SAS/ETS(R) 9.2 User's Guide

The SMM (simulated method of moments) estimation is now available. This method of estimation is appropriate for estimating models in which integrals appear in the objective function and these integrals can be approximated by simulation. There may be various reasons for that to happen (for example, transformation of a latent model into an observable model, missing data, random coefficients, heterogeneity, and so on). A typical use of SMM is in estimating stochastic volatility models in finance, where only the stock return is observable (while the volatility process is not) and needs to be integrated out of the likelihood function. The simulation method can be used with all the estimation methods except full information maximum likelihood (FIML) in PROC MODEL. Examples have been provided to illustrate SMM estimation.

Heteroscedasticity-consistent covariance matrix estimators (HCCME) have been implemented. The HCCME= option selects which correction is applied to the covariance matrix.

Instrumental variables can now be specified for specific equations rather than for all equations. This is done with expanded syntax on the INSTRUMENT statement.