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Size corrected significance tests in Seemingly Unrelated Regressions with autocorrelated errors

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  • Spyridon D. Symeondes
  • Yiannis Karavias
  • Elias Tzavalis

Abstract

Refined asymptotic methods are used to produce degrees-of-freedom adjusted Edgeworth and Cornish-Fisher size corrections of the t and F testing procedures for the parameters of a S.U.R. model with serially correlated errors. The corrected tests follow the Student-t and F distributions, respectively, with an approximation error of order O(\tau^3), where \tau = 1/sqrt(T) and T is the number of time observations. Monte Carlo simulatitions provide evidence that the size corrections suggested hereby have better finite sample properties, compared to the asymptotc testing procedures (either standard or Edgeworth corrected), which do not adjust for the degrees of freedom.

Suggested Citation

  • Spyridon D. Symeondes & Yiannis Karavias & Elias Tzavalis, 2014. "Size corrected significance tests in Seemingly Unrelated Regressions with autocorrelated errors," Discussion Papers 14/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    • Handle: RePEc:not:notgts:14/01
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    More about this item

    Keywords

    Linear regression; S.U.R. models; stochastic expansions; asymptotic approximations; AR(1) errors.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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