Published online by Cambridge University Press: 21 February 2013
We provide new conditions for identification of accelerated failure time competing risks models. These include Roy models and some auction models. In our setup, 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.
We would like to thank Xiaohong Chen for very helpful discussions at the early stage of this project. We also would like to thank Hidehiko Ichimura, Ivana Komunjer, Rosa Matzkin, Whitney Newey, Jean-Marc Robin, Elie Tamer, and two anonymous referees for helpful comments. This work was supported by the Economic and Social Research Council for the ESRC Centre for Microdata Methods and Practice (RES-589-28-0001) and a small research grant (RES-000-22-2761), by a European Research Council grant (ERC-2009-StG-240910-ROMETA), and by the National Research Foundation of Korea grant funded by the Korean Government (NRF-2011-327-B00073).