Computing the Distributions of Economic Models Via Simulation

John Stachurski ()

No 949, Department of Economics - Working Papers Series from The University of Melbourne

Abstract: This paper studies the convergence properties of a Monte Carlo algorithm for computing distributions of state variables when the underlying model is a Markov chain with absolutely continuous transition probabilities. We show that the L1 error of the estimator always converges to zero with probability one. In addition, rates of convergence are established for L1 and integral mean squared errors. The algorithm is shown to have many applications in economics.

New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ict
Date: 2005
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Related works:
Working Paper: Computing the Distributions of Economic Models Via Simulation (2006)
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:mlb:wpaper:949

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