Size corrected significance tests in Seemingly Unrelated Regressions with autocorrelated errors

Spyridon D. Symeondes, Yiannis Karavias and Elias Tzavalis

Discussion Papers from University of Nottingham, Granger Centre for Time Series Econometrics

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.

Keywords: Linear regression; S.U.R. models; stochastic expansions; asymptotic approximations; AR(1) errors. (search for similar items in EconPapers)
Date: 2014-01
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nottingham.ac.uk/research/groups/grangercentre/documents/14-01.pdf (application/pdf)

Related works:
Journal Article: Size corrected Significance Tests in Seemingly Unrelated Regressions with Autocorrelated Errors (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:not:notgts:14/01

Access Statistics for this paper

More papers in Discussion Papers from University of Nottingham, Granger Centre for Time Series Econometrics School of Economics University of Nottingham University Park Nottingham NG7 2RD. Contact information at EDIRC.
Bibliographic data for series maintained by ().