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EFFICIENT SEMIPARAMETRIC ESTIMATION OF DURATION MODELS WITH UNOBSERVED HETEROGENEITY

Published online by Cambridge University Press:  30 January 2007

Peter Bearse
Affiliation:
University of North Carolina at Greensboro
José Canals-Cerdá
Affiliation:
University of Colorado
Paul Rilstone
Affiliation:
York University

Abstract

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.

Type
Research Article
Copyright
© 2007 Cambridge University Press

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References

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EFFICIENT SEMIPARAMETRIC ESTIMATION OF DURATION MODELS WITH UNOBSERVED HETEROGENEITY
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