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Tests for the Null Hypothesis of Cointegration: A Monte Carlo Comparison

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  • Vasco Gabriel

Abstract

The aim of this paper is to compare the relative performance of several tests for the null hypothesis of cointegration, in terms of size and power in finite samples. This is carried out using Monte Carlo simulations for a range of plausible data-generating processes. We also analyze the impact on size and power of choosing different procedures to estimate the long run variance of the errors. We found that the parametrically adjusted test of McCabe et al. (1997) is the most well-balanced test, displaying good power and relatively few size distortions.

Suggested Citation

  • Vasco Gabriel, 2003. "Tests for the Null Hypothesis of Cointegration: A Monte Carlo Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 411-435.
    • Handle: RePEc:taf:emetrv:v:22:y:2003:i:4:p:411-435
    DOI: 10.1081/ETC-120025897
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    Cited by:

    1. Ahmet Faruk Aysan & Ibrahim Guney & Nicoleta Isac & Asad ul Islam Khan, 2022. "The probabilities of type I and II error of null of cointegration tests: A Monte Carlo comparison," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-15, January.
    2. Gabriel, Vasco J., 2003. "Cointegration and the joint confirmation hypothesis," Economics Letters, Elsevier, vol. 78(1), pages 17-25, January.
    3. Nicoleta ISAC & Cosmin DOBRIN & Mehmood HUSSAN & Asad ul Islam KHAN & Alina- Andreea MARIN, 2020. "On The Ranks Of Tests Having Null Of Cointegration: A Monte Carlo Comparison," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 12(2), pages 58-69, June.
    4. Vasco J. Gabriel & Martin Sola & Zacharias Psaradakis, 2002. "Residual-based tests for cointegration and multiple regime shifts," NIPE Working Papers 7/2002, NIPE - Universidade do Minho.

    More about this item

    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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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