A residual-based nonparametric variance ratio no-cointegration test

被引:0
|
作者
Reichold, Karsten [1 ,2 ]
机构
[1] TU Wien, Inst Stat & Math Methods Econ, Vienna, Austria
[2] TU Wien, Inst Stat & Math Methods Econ, Wiedner Hauptstr 8-10, A-1040 Vienna, Austria
关键词
Unit root; cointegration; variance ratio test; local asymptotic power; UNIT-ROOT TESTS; POWER;
D O I
10.1111/jtsa.12734
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
It is prominently stated in the literature that local asymptotic power properties serve as a useful indicator for the performance of residual-based no-cointegration tests in finite samples. However, this article comes to an opposing conclusion. In particular, we show that Breitung's (2002, Journal of Econometrics 108, 343-363) nonparameteric variance ratio unit root test applied to regression residuals serves as a no-cointegration test but is inferior to its competitors from a local asymptotic power perspective. Nevertheless, in finite samples, the variance ratio test has good size properties, competitive power, and the convenience of being tuning parameter free. In general, we find that short-run dynamics in the error process can have considerably larger detrimental effects on the performance of residual-based no-cointegration tests in finite samples than changes in the only nuisance parameter affecting local asymptotic power of the tests. The results serve as a warning for practitioners and lead to interesting directions for future research.
引用
收藏
页码:847 / 856
页数:10
相关论文
共 50 条
  • [31] A residual based test for the null hypothesis of cointegration
    Xiao, ZJ
    ECONOMICS LETTERS, 1999, 64 (02) : 133 - 141
  • [32] A vibration model residual-based sequential probability ratio test framework for structural health monitoring
    Kopsaftopoulos, Fotis P.
    Fassois, Spilios D.
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2015, 14 (04): : 359 - 381
  • [33] On Nonparametric Residual Variance Estimation
    Liitiainen, Elia
    Corona, Francesco
    Lendasse, Amaury
    NEURAL PROCESSING LETTERS, 2008, 28 (03) : 155 - 167
  • [34] On Nonparametric Residual Variance Estimation
    Elia Liitiäinen
    Francesco Corona
    Amaury Lendasse
    Neural Processing Letters, 2008, 28 : 155 - 167
  • [35] A residual-based test for autocorrelation in quantile regression models
    Huo, Lijuan
    Kim, Tae-Hwan
    Kim, Yunmi
    Lee, Dong Jin
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2017, 87 (07) : 1305 - 1322
  • [36] Residuals-based tests for the null of no-cointegration: An analytical comparison
    Pesavento, Elena
    JOURNAL OF TIME SERIES ANALYSIS, 2007, 28 (01) : 111 - 137
  • [37] THE ESTIMATION OF RESIDUAL VARIANCE IN NONPARAMETRIC REGRESSION
    BUCKLEY, MJ
    EAGLESON, GK
    SILVERMAN, BW
    BIOMETRIKA, 1988, 75 (02) : 189 - 199
  • [38] Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies
    Miller, J. Isaac
    Wang, Xi
    JOURNAL OF TIME SERIES ANALYSIS, 2016, 37 (06) : 810 - 824
  • [39] NONPARAMETRIC-ESTIMATION OF RESIDUAL VARIANCE REVISITED
    SEIFERT, B
    GASSER, T
    WOLF, A
    BIOMETRIKA, 1993, 80 (02) : 373 - 383
  • [40] Sequential Residual-Based RAIM
    Joerger, Mathieu
    Pervan, Boris
    PROCEEDINGS OF THE 23RD INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS 2010), 2010, : 3167 - 3180