Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Using National Longitudinal Survey data, the authors estimate proportional hazard models in order to learn whether it is more difficult for employers to identify female nonquitters than male nonquitters. They find that women may be a higher risk than men in the overall sample because they are more likely to be "movers" for unobserved reasons. When the authors focus on a relatively recent birth cohort, however, they find that it is no longer difficult to identify female nonquitters. Unobserved heterogeneity becomes an insignificant factor among women and virtually all determinants of turnover are observable at the time of hire. Copyright 1992 by University of Chicago Press.