Hello,
I'm doing regression analysis with panel data (small N, large T). I have three related questions and I would be most grateful if anyone could answer at least one of them.
1. Can PROC MIXED estimate one-way fixed/random effects models as in TSCSREG? If so, which settings should one use?
2. I have constructed a mixed effects model. I have a collection of fixed effects plus cross-sectional random effects with autoregressive AR(1) error terms. All is well, but...
Other academic papers that report similar models also report the significance levels associated with
- the covariance parameter estimates; and
- the - 2 log likelihood
The only p-value that I can find is the null model likelihood ratio test. Is this p-value related to one of the above? If not, how will I know how many asterisks to put next to the covariance parameter estimates and the - 2 log likelihood 🙂
3. Is it so that the main difference between TSCSREG and MIXED is that they can manage different kinds of error covariance structures. That is, TSCSREG can handle cross-sectional heterogeneity (one-way fixed/random) and contemporaneous correlation (Parks), etc.; and MIXED can handle autoregressive error terms plus random cross-sectional errors (AR(1)), etc.
THANKS!