Statistical Papers

, Volume 45, Issue 2, pp 249–266 | Cite as

Implementing unit roost tests in ARMA models of unknow order

  • Ismael Sánchez


This paper compares the performance of classical and recent unit root tests based on different estimation procedures, including fitting ARMA models of unknown orders. The article also introduces an estimator of the spectral density function that is based on the estimation of an ARMA model with data previously detrended by GLS. The Monte Carlo experiment shows that tests improve their performance if an ARMA model is estimated, instead of an autoregressive approximation. The best results are obtained by tests based on the estimation of the spectral density function.


Ordinary Little Square Unit Root Test ARMA Model Error Correction Model Generalize Little Square 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • Ismael Sánchez
    • 1
  1. 1.Departmento de Estadística y EconometríaMadrid(Spain)

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