st: Least square regression involving time lags in the parameters

["Lodh Ashish" <Ashish.Lodh@Generali.com>]

Dear all,

I am trying to model a regression on a dependent variable using 6
independent parameters.
All these variables are time series sampled at identical time intervals.
I have the independence to lag the 6 parameters individually by 0 to 10
time steps in order to get a better fit.
My aim is to find the best fit (with significantly low p-values for the
betas) of regression by using different lags on the parameters.
For example, I might get the best fit (say adjusted R-square of 94%)
using the lags 0, 2, 0, 5, 5, 1 respectively on the six variables.

I made a program in MATLAB using nested loops and it works fine. The
only problem being large number of OLS regressions take a long time to
compile.
I wish to do the same in Stata. Can anybody throw some light on how it
can be done in Stata?
I hope there is a simpler process in Stata to do the same.

Thanks
Ashish



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