Results indicate that each of the features above partially account for the persistence and occasional spikes observed in actual data. Evidence is presented that the precautionary demand for stocks might play a substantial role in the dynamics of commodity prices. In this paper, the structural parameters of this model are estimated using three simulation based estimators. Exploiting the invariant distribution implied by the theory allows us to assess the error induced by simulations. Our results show that while all three estimators produce reasonably good estimates with properties that stack up well with those of the PMLE, there are tradeoffs among the three estimators in terms of bias, efficiency, and computation demands.
Some estimators are more sensitive to the sample size and the number of simulations than others.
Increasing the number of simulated data points can sometimes reduce the bias and improve the efficiency of the estimates when the sample size is small. Specifically, we examine the models' ability to price Treasuries for one to five trading days ahead. Their relative success also depends on time, the forecast horizon, and whether price or yield errors are compared. We find wide variation in retirement patterns and recent trends.