Hello,
I want to make a difference in difference analysis with analysis objects that sometimes have repeat treatments over time (for example, in 2010, 2013). As I do not expect the repeat treatments to magnify the effect, I would just stack the objects according to the timing and restructure my dataset to reflect t-3, …, t0, … t+3 with some observations appearing multiple times.
My treatment sample has around 400 objects and the population has around 11,000. So I have quite some space to maneuver to find a suitable control group that ideally matches the pre-treatment development of the treatment group as close as possible. However, as I move the variables in time from fixed year (e.g., 2013) to relative timing (e.g., t+3), with some objects receiving treatments in multiple years, how would I treat these issues in Propensity Score Matching?
Would it be a problem to essentially have repeated objects in PSM at different time points? If yes, are there any solutions to it?
Thank you in advance!
I want to make a difference in difference analysis with analysis objects that sometimes have repeat treatments over time (for example, in 2010, 2013). As I do not expect the repeat treatments to magnify the effect, I would just stack the objects according to the timing and restructure my dataset to reflect t-3, …, t0, … t+3 with some observations appearing multiple times.
My treatment sample has around 400 objects and the population has around 11,000. So I have quite some space to maneuver to find a suitable control group that ideally matches the pre-treatment development of the treatment group as close as possible. However, as I move the variables in time from fixed year (e.g., 2013) to relative timing (e.g., t+3), with some objects receiving treatments in multiple years, how would I treat these issues in Propensity Score Matching?
Would it be a problem to essentially have repeated objects in PSM at different time points? If yes, are there any solutions to it?
Thank you in advance!
