Computing the Distributions of Economic Models Via Simulation

John Stachurski ()

No 615, KIER Working Papers from Kyoto University, Institute of Economic Research

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 L1 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 investigated.

Keywords: Distributions; Markov processes; simulation. (search for similar items in EconPapers)
JEL-codes: C15 C22 C63 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-cmp, nep-ecm and nep-ict
Date: 2006-04
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http://www.kier.kyoto-u.ac.jp/DP/DP615.pdf (application/pdf)

Related works:
Working Paper: Computing the Distributions of Economic Models Via Simulation (2005)
Working Paper: Computing the Distributions of Economic Models via Simulation (2006)
Journal Article: Computing the Distributions of Economic Models via Simulation (2008)
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Persistent link: http://EconPapers.repec.org/RePEc:kyo:wpaper:615

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