论文标题
估计潜在回归器的平均衍生工具：通过推断缓冲库存的应用
Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving
论文作者
论文摘要
本文提出了基于潜在回归剂的两个嘈杂度量的密度加权平均衍生物估计量。这两种措施都有经典错误，可能是不对称的分布。我们表明，所提出的估计器达到了收敛的根N速率，并得出其渐近正态分布以进行统计推断。模拟研究表明，出色的小样本性能支持根 - N渐近差。根据拟议的估计器，我们在非参数消费模型下对边际倾向的子倾向（MPCP）进行了正式测试，并使用非参数分布的永久性收入动力学模型进行了正式测试。将测试应用于最近的四个美国小组收入动力学研究（PSID），我们拒绝了单位MPCP的零假设，而支持亚单位MPCP，从而支持了节省缓冲股模型。
This paper proposes a density-weighted average derivative estimator based on two noisy measures of a latent regressor. Both measures have classical errors with possibly asymmetric distributions. We show that the proposed estimator achieves the root-n rate of convergence, and derive its asymptotic normal distribution for statistical inference. Simulation studies demonstrate excellent small-sample performance supporting the root-n asymptotic normality. Based on the proposed estimator, we construct a formal test on the sub-unity of the marginal propensity to consume out of permanent income (MPCP) under a nonparametric consumption model and a permanent-transitory model of income dynamics with nonparametric distribution. Applying the test to four recent waves of U.S. Panel Study of Income Dynamics (PSID), we reject the null hypothesis of the unit MPCP in favor of a sub-unit MPCP, supporting the buffer-stock model of saving.
