KTH/CESIS Working Paper Series in Economics and Institutions of Innovation
The Effectiveness of Information Criteria in Determining Unit Root and Trend Status
Abstract: This paper compares the performance of using an
information criterion, such as the Akaike information criterion or the
Schwarz (Bayesian) information criterion, rather than hypothesis testing in
consideration of the presence of a unit root for a variable and, if
unknown, the presence of a trend in that variable. The investigation is
performed through Monte Carlo simulations. Properties considered are
frequency of choosing the unit root status correctly, predictive
performance, and frequency of choosing an appropriate subsequent action on
the examined variable (first differencing, detrending, or doing nothing).
Relative performance is considered in a minimax regret framework. The
results indicate that use of an information criterion for determining unit
root status and (if necessary) trend status of a variable can be
competitive to alternative hypothesis testing strategies.
Keywords: Unit Root; Stationarity; Model Selection; Minimax regret; Information Criteria; (follow links to similar papers)
JEL-Codes: C22; (follow links to similar papers)
33 pages, February 11, 2010
Before downloading any of the electronic versions below
you should read our statement on
for viewing Postscript files and the
Acrobat Reader for viewing and printing pdf files.
Full text versions of the paper:
Questions (including download problems) about the papers in this series should be directed to Vardan Hovsepyan ()
Report other problems with accessing this service to Sune Karlsson ()
or Helena Lundin ().
Design by Joachim Ekebom