Asymptotic Properties of the Estimators in Mildly Stable Unit Root Process

Xiyao Zhang (), Hui Jiang (), Weilin Xiao () and Weigang Wang ()
Additional contact information
Xiyao Zhang: Nanjing University of Aeronautics and Astronautics
Hui Jiang: Nanjing University of Aeronautics and Astronautics
Weilin Xiao: Zhejiang University
Weigang Wang: Zhejiang Gongshang University

Methodology and Computing in Applied Probability, 2025, vol. 27, issue 2, 1-22

Abstract: Abstract In this paper, we study asymptotic properties of the Yule-Walker estimator and ordinary least squares (OLS) estimator in a mildly stable unit root process with Gaussian noise. By the change of measure method and asymptotic analysis technique, we establish the exponential nonuniform Berry-Esseen bounds of the two estimators. As applications, the optimal uniform Berry-Esseen bounds and optimal Cramér-type moderate deviation principles can be obtained.

Keywords: Berry-Esseen bound; Change of measure method; Cramér-type moderate deviation principle; Unit root process; Yule-Walker estimator; 60F10; 60G22; 62N02 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11009-025-10175-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:metcap:v:27:y:2025:i:2:d:10.1007_s11009-025-10175-5

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-025-10175-5

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().