RT Journal Article SR Electronic T1 Selection into Identification in Fixed Effects Models, with Application to Head Start JF Journal of Human Resources JO J Hum Resour FD University of Wisconsin Press SP 1523 OP 1566 DO 10.3368/jhr.58.5.0520-10930R1 VO 58 IS 5 A1 Miller, Douglas L. A1 Shenhav, Na’ama A1 Grosz, Michel YR 2023 UL http://jhr.uwpress.org/content/58/5/1523.abstract AB Many papers use fixed effects (FE) to identify causal impacts. We document that when treatment status only varies within some FE groups (for example, families, for family fixed effects), FE can induce nonrandom selection of groups into the identifying sample. To address this, we introduce a reweighting-on-observables estimator that can help recover the average treatment effect for policy-relevant populations. We apply these insights to reexamine the long-term effects of Head Start in the PSID and the CNLSY and find that the reweighted estimates are frequently smaller than the FE estimates. This underscores concerns with the external validity of FE estimates. The tools that we propose can strengthen the validity of this approach.