We study a Monte Carlo algorithm for computing marginal and stationary densities of stochastic models with the Markov property, establishing global asymptotic normality and O(n^(1/2)) convergence. Asymptotic normality is used to derive error bounds in terms of the distribution of the norm...

This study demonstrates the possibility of ergodically chaotic optimal accumulation in the case in which future utilities are discounted arbitrarily weakly. For this purpose, the authors use a two-sector model with Leontief production functions and construct a condition under which the optimal...