Nonparametric identification of accelerated failure time competing risks models

Sokbae (Simon) Lee and Arthur Lewbel

No CWP14/10, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract:

We provide new conditions for identification of accelerated failure time competing risks models. These include Roy models and some auction models. In our set up, unknown regression functions and the joint survivor function of latent disturbance terms are all nonparametric. We show that this model is identified given covariates that are independent of latent errors, provided that a certain rank condition is satisfied. We present a simple example in which our rank condition for identification is verified. Our identification strategy does not depend on identification at infinity or near zero, and it does not require exclusion assumptions. Given our identification, we show estimation can be accomplished using sieves.

Date: 2010-06-05
New Economics Papers: this item is included in nep-ecm
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Related works:
Journal Article: NONPARAMETRIC IDENTIFICATION OF ACCELERATED FAILURE TIME COMPETING RISKS MODELS (2013)
Working Paper: Nonparametric Identification of Accelerated Failure Time Competing Risks Models (2011)
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