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Detecting Unbalanced Regressions Using the Durbin-Watson Test

Author

Listed:
  • Marmol, F.
  • Reboredo, J.C.

Abstract

The aim of this paper is to provide a simulation-based analysis on the bahavior of the Durbin-Watson statistic as a misspecification test againstthe presence of unbalanced regressions among nonstationary fractionally integrated process. Theoretically, it is well-known that this statistic converges in probability to zero under this setup. In finite samples, however, from our Monte Carlo experiments it shows up a rather surprising behaviour with respect to the expected asymptotic one.

Suggested Citation

  • Marmol, F. & Reboredo, J.C., 1997. "Detecting Unbalanced Regressions Using the Durbin-Watson Test," UFAE and IAE Working Papers 380.97, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
  • Handle: RePEc:aub:autbar:380.97
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    More about this item

    Keywords

    ECONOMETRICS;

    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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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