Assume that we have a panel data set with individuals' income (Y) over multiple years and a certain event (POST) in one year that is hypothesized to affect Y for a subgroup of these individuals (TREAT).
The regular diff-in-diff design would be: Y = a + bPOST + cTREAT + d*POSTxTREAT + e
How would time-fixed effects affect the interpretation of this standard DiD-model? (only time-fixed effects (!) - no individual-fixed effects are added, so it is not a two-way fixed effects model). In my opinion this should erroneously remove part of the actual treatment effect, right?