Propensity score analysis is a statistical method that balances pre-existing differences across treatment conditions achieving a similar condition as randomization and thus, allowing the estimation of causal effects in non-randomized experimental designs. The four stages in propensity score analysis are (1) propensity score estimation, (2)…

This paper estimates the treatment effect of grade repetitions in French junior high schools, using a value-added test score as outcome and quarter of birth as instrument. With linear two-stage least squares, local average treatment effect is estimated at around 1.6 times the standard deviation of the achievement gain. With non-linear…

In this article we propose several modeling choices to extend propensity score analysis to clustered data. We describe different possible model specifications for estimation of the propensity score: single-level model, fixed effects model, and two random effects models. We also consider both conditioning within clusters and conditioning across…