Abstract #302330

This is the preliminary program for the 2003 Joint Statistical Meetings in San Francisco, California. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 2-5, 2003); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2003 Program page
JSM 2003 Abstract #302330
Activity Number: 244
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #302330
Title: Unit Root Testing via the Stationary Bootstrap
Author(s): Cameron Parker*+ and Dimitris N. Politis
Companies: University of California, San Diego and University of California, San Diego
Address: 9176-1 Regents Rd., La Jolla, CA, 92093,
Keywords: integrated time series ; resampling ; stationary bootstrap ; unit root testing
Abstract:

A nonparametric, residual-based stationary bootstrap procedure is proposed for testing for the presence of a unit root in a given time series. The procedure gives a way of generating a pseudoseries which mimics the original in terms of dependence structure but that has the property of ensuring the presence of a unit root. The proposed test has an advantage over many others in the literature in that it is valid for a wide class of weakly dependent processes and is not based on any parametric assumptions on the data generating process. In addition, our bootstrap methodology is valid for a very general class of test statistics. Large sample theory is developed and the asymptotic validity of the test is shown via a bootstrap functional limit theorem. The particular case of a least squares statistic is discussed in detail, and simulations to investigate the sample performance of the procedure are performed in this case.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2003 program

JSM 2003 For information, contact meetings@amstat.org or phone (703) 684-1221. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2003