st: eViews "model solving" in Stata?

[Diego Navarro <the.electric.me@gmail.com>]

I've been doing most of my work in Stata now -- like I got used to in  
grad school -- but there's some legacy stuff I'm inheriting from  
eViews. After estimating a dynamic model, eViews can generate a  
"model" object that has a "solve" method; it can do rolling-time  
prediction (predicting state t+1 after actual data at time t) or  
"dynamic" prediction (predicting the whole trajectory after the  
initial state), optionally using random parameters (as estimated from  
the model) and generated confidence bands.

What's the "Stata-ish" way to do this in Stata, short of cobbling  
together some /program define/ procedures?

I appreciate any help at all, and hope to be useful to others in the  
future.
--
Diego Navarro
(21) 2559-5620

“The first step is to measure what can be easily measured.  This is  
okay as far as it goes.  The second step is to disregard that which  
cannot be measured, or give it an arbitrary quantitative value.  This  
is artificial and misleading.  The third step is to presume that what  
cannot be measured really is not very important.  This is blindness.   
The fourth step is to say that what cannot be measured does not really  
exist.  This is suicide.” (Daniel Yankelovich, 1973)


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