Hi Sassers-

I need some guidance on how to setup and interpret results from the PROC MIXED statement.

I have the following model of sector-level production: Q (i.e. sector output) is a fcn of (capital, labor, energy). The input data is a panel data set with cross sections of year and U.S. state. The error structure of the data is best modeled with an AR(1) process AND heterscedasticity. So far, I have the following code to make this data stationary (and non-biased inference possible):

proc mixed data=modeldata; by sector; class state year; model LN_Q = LN_KAP LN_E LN_L /s; repeated /type=ar(1) subject=fips group=fips; run;

Two questions: 1) I still don't understand what the group, subject, and class statements are really doing in PROC MIXED. Considering the structure of my panel, is the above code correct? All I'm trying to do is to account for state effects and year effects in the error term.

2) How do I generate estimated coefficients for KAP, E, and L as well as fit statistics. All I can see for output choices are covariance parameters, etc. All I really want is the beta hats...

Any help is greatly appreciated.

Have a great weekend. I'll be working on this. Pete