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The probabilities of type I and II error of null of cointegration tests: A Monte Carlo comparison

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  • Ahmet Faruk Aysan
  • Ibrahim Guney
  • Nicoleta Isac
  • Asad ul Islam Khan

Abstract

This paper evaluates the performance of eight tests with null hypothesis of cointegration on basis of probabilities of type I and II errors using Monte Carlo simulations. This study uses a variety of 132 different data generations covering three cases of deterministic part and four sample sizes. The three cases of deterministic part considered are: absence of both intercept and linear time trend, presence of only the intercept and presence of both the intercept and linear time trend. It is found that all of tests have either larger or smaller probabilities of type I error and concluded that tests face either problems of over rejection or under rejection, when asymptotic critical values are used. It is also concluded that use of simulated critical values leads to controlled probability of type I error. So, the use of asymptotic critical values may be avoided, and the use of simulated critical values is highly recommended. It is found and concluded that the simple LM test based on KPSS statistic performs better than rest for all specifications of deterministic part and sample sizes.

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  • 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.
    • Handle: RePEc:plo:pone00:0259994
    DOI: 10.1371/journal.pone.0259994
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    Cited by:

    1. Khan, Asad Ul Islam & Shahbaz, Muhammad & Napari, Ayuba, 2023. "Subsample stability, change detection and dynamics of oil and metal markets: A recursive approach," Resources Policy, Elsevier, vol. 83(C).

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