This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic causal effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...

Lechner and Miquel (2001) approached the causal analysis of sequences of interventions from a potential outcome perspective based on selection on observable type of assumptions (sequential conditional independence assumptions). Lechner (2004) proposed matching estimators for this framework....

This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic casual effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...

This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic causal effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...