I saw the impact of anticollusion laws on dependent variables Y across the country by using generalized DID by following Dasgupta, 2019.
The identification is:
$Y_{it}$ = $\alpha$ + $\beta$ $(pt)_{kt}$ + $\delta$$X_{ikt}$ + $\theta$$_t$ + $\gamma$$_i$ +$\epsilon$$_{it}$
where i,k, and t index firms, countries, and years respectively. $X_{ikt}$ is a vector of the different firm, country, and industry control, while $\gamma$ and $\theta$ are firm and year fixed effects.$(pt)_{kt}$ is the post * treat variable
The result is
While 6 columns all using firm and years fixed effects if not stated elsewhere.Column 1, I did not control any independent variables. Column(2), I control for some firm and country independent variables. In column (3), I control for firm, country and industry variables. in column (4), I control for country and firm independent variable along with firm and industry * year fixed effect. In column (5). I control for the country and firm independent variables along with firm and region * year fixed effect. In column (6), I control for some firm and country independent variables, similar to column (2) but without US firms.
I am wondering whether I can conclude that: anticollusion laws, in general, have weak but consistent negative impact on Y ceteris paribus, on average in this situation?