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...

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...

This paper strengthens the Hopenhayn-Prescott stability theorem for monotone economies by extending it to a significantly larger class of models. We provid general conditions for existence, uniqueness and stability of stationary distributions. The conditions in our main result are both necessary...

In equilibrium models of firm dynamics, the stationary equilibrium distribution of firms summarizes the predictions of the model for a given set of primitives. Focusing on Hopenhayn's seminal model of firm dynamics with entry and exit (Econometrica, 60:5, 1992, p. 1127–1150), we provide an...