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Impact of Model Specification Decisions on Unit Root Tests

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  • Atiq-ur-Rehman, Atiq-ur-Rehman
  • Zaman, Asad

Abstract

Performance of unit tests depends on several specification decisions prior to their application e.g., whether or not to include a deterministic trend. Since there is no standard procedure for making such decisions, therefore the practitioners routinely make several arbitrary specification decisions. In Monte Carlo studies, the design of DGP supports these decisions, but for real data, such specification decisions are often unjustifiable and sometimes incompatible with data. We argue that the problems posed by choice of initial specification are quite complex and the existing voluminous literature on this issue treats only certain superficial aspects of this choice. We also show how these initial specifications affect the performance of unit root tests and argue that Monte Carlo studies should include these preliminary decisions to arrive at a better yardstick for evaluating such tests.

Suggested Citation

  • Atiq-ur-Rehman, Atiq-ur-Rehman & Zaman, Asad, 2009. "Impact of Model Specification Decisions on Unit Root Tests," MPRA Paper 19963, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:19963
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    Cited by:

    1. Atiq-ur-Rehman, 2011. "Impact of Model Specification Decisions on Unit Root Tests," International Econometric Review (IER), Econometric Research Association, vol. 3(2), pages 22-33, September.
    2. Asad Zaman, 2012. "Methodological Mistakes and Econometric Consequences," International Econometric Review (IER), Econometric Research Association, vol. 4(2), pages 99-122, September.
    3. Muhammad Irfan Malik & Atiq-ur-Rehman, 2015. "Choice of Spectral Density Estimator in Ng-Perron Test: A Comparative Analysis," International Econometric Review (IER), Econometric Research Association, vol. 7(2), pages 51-63, September.

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    More about this item

    Keywords

    model specification; trend stationary; difference stationary;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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