This paper develops a new semiparametric approach for the estimation
of hazard functions in the presence of unobserved heterogeneity. The
hazard function is specified parametrically, whereas the distribution of
the unobserved heterogeneity is indirectly estimated using the method of
kernels. The semiparametric efficiency bounds are derived. The estimator
obtains these bounds in large samples.The
authors thank Yongmiao Chen, James Heckman, Hidehiko Ichimura, Tony
Lancaster, Qi Li, Adrian Pagan, Barry Smith, two anonymous referees, and
the co-editor for helpful input. We particularly thank Steven Stern, who
prompted us toward this line of research. Any errors are those of the
authors. Research funding for Rilstone was provided by the Social Sciences
and Humanities Research Council of Canada.