Change point in a panel data refers to the time when a change(s) takes a place in the cross-sections of the panel. This key time helps practitioners to analyze the root cause(s) of the change manifested itself to the process. This paper attempts to introduce a new hybrid approach called Double-CUSUM-Modified EWMA (DCME) which is capable of providing a high sensitivity of detecting the change point in a panel data. The step change analysis of this paper addressees that the performance of the proposed model is more sensitive compared to the best available methods based on location accuracy and power terms. Furthermore this paper develops the proposed hybrid method using the binary method to identify the multiple change points in a panel data. Several numerical examples are considered to evaluate the capability of the proposed hybrid method.

面板数据中的更改点是指在面板横截面中发生更改的时间。这个关键时间可以帮助从业人员分析过程本身所表现出的变化的根本原因。本文试图介绍一种称为Double-CUSUM-Modified EWMA（DCME）的新混合方法，该方法能够提供高灵敏度来检测面板数据中的变化点。本文的逐步变化分析指出，与基于位置精度和功率项的最佳可用方法相比，该模型的性能更为敏感。此外，本文提出了一种使用二进制方法来识别面板数据中多个变化点的混合方法。考虑了几个数值示例来评估所提出的混合方法的能力。