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AGE- AND TIME-VARYING PROPORTIONAL HAZARDS MODELSFOR EMPLOYMENT DISCRIMINATION

机译:就业歧视的年龄和时变比例危害模型

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We use a discrete-time proportional hazards model of time to involuntary employment termination. This model enables us to examine both the contin-uous effect of the age of an employee and whether that effect has varied over time, generalizing earlier work [Kadane and Woodworth J. Bus. Econom. Sta-tist. 22 (2004) 182-193]. We model the log hazard surface (over age and time) as a thin-plate spline, a Bayesian smoothness-prior implementation of penalized likelihood methods of surface-fitting [Wahba (1990) Spline Models for Observational Data. SIAM]. The nonlinear component of the surface has only two parameters, smoothness and anisotropy. The first, a scale parameter, governs the overall smoothness of the surface, and the second, anisotropy, controls the relative smoothness over time and over age. For any fixed value of the anisotropy parameter, the prior is equivalent to a Gaussian process with linear drift over the time–age plane with easily computed eigenvectors and eigenvalues that depend only on the configuration of data in the time–age plane and the anisotropy parameter. This model has application to legal cases in which a company is charged with disproportionately disadvantaging older workers when deciding whom to terminate. We illustrate the application of the modeling approach using data from an actual discrimination case.
机译:我们使用时间的离散时间比例风险模型来自愿终止雇佣关系。该模型使我们既可以检查雇员年龄的连续影响,又可以检查这种影响是否随时间变化,从而概括了早期的工作[Kadane and Woodworth J. Bus。经济。战略师。 22(2004)182-193]。我们将对数危险表面(随着年龄和时间的变化)建模为薄板样条,这是贝叶斯平滑度优先于表面拟合的惩罚似然方法的实现方法[Wahba(1990)样条模型用于观测数据。暹]。表面的非线性成分只有两个参数:平滑度和各向异性。第一个参数是比例参数,控制表面的总体平滑度,第二个参数各向异性是控制时间和年龄范围内的相对平滑度。对于各向异性参数的任何固定值,先验等效于高斯过程,该过程在时域平面上具有线性漂移,具有容易计算的特征向量和特征值,该特征向量和特征值仅取决于时域平面中的数据配置和各向异性参数。该模型适用于法律案件,在该案件中,公司在决定终止人员时被指控严重不利于年长的工人。我们使用来自实际判别案例的数据说明了建模方法的应用。

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