Working Paper: NBER ID: w15179
Authors: James J. Heckman; Petra E. Todd
Abstract: The probability of selection into treatment plays an important role in matching and selection models. However, this probability can often not be consistently estimated, because of choice-based sampling designs with unknown sampling weights. This note establishes that the selection and matching procedures can be implemented using propensity scores fit on choice-based samples with misspecified weights, because the odds ratio of the propensity score fit on the choice-based sample is monotonically related to the odds ratio of the true propensity scores.
Keywords: No keywords provided
JEL Codes: C13; C51
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| propensity score (C52) | treatment effects (C22) |
| choice-based sample (C25) | odds ratio of propensity score (C52) |
| estimated propensity scores (C51) | identification of population treatment effects (C22) |
| misspecified weights (C51) | robustness of selection models (C52) |