Effects of a signal-to-noise ratio on finite sample inference for cointegrating vectors

Takamitsu Kurita

Mathematics and Computers in Simulation (MATCOM), 2010, vol. 80, issue 10, 2033-2039

Abstract: This paper investigates effects of a signal-to-noise ratio on finite sample inference for cointegrating vectors. The ratio is defined as a measure of the magnitude of a permanent shock relative to a transitory shock. According to Monte Carlo experiments conducted in this paper, a high signal-to-noise ratio tends to reduce size distortions of a likelihood-based test statistic for a hypothesis on cointegrating vectors; a low signal-to-noise ratio is, in contrast, prone to amplify the size distortions. The experiments demonstrate that the performance of a bootstrap method also depends on the volume of the signal-to-noise ratio. Finally, an empirical illustration is presented.

Keywords: Signal-to-noise ratio; Permanent shock; Transitory shock; Finite sample inference; Cointegrating vector (search for similar items in EconPapers)
JEL-codes: C32 C52 C63 (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475410000832
Full text for ScienceDirect subscribers only

Related works:
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:eee:matcom:v:80:y:2010:i:10:p:2033-2039

DOI: 10.1016/j.matcom.2010.03.008

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().