Fixed Effects in Differences-in-Differences estimations?

[Berkay Ozcan]

Can anyone explain me how to interpret fixed effects estimation applied to a regression-DD (Differences in Differences)? I understand the logic of adding state-specific trends but not quite estimating fixed effects. What does fixed effects do to a regression equation as in the following? :

Here LS is a dependent variable (labour supply) of an individual i in group j , F is a logit or probit function which will be estimated in fixed effects. T is an indicator for individuals belonging to the treatment group and Post is a dummy variable for the period after the treatment. X represents all the other control variables (time varying or constant). The data I use is an individual panel.

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