandmont Jean-michel, 1983. "On endogenous competitive business cycles," CEPREMAP Working Papers (Couverture Orange) 8316, CEPREMAP.
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  29. Blume, Lawrence E., 1982. "New techniques for the study of stochastic equilibrium processes," Journal of Mathematical Economics, Elsevier, vol. 9(1-2), pages 61-70, January.
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  35. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
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