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RELATIVE POWER OF t TYPE TESTS FOR STATIONARY AND UNIT ROOT PROCESSES

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  • Jesus Gonzalo
  • Tae‐Hwy Lee

Abstract

. This paper shows numerically that the lack of power and size distortions of the Dickey‐Fuller type tests for unit roots (very well documented in the unit root literature) are similar to and in many situations even smaller than the lack of power and size distortions of the standard Student t tests for stationary roots of an autoregressive model.

Suggested Citation

  • Jesus Gonzalo & Tae‐Hwy Lee, 1996. "RELATIVE POWER OF t TYPE TESTS FOR STATIONARY AND UNIT ROOT PROCESSES," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(1), pages 37-47, January.
    • Handle: RePEc:bla:jtsera:v:17:y:1996:i:1:p:37-47
    DOI: 10.1111/j.1467-9892.1996.tb00263.x
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    Cited by:

    1. Tilak Abeysinghe & Gulasekaran Rajaguru, 2009. "A Gaussian Test for Cointegration," Microeconomics Working Papers 22013, East Asian Bureau of Economic Research.
    2. Francesca Di Iorio & Umberto Triacca, 2014. "Testing for A Set of Linear Restrictions in VARMA Models Using Autoregressive Metric: An Application to Granger Causality Test," Econometrics, MDPI, vol. 2(4), pages 1-14, December.
    3. González, M. & Gonzalo, Jesús, 1997. "Threshold unit root models," DES - Working Papers. Statistics and Econometrics. WS 6214, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Jürgen Wolters & Uwe Hassler, 2006. "Unit root testing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 43-58, March.
    5. Gonzalo, Jesus & Lee, Tae-Hwy, 1998. "Pitfalls in testing for long run relationships," Journal of Econometrics, Elsevier, vol. 86(1), pages 129-154, June.
    6. Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
    7. Lim Kai Jie, Shawn & Chadha, Pavneet & Lau, Joshua & Potdar, Nishad, 2012. "Is the Mongolian Equity Market Efficient? Empirical Evidence from Tests of Weak-Form Efficiency," MPRA Paper 41834, University Library of Munich, Germany.
    8. Di Iorio, Francesca & Triacca, Umberto, 2013. "Testing for Granger non-causality using the autoregressive metric," Economic Modelling, Elsevier, vol. 33(C), pages 120-125.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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