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A simple GMM estimator for the semi-parametric mixed proportional hazard model

Bijwaard, G.E. and Ridder, G. (2009) A simple GMM estimator for the semi-parametric mixed proportional hazard model.

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Official URL: http://depot.knaw.nl/7582

Abstract

Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a Semi-Parametric Mixed Proportional Hazard Model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity. We extend the Linear Rank Estimator (LRE) of Tsiatis (1990) and Robins and Tsiatis (1991) to this class of models. The optimal LRE is a two-step estimator. We propose a simple first-step estimator that is close to optimal if there is no unobserved heterogeneity. The efficiency gain associated with the optimal LRE increases with the degree of unobserved heterogeneity.

Item Type:Report
Institutes:Ned. Interdisc. Demografisch Instituut (NIDI)
ID Code:7582
Deposited On:09 Nov 2009 01:00
Last Modified:26 Oct 2010 14:21

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