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Estimating a semi-parametric duration model without specifying heterogeneity

机译:在不指定异质性的情况下估计半参数持续时间模型

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This paper presents a new estimator for the mixed proportional hazard model that allows for a nonparametric baseline hazard and time-varying regressors. In particular, this paper allows for discrete measurement of the durations as happens often in practice. The integrated baseline hazard and all parameters are estimated at the regular rate, root N, where N is the number of individuals. A hazard model is a natural framework for time-varying regressors. In particular, if a flow or a transition probability depends on a regressor that changes with time, a hazard model avoids the curse of dimensionality that would arise from interacting the regressors at each point in time with one another. This paper also presents a new test to detect unobserved heterogeneity
机译:本文提出了一种混合比例风险模型的新估计量,该模型考虑了非参数基准风险和时变回归因素。特别是,本文允许在实践中经常进行的持续时间的离散测量。综合基准​​危害和所有参数均以固定比率(根N)估算,其中N是个体数。危害模型是随时间变化的回归变量的自然框架。特别是,如果流量或过渡概率取决于随时间变化的回归变量,则危害模型可以避免因在每个时间点相互影响回归变量而引起的维度诅咒。本文还提出了检测未观察到的异质性的新测试

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