Abstract

The Almon technique is a widely used estimation procedure for the distributed lag model (DLM) to encounter the problems associated with direct application of the ordinary least squares method to this model. The Almon estimator may be sensitive to outliers in the y-direction. This study is aimed to propose a robust estimator for parameter vector of the DLM when data set is contaminated with outliers. Moreover, this study proposes the robust t-tests and confidence intervals for the lag coefficients. Performance of our proposed estimator is evaluated through the Monte Carlo simulations by comparing the estimated mean squared error while the performance of t-tests and confidence intervals is evaluated using the null rejection rates and coverage, respectively. The simulation results reveal an attractive performance of the proposed methods in the presence of outliers in the y-direction.

摘要

Almon 技术是一种广泛使用的分布式滞后模型 (DLM) 估计程序，用于解决与直接将普通最小二乘法应用于该模型相关的问题。Almon 估计器可能对y方向上的异常值敏感。本研究旨在提出一种当数据集受到异常值污染时 DLM 参数向量的鲁棒估计器。此外，本研究提出了滞后系数的稳健t检验和置信区间。我们提出的估计器的性能通过蒙特卡罗模拟进行评估，通过比较估计的均方误差和t的性能-分别使用零拒绝率和覆盖率来评估测试和置信区间。仿真结果表明，在y方向存在异常值的情况下，所提出的方法具有有吸引力的性能。