Hausman test for panel data, fe and re. Error in the estimation, what to do? Stata I am performing a Hausman test on panel data to determine whether to choose Random Effects or Fixed Effects for my analysis.  After performing the test I get this error:
chi2(2) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                          =    -8.32    chi2<0 ==> model fitted on these
                                        data fails to meet the asymptotic
                                        assumptions of the Hausman test;
                                        see suest for a generalized test

What does this mean? Is this result OK, and it simply means that I should use random effects or something is terribly wrong here?  I cannot use suest as the software suggest, because that's not for panel data.
In addition, when I change the order of the analysis, i.e. I estimate re first, and then fe, and do:  hausman random fixed, I get a "normal" result, like this:
chi2(17) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                          =      411.18
                Prob>chi2 =      0.0000

However, I read on Statalist that it is not as simple as changing the order, since you get a wrong statistic.
So, the question is, what to do in this case, can I change the order of the estimation? I am pretty sure that FE does not work well with my data, but I need a way to prove it. 
Please consider I am not a statistician, so the simpler the answer, the better.
 A: Your first test returns a negative test statistic (-8.32) which should not happen. Usually the reason for this is a too small sample or mis-specification of the model. As it stands the result of your first test cannot be used to infer much more. Certainly it is not advisable to reverse the order of the estimates in the test for the reasons highlighted in the Statalist post you linked.
You may want to try the command xtoverid which gives a positive test statistic and also works with panels (unlike suest). In Stata you can install it by typing
ssc install xtoverid 
At the bottom of the help file you will also find an example of how to use the test for deciding between FE or RE models. Run the RE model and then use the xtoverid command after that. The interpretation is the same as with hausman, i.e. a significant test statistic rejects the null hypothesis that RE is consistent.
A: The negative sign can  arise  if different  esti­mates of  the  error variance  are  used  in forming variance of b and variance of B. In that case, you need to use the sigmamore  option, which specifies that both covariance matri­ces are based on the  (same)  estimated disturbance variance from the efficient estimator. 
hausman  FE RE , sigmamore

Note: FE and RE are estimates stored from fixed effect and random effect model. The answer is based on Microeconometrics using Stata by Cameron and Trivedi p. 261. 
