Adjusting Standard Errors in Non-linear Seemingly Unrelated Regression

[Turkeyboy]

Hi,

I am estimating a non-linear seemingly unrelated regressing using proc model, as follows:

proc model data=temp2w;
   Y1= a0 + ((gamma))*(rho1)*X1+ (1-(theta))*(rho2)*X2;
   Y2= b0 + (1-(gamma))*(rho1)*X1+ (theta)*(rho2)*X2;
   fit  dPIFO dPIDOM/ sur;
run;
quit;

I need estimates of a0, b0, gamma, theta, rho1, and rho2. The model estimates the parameters as I would expect. Is there a way to adjust standard errors for clustered observations in SAS? My dataset consists of a panel of firms, and there is reason to suspect that observations are not independent within a firm.

[RobPratt]

Since PROC MODEL is part of SAS/ETS and not SAS/OR, you might have better luck in the Forecasting and Econometrics community:

https://communities.sas.com/community/support-communities/sas_forecasting

[Turkeyboy]

Great. Thanks!