Hi all,

I have a problem that involves nonlinear estimation, period-by-period.

I have (say) 8 equations of the form

f(delta,theta(i)) = epsilon(i)

and (say) 28 equations of the form

g(delta,theta(i)) = epsilon(i) - epsilon(j).

I can successfully use FIND to estimate all the parameters (delta vector, plus all the theta(i)), if I minimize the squared epsilons AND the squares of (epsilon(i) - epsilon(j)). (This post has been edited, as I had an error.) I think that what I am doing is akin to GMM or indirect inference - and if so, as any covariance matrix yields consistent estimates, I can run this unweighted - but I am not sure about that.)

Since this is period-by-period, I don't think NLSYSTEM is appropriate.

I also plan to bootstrap the standard errors by simulating new data using the estimated parameters and sampling from the estimated epsilons.

Thanks everyone.

Randy