Computing the Distributions of Economic Models via Simulation

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

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Year of publication:	2006-07-04
Authors:	Stachurski, John
Institutions:	Society for Computational Economics - SCE
Subject:	Distributions \| Markov processes \| simulation

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Series:	Computing in Economics and Finance 2006.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series Computing in Economics and Finance 2006 Number 185
Classification:	C15 - Statistical Simulation Methods; Monte Carlo Methods ; C22 - Time-Series Models ; C63 - Computational Techniques
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005342929