Finally you could test the significance of the parameter from the SUR. But I am not 100% sure whether this could actually work. I think it might be possible to set-up the fixed effect model as a least square dummy variable regression, and use a seemingly uncorrelated regression to include a few regression equations.
I think you are talking about the linear panel data model under the fixed effects assumption. applications of suest are tests for cross-part hypotheses using test or testnl. I discuss two potential advantages of the approach over the mvprobit command (Cappellari and Jenkins, 2003, Stata Journal 3: 278294): significant reductions in computation time and essentially unlimited dimensionality of the outcome set. If you want to perform tests that are usually run with suest, such as non-nested models, tests using alternative specifications of the variables, or tests on different groups, you can replicate it manually, as described here. suest Do not use suest.It will run, but the results will be incorrect. I've seen that I can't use 'suest' since this doesn't work for fixed effects regressions and I also can't create the equivalent of a fixed effects model using reg and individual dummies since I have 1666 individuals which is greater than the max matsize. The Stata Journal publishes reviewed papers together with shorter notes. This approach is based on Stata's biprobit and suest commands and is driven by a Mata function, bvpmvp(). test Performs significance test on the parameters, see the stata help. I based my replication on: Zhuan Pei, Jrn-Steffen Pischke & Hannes Schwandt (2019) Poorly. As explained above I wish to test coefficients from different fixed effects regressions. I was able to replicate Statas suest using geepack in R.
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