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Panel unit root tests in the presence of a multifactor error structure

Author

Listed:
  • Pesaran, M. Hashem
  • Vanessa Smith, L.
  • Yamagata, Takashi
Abstract
This paper extends the cross-sectionally augmented panel unit root test (CIPS) proposed by Pesaran (2007) to the case of a multifactor error structure, and proposes a new panel unit root test based on a simple average of cross-sectionally augmented Sargan–Bhargava statistics (CSB). The basic idea is to exploit information regarding the m unobserved factors that are shared by k observed time series in addition to the series under consideration. Initially, we develop the tests assuming that m0, the true number of factors, is known and show that the limit distribution of the tests does not depend on any nuisance parameters, so long as k≥m0−1. Small sample properties of the tests are investigated by Monte Carlo experiments and are shown to be satisfactory. Particularly, the proposed CIPS and CSB tests have the correct size for all combinations of the cross section (N) and time series (T) dimensions considered. The power of both tests rises with N and T, although the CSB test performs better than the CIPS test for smaller sample sizes. The various testing procedures are illustrated with empirical applications to real interest rates and real equity prices across countries.

Suggested Citation

  • Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    • Handle: RePEc:eee:econom:v:175:y:2013:i:2:p:94-115
    DOI: 10.1016/j.jeconom.2013.02.001
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    More about this item

    Keywords

    Panel unit root tests; Cross section dependence; Multifactor error structure; Fisher inflation parity; Real equity prices;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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