论文标题
动态异质分配回归面板模型，并应用于劳动收入流程
Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes
论文作者
论文摘要
我们介绍了一个动态分布回归面板数据模型，具有各个单位的异质系数。主要兴趣的对象是这些系数的功能，包括预测结果变量的一步和固定横截面分布。系数及其功能是通过固定效应方法估算的。我们研究了这些功能如何响应初始条件或协变量的反事实变化而变化。我们还确定了与未知系数异质性程度的鲁棒性有关的均匀性问题，并提出了一种横截面自举法，以均匀地对功能值值对象进行有效的推理。我们通过对个人收入动态的经验应用来展示我们的方法的实用性。采用年度收入动态数据小组研究，我们确定了实质系数异质性的存在。然后，我们重点介绍了我们的方法论可以解决的一些重要的经验问题。首先，我们量化负劳动收入冲击对未来劳动收入分配的影响。
We introduce a dynamic distribution regression panel data model with heterogeneous coefficients across units. The objects of primary interest are functionals of these coefficients, including predicted one-step-ahead and stationary cross-sectional distributions of the outcome variable. Coefficients and their functionals are estimated via fixed effect methods. We investigate how these functionals vary in response to counterfactual changes in initial conditions or covariate values. We also identify a uniformity problem related to the robustness of inference to the unknown degree of coefficient heterogeneity, and propose a cross-sectional bootstrap method for uniformly valid inference on function-valued objects. We showcase the utility of our approach through an empirical application to individual income dynamics. Employing the annual Panel Study of Income Dynamics data, we establish the presence of substantial coefficient heterogeneity. We then highlight some important empirical questions that our methodology can address. First, we quantify the impact of a negative labor income shock on the distribution of future labor income.
