Regression model for pre-post single group design I am analysing cross-section data from two time points, i.e. before and after an intervention and I am particularly interested in the causal effect of the intervention. The outcome of interest ($Y$) is metric and I have some control variables (all nominal or ordinal) like gender, size of company etc. In order to calculate the effect of the intervention I included a pre/post dummy into  a regression model: $Y = a + b1*PrePost + b2*male + b3*small \ enterprise + b4*large \ enterprise$
I need some help with the interpretation: $b1$ is the effect of the intervention when all control var are held constant (in the two groups, pre- and post), right? Is that true even when one category of the dummies is left out?
How to interpret the coeffs on the dummies in relation to $b1$ (the most interesting coefficient of the intervention effect)? 
How do I calculate the effect of the intervention ($b1$) for various subgroups defined by the dummies? Do I have to include the interaction of each dummy-categorie and the PrePost dummy - in addition to all group dummies? E.g. $Y = a + b1*prepost + b2*male + b3*small \ enterprise + b4*male*prepost + b5*small \ enterprise*prepost$
How are these coeffs then interpreted? 
 A: In your first model, $\beta_1$ reflects the estimated effect of the intervention at all levels of all your control variables. So regardless of whether you're male or female, or the size of your enterprise, the estimated effect of the intervention is $\beta_1$.
If you want to allow every subgroup to have their own effect then you would fit an interaction. If you're wanting to do this for every subgroup then you'll need to include an interaction term containing all of the variables. This will mean you need two-way and three-way interactions:
$Y=\beta_0+\beta_1∗prepost+\beta_2∗M+
\beta_3∗SE+
\beta_4∗LE+
\beta_5*M*prepost+
\beta_6*SE∗prepost+
\beta_7*LE∗prepost+
\beta_8*M*SE+
\beta_9*M*LE+
\beta_{10}*M*SE*prepost+
\beta_{11}*M*LE*prepost
$
How you interpret the coefficients will depend on how you choose to code the variables. This, in term, will depend on the research question that you have but very generally they'll tell you whether the effect of the intervention varies depending on differences in the subgroup a person is in.
