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

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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 resorting to Monte Carlo simulations, considering a range of plausible data-generating processes. As of this writing, there is no study providing guidance on the use of this type of procedures in empirical situations, with the exception of the limited studies of McCabe et al. (1997) and Haug (1996). We also analyse 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 in terms of power and size distrortions.

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  • Vasco J. Gabriel, 2001. "Tests for the Null Hypothesis of Cointegration: a Monte Carlo Comparison," NIPE Working Papers 7/2001, NIPE - Universidade do Minho.
    • Handle: RePEc:nip:nipewp:7/2001
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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.

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    More about this item

    Keywords

    Cointegration; Tests; Monte Carlo.;
    All these keywords.

    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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