JSM 2005 - Toronto

Abstract #302659

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); 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.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page
Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 428
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor: Business and Economics Statistics Section
Abstract - #302659
Title: Combined Estimator of Time Series Conditional Hetroskedasticity
Author(s): Aman Ullah*+ and Santosh Mishra and Liangjun Su
Companies: University of California, Riverside and Oregon State University and Peking University
Address: Dept of Economics, Rivrside, CA, 92521, USA
Keywords: semiparametric models ; nonparametric estimator ; conditional variance
Abstract:

We propose a new combined semiparametric estimator, which incorporates the parametric and nonparametric estimators of the conditional variance in a multiplicative way. We derive bias, variance, and asymptotic normality of the combined estimator. Under correct parametric specification, our estimator can do almost as well as the parametric estimator; whereas, under parametric misspecification, our estimator can still be consistent. It also improves over the nonparametric estimator of Ziegelman (2002) in terms of bias reduction. The superiority of our estimator is verified by Monte Carlo simulation and empirical data analysis.

  • 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 2005 program

JSM 2005 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2005