| By: |
John Stachurski (Department of Economics, University of Melbourne) |
| 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. |
| JEL: |
C15 C22 C63 |
| Date: |
2006–04 |
| URL: |
http://d.repec.org/n?u=RePEc:kyo:wpaper:615&r=ict |