I have a panel data set. The dependent variable is a certain numerical score for each individual and time period. I have a number of independent variables that vary by individual, by time, or by both.
Over the time of the data, two interventions were done (for all individuals at the same time) to increase the score. No one was assigned to control, as this was not an experiment but a managerial decision. So difference-in-differences is not a suitable tool here.
Is there any methodology to quantify the impact of the interventions on the score in the absence of a control group? If every possible other variable that could have an effect on the score (based on literature and industry-specific knowledge) is added as an independent variable, does it provide a stronger justification on the impact of the interventions on the score?