Indirect inference and variance reduction using control variates

Simulation based estimators are successfully employed for estimating models whose likelihood functions do not have manageable closed-form expressions. The price to be paid is an increased variance of the estimated parameters. To reduce this undesirable effect, one should properly increase the number of simulations (or the length of each simulation) and thus the computational cost. Alternatively, this paper shows how variance reduction can be achieved, at virtually no additional computational cost, by use of control variates.