In a paper, Dasgupta, 2019 used Difference-in-Difference approach to see whether anticollusion laws implemented by different countries (staggered implementation) affect firms financial flexibility.
Dasgupta, 2019, p.2610 used an approach called "prediction model"
by only using pre-leniency observations and predict the probability that the firm will be convicted in the cartel case after the passage of a leniency law.
In particular, what they did is
First, we estimate the propensity of a firm to be convicted in a cartel case. We use a prediction model based on time-varying firm characteristics (asset size, leverage, and ROA), country characteristics (GDP and unemployment), and country fixed effects and three-digit SIC fixed effects.
I do not understand how they calculate the "probability that the firm will be convicted in the cartel case after the passage of a leniency law" like that by using STATA. The one command I can link to is "predict" but it seems not to work in this case.