Let's suppose I want to measure the impact of M&A in the hospital sector. I have a dataset containing hundreds of hospitals, a quality indicator and the type of ownership for each over a time period of 5 years (2005 - 2010). Some of the hospitals changed their ownership in 2005, some in 2008 and some didn't changed at all. For the hospitals that changed from nonprofit to profit, I want to measure if there was an impact on the quality. So basically, I want to compare the quality before and after the change of ownership and compared to other hospitals, which don't changed their ownership.

I thought about using the difference in difference approach, but I guess there's a problem, because I don't have that one year of intervention I can compare. Instead I have many different years (some hospitals may changed the ownership in 2006, some in 2009).

Could anybody please explain to me, which (regression-)model would be the right to use here?

I appreciate any kind of help!

Thanks in advance.

  • $\begingroup$ Perhaps you'd like to take a look at the literature on staggered interventions : psantanna.com/files/Callaway_SantAnna_2020.pdf Just one example, there are many more that you can retrieve from the literature reviews mentioned there. Brantly Callaway, Pedro H.C. Sant’Anna,Difference-in-Differences with multiple time periods,Journal of Econometrics,Volume 225, Issue 2,2021,Pages 200-230,ISSN 0304-4076,doi.org/10.1016/j.jeconom.2020.12.001. $\endgroup$
    – Luis
    Jun 20 at 15:26


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