Hi all,
I am stuck on a problem of when to use a matched versus unmatched sample. I have a list of companies and I am trying figure out the effect of a treatment (a policy change in this case) on company financial performance (the dependent variable). I will use difference-in-differences for the analysis.
I do not know when (generally speaking) a matched sample design is better/worse than an unmatched sample design. To my understanding, matching "controls" for confounding variables before running regression models. Alternatively, using an unmatched sample, one would add the control variables into the regression model to "control" for these factors.
But broadly speaking, can someone please help me decide if I should use a matched sample with this case (pros/cons) and if so/not, why?
Roger C.
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