Measurement of Simulation Variance in Parameter Estimation by

Estimation by simulation involves drawing random terms for each observation and calculating an element (such as the probability or score) that enters an objective function (e.g. the simulated log-likelihood function) and/or a first-order condition (e.g., the sum of simulated scores or simulated moment conditions). The resulting parameter estimates depend on the particular values of the draws for each observation and necessarily vary over draws. We investigate the variance in parameter estimates that is induced by the drawing of random terms and propose a practical method for measuring this simulation variance and correcting the standard errors of the estimates to account for it.