NONPARAMETRIC IDENTIFICATION OF ACCELERATED FAILURE TIME COMPETING RISKS MODELS
提出了加速失效时间竞争风险模型（包括Roy模型和拍卖模型）的识别新条件，在协变量与潜在误差独立且满足秩条件时，非参数回归函数和联合生存函数可被识别，不依赖无穷远或零附近的识别及排除性假设。
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.