I am running a difference-in-difference model using the SSC command -xthybrid. I am interested in both the diff-in-diff coefficients (incomegroup*post) as well as the income group coefficients on their own. I created these interactions manually with:

Code:
generate lowincome_post = lowincome*post
generate lowmidincome_post = lowmidincome*post
generate upmidincome_post = upmidincome*post
generate highincome_post = highincome*post
However, the income group coefficients alone drop out when I run the regression.

Code:
xthybrid workplaces lowincome lowmidincome upmidincome highincome post lowincome_post lowmidincome_post upmidincome_post hi
> ghincome_post autocracy anocracy democracy over65_2019 covid_cases_prev_day ghsindex date, clusterid(id) se star

The variable 'lowincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'lowincome' is within clusters]
The variable 'lowmidincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'lowmidincome' is within clusters]
The variable 'upmidincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'upmidincome' is within clusters]
The variable 'highincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'highincome' is within clusters]
The variable 'autocracy' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'autocracy' is within clusters]
The variable 'anocracy' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'anocracy' is within clusters]
The variable 'democracy' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'democracy' is within clusters]
The variable 'over65_2019' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'over65_2019' is within clusters]
The variable 'ghsindex' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'ghsindex' is within clusters]

Hybrid model. Family: gaussian. Link: identity.

+--------------------------------------+
|             Variable |     model     |
|----------------------+---------------|
| workplaces           |               |
|         R__autocracy |     7.4840*   |
|          R__anocracy |     5.3708    |
|         R__democracy |  (omitted)    |
|       R__over65_2019 |     0.0947    |
|          R__ghsindex |    -0.0950    |
|              W__post |   -42.6952*** |
|    W__lowincome_post |    12.5376*** |
| W__lowmidincome_post |     3.1323*** |
|  W__upmidincome_post |    -4.0732*** |
|   W__highincome_post |  (omitted)    |
| W__covid_cases_pre~y |    -0.0000    |
|              W__date |     0.1288*** |
|              B__post |  (omitted)    |
|    B__lowincome_post |    13.0836*   |
| B__lowmidincome_post |     5.4908    |
|  B__upmidincome_post |    -0.7562    |
|   B__highincome_post |  (omitted)    |
| B__covid_cases_pre~y |    -0.0000    |
|              B__date |  (omitted)    |
|                _cons |   -25.2668*** |
|----------------------+---------------|
|        var(_cons[id])|               |
|                _cons |   102.0214*** |
|----------------------+---------------|
|     var(e.workplaces)|               |
|                _cons |   301.9074*** |
|----------------------+---------------|
| Statistics           |               |
|                   ll | -6.300e+04    |
|                 chi2 |  9331.7036    |
|                    p |     0.0000    |
|                  aic |  1.260e+05    |
|                  bic |  1.262e+05    |
+--------------------------------------+
   legend: * p<.05; ** p<.01; *** p<.001
Level 1: 14690 units. Level 2: 113 units.
I am using the hybrid model in order to retain rather than omit my time invariant variables (including income group variables). Why are the income group variables omitted?

If I do not include the interaction terms in my model, the income group variables remain in the output.

Code:
xthybrid workplaces lowincome lowmidincome upmidincome highincome post autocracy anocracy democracy over65_2019 covid_cases
> _prev_day ghsindex date, clusterid(id) se star

The variable 'lowincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'lowincome' is within clusters]
The variable 'lowmidincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'lowmidincome' is within clusters]
The variable 'upmidincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'upmidincome' is within clusters]
The variable 'highincome' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'highincome' is within clusters]
The variable 'autocracy' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'autocracy' is within clusters]
The variable 'anocracy' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'anocracy' is within clusters]
The variable 'democracy' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'democracy' is within clusters]
The variable 'over65_2019' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'over65_2019' is within clusters]
The variable 'ghsindex' does not vary sufficiently within clusters
and will not be used to create additional regressors.
[~0% of the total variance in 'ghsindex' is within clusters]

Hybrid model. Family: gaussian. Link: identity.

+--------------------------------------+
|             Variable |     model     |
|----------------------+---------------|
| workplaces           |               |
|         R__lowincome |    10.5675*   |
|      R__lowmidincome |     4.4349    |
|       R__upmidincome |    -0.6107    |
|        R__highincome |  (omitted)    |
|         R__autocracy |     7.4840*   |
|          R__anocracy |     5.3708    |
|         R__democracy |  (omitted)    |
|       R__over65_2019 |     0.0947    |
|          R__ghsindex |    -0.0950    |
|              W__post |   -41.9442*** |
| W__covid_cases_pre~y |    -0.0000*   |
|              W__date |     0.1295*** |
|              B__post |  (omitted)    |
| B__covid_cases_pre~y |    -0.0000    |
|              B__date |  (omitted)    |
|                _cons |   -25.2668*** |
|----------------------+---------------|
|        var(_cons[id])|               |
|                _cons |   101.9970*** |
|----------------------+---------------|
|     var(e.workplaces)|               |
|                _cons |   305.0783*** |
|----------------------+---------------|
| Statistics           |               |
|                   ll | -6.308e+04    |
|                 chi2 |  9083.5563    |
|                    p |     0.0000    |
|                  aic |  1.262e+05    |
|                  bic |  1.263e+05    |
+--------------------------------------+
   legend: * p<.05; ** p<.01; *** p<.001
Level 1: 14690 units. Level 2: 113 units.
How can I get the coefficients for both sets?