Interrupted Time Series

When I first heard about this design, I had an impression that it is a difficult impact evaluation design.  At first, it was really confusing but I persisted and looked for simpler reading material that explains the concept.  From that time on, I got intrigued about this approach and I even went to the extent of buying two books from Amazon on time series.

So what is interrupted time series?

Interrupted time series (ITS) is a quasi-experimental design that uses historical data to show the impact and to infer the causal connection between the outcome of interest and the intervention.  In this design, there is no random allocation of treatment to program participants.  The counterfactual or the situation if the intervention was not introduced is the forecasted value of variable being measured. The reasoning behind this design is that if it can be shown that an "interruption" or break in the trend at the time of introduction of the intervention, then such break provides support to causal argument in favor of the intervention in the absence of other competing explanations.    

I tried playing around the employment rate from 2002 to 2014 to see if I could apply ITS in this data set.  Lo and behold! There is an interruption in the trend in 2005!  The blue line represents the intervention.  What happened in 2005 that caused abrupt change in the employment trend?  That is something subject for a proper research.  

Source of Data: NSCB