Assessing the Causal Effect of Binary Interventions from Observational Panel Data with Few Treated Units
2019
Researchers are often challenged with assessing the impact of an
intervention on an outcome of interest in situations where the intervention
is nonrandomised, the intervention is only applied to one or few units, the
intervention is binary, and outcome measurements are available at multiple
time points. In this paper, we review existing methods for causal inference
in these situations. We detail the assumptions underlying each method, emphasize
connections between the different approaches and provide guidelines
regarding their practical implementation. Several open problems are identified
thus highlighting the need for future research.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
43
References
19
Citations
NaN
KQI