#StackBounty: #regression #time-series #regression-discontinuity What is difference between interrupted time series and regression disc…

Bounty: 50

Say that one has data over time, t, on an outcome, y. There is an event that happens at t==0. One is interested in testing for evidence that the event is related to (I am being cautious on a causal interpretation) a change in the outcome. Importantly, there are many observations for each t (as opposed to a traditional time series when there is only one observation per t).

Suppose also that this is not a situation where the event happened in only or some of the units (e.g., states), but that there is only one unit. This rules out an analysis such as a difference in difference as there is no control group.

In a situation like this, should I use a interrupted time series analysis or regression discontinuity design? If both are fine, what are the differences/advantages/disadvantages? (I am also much more familiar with RDD than the interrupted time series; where is a good place to learn about the latter?)


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