Title: Review of methods for assessing the causal effect of binary interventions from aggregate time-series observational data,
Abstract: Researchers are often interested in assessing the impact of an intervention
on an outcome of interest in situations where the intervention is
non-randomised, information is available at an aggregate level, the
intervention is only applied to one or few units, the intervention is binary,
and there are outcome measurements at multiple time points. In this paper, we
review existing methods for causal inference in the setup just outlined. We
detail the assumptions underlying each method, emphasise connections between
the different approaches and provide guidelines regarding their practical
implementation. Several open problems are identified thus highlighting the need
for future research.