What is counterfactual treatment?

What is counterfactual treatment?

Counterfactuals and potential outcomes Obviously, the outcome can be observed only (or more precisely, at most) under one, and not under both conditions. The treatment that individual i actually does not receive is called counterfactual treatment.

What is the counterfactual effect?

In its simplest form, counterfactual impact evaluation (CIE) is a method of comparison which involves comparing the outcomes of interest of those having benefitted from a policy or programme (the “treated group”) with those of a group similar in all respects to the treatment group (the “comparison/control group”), the …

What is the sample average treatment effect?

In contrast, the sample average treatment effect (SATE) is the mean difference in the counterfactual outcomes for the study units. The sample parameter is easily interpretable and arguably the most relevant when the study units are not sampled from some specific super-population of interest.

Why is a counterfactual important?

Counterfactual analysis enables evaluators to attribute cause and effect between interventions and outcomes. The ‘counterfactual’ measures what would have happened to beneficiaries in the absence of the intervention, and impact is estimated by comparing counterfactual outcomes to those observed under the intervention.

How to compare results to the counterfactual?

Compare results to the counterfactual One of the three tasks involved in understanding causes is to compare the observed results to those you would expect if the intervention had not been implemented – this is known as the ‘counterfactual’. Many discussions of impact evaluation argue that it is essential to include a counterfactual.

What does the term counterfactual treatment refer to?

The treatment that individual i actually does not receive is called counterfactual treatment. Likewise, the outcome under this treatment is referred to as counterfactual or potential outcome. The term potential outcome reflects the perspective before the treatment assignment and is more widespread in statistics (e.g. [ 8 ]).

Which is the best definition of counterfactual inference?

Counterfactual inference can, in a way, be defined as the prediction of an alternate reality. Given a pair of a cause and its effect, counterfactual inference focuses on answering the question — “What would have been the effect of a different treatment applied to the unit keeping all the other conditions constant?”.

How is the average outcome among the treatment units?

Thus the average outcome among the treatment units serves as a counterfactual for the average outcome among the control units. The differences between these two averages is the ATE, which is an estimate of the central tendency of the distribution of unobservable individual-level treatment effects.