Unit Root Test in Panel Data Basing on the Limiting Spectral Distribution of Large-Dimensional Random Matrix

被引:0
|
作者
Zhao Xiaofang [1 ]
Wang Cheng [1 ]
Miao Baiqi [1 ]
机构
[1] Univ Sci & Technol China, Dept Stat & Finance, Hefei 230026, Peoples R China
关键词
Unit root test; Panel Data; Large-dimensional Random Matrix; Limiting Spectral Distribution; SAMPLE COVARIANCE MATRICES; EIGENVALUES;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
With the development of Computer information technology, large-dimensional panel data models have been introduced into the econometric researches during the past three decades, in order to solve the more and more complex economic phenomenons. As we know, the one-dimensional time series has the across time feature, so the panel data does. Then, when we confront with the panel data, we must be sure it is stationary. That means we should test unit root before regressing in order to avoid spurious regression. This article provides a new unit root test method for panel data which is basing on the theory of the limiting spectral distribution of large-dimensional random matrix.
引用
收藏
页码:458 / 466
页数:9
相关论文
共 50 条
  • [21] The accuracy of normal approximation in a heterogeneous panel data unit root test
    Kristian Jönsson
    Statistical Papers, 2008, 49 : 565 - 579
  • [22] Panel data unit root test with structural break: A Bayesian approach
    Kumar, Jitendra
    Agiwal, Varun
    HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, 2019, 48 (04): : 1213 - 1231
  • [23] Limiting spectral distribution of the sample covariance matrix of the windowed array data
    Ehsan Yazdian
    Saeed Gazor
    Mohammad Hasan Bastani
    EURASIP Journal on Advances in Signal Processing, 2013
  • [24] Testing covariance structure of large-dimensional data based on Wald's score test
    Jiang, Dandan
    Zhang, Qibin
    Hui, Yongchang
    RANDOM MATRICES-THEORY AND APPLICATIONS, 2017, 6 (03)
  • [25] Limiting spectral distribution of the sample covariance matrix of the windowed array data
    Yazdian, Ehsan
    Gazor, Saeed
    Bastani, Mohammad Hasan
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2013,
  • [26] On the limiting spectral distribution for a large class of symmetric random matrices with correlated entries
    Banna, Marwa
    Merlevede, Florence
    Peligrad, Magda
    STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 2015, 125 (07) : 2700 - 2726
  • [27] Large-dimensional covariance matrix estimation and its application with RCM using high frequency data
    Ni X.
    Qian L.
    Zhao H.
    Huang S.
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2019, 39 (08): : 1943 - 1953
  • [28] Limiting spectral distribution of a new random matrix model with dependence across rows and columns
    Pfaffel, Oliver
    Schlemm, Eckhard
    LINEAR ALGEBRA AND ITS APPLICATIONS, 2012, 436 (09) : 2966 - 2979
  • [29] RANDOM MATRIX-IMPROVED KERNELS FOR LARGE DIMENSIONAL SPECTRAL CLUSTERING
    Ali, Hafiz Tiomoko
    Kammoun, Abla
    Couillet, Romain
    2018 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP), 2018, : 453 - 457
  • [30] Anomaly Detection of Distribution Network Synchronous Measurement Data Based on Large Dimensional Random Matrix
    Chen, Zhongming
    Zhang, Yaoyu
    Qing, Chuan
    Liu, Jierong
    Tang, Jiaqi
    Pang, Jingzhi
    ADVANCES IN ARTIFICIAL SYSTEMS FOR MEDICINE AND EDUCATION II, 2020, 902 : 449 - 458