Hello all,


I am trying to get around the "variance matrix is nonsymmetric or highly singular" error and force Stata to give me standard errors. Is this possible in Stata? I have looked at other threads, but haven't found a way to force standard errors to be given in them.

Context:
In the project I am working on with my colleague, he is running a regression with a CBSA fixed effect; this means that there are a huge number of regressors and that most of them are sparse indicator variables. When non-clustered standard errors are requested, there is no problem. When clustered standard errors are requested, we get the "variance matrix is nonsymmetric or highly singular" error. This is expected – when the number of regressors exceeds the number of clusters (which is the case with our project), the var-cov matrix is rank-deficient, and valid statistical inference on a limited number of coefficients (but not jointly on all of them at once) can still be conducted. So, we would like to get around the "variance matrix is nonsymmetric or highly singular" error and have Stata give us the var-cov matrix and standard errors anyway, despite the singular nature of the var-cov matrix.