EconBiz - Find Economic Literature
    • Logout
    • Change account settings
  • A-Z
  • Beta
  • About EconBiz
  • News
  • Thesaurus (STW)
  • Academic Skills
  • Help
  •  My account 
    • Logout
    • Change account settings
  • Login
EconBiz - Find Economic Literature
Publications Events
Search options
Advanced Search history
My EconBiz
Favorites Loans Reservations Fines
    You are here:
  • Home
  • Search: subject:"Yule–Walker estimator"
Narrow search

Narrow search

Year of publication
Subject
All
Autoregressive time series 1 GMM 1 Local polynomial 1 Moving average 1 Oracle efficiency 1 Yule-Walker estimator 1 Yule–Walker estimator 1 autoregressive process 1 efficiency gains 1 empirical autocorrelations 1
more ... less ...
Online availability
All
Free 1 Undetermined 1
Type of publication
All
Article 1 Book / Working Paper 1
Language
All
Undetermined 2
Author
All
BROZE, Laurence 1 FRANCQ, Christian 1 Qiu, D. 1 Shao, Q. 1 Yang, L. 1 ZAKOIAN, Jean-Michel 1
Institution
All
Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain 1
Published in...
All
CORE Discussion Papers 1 Journal of Multivariate Analysis 1
Source
All
RePEc 2
Showing 1 - 2 of 2
Cover Image
Efficient inference for autoregressive coefficients in the presence of trends
Qiu, D.; Shao, Q.; Yang, L. - In: Journal of Multivariate Analysis 114 (2013) C, pp. 40-53
Time series often contain unknown trend functions and unobservable error terms. As is known, Yule–Walker estimators are asymptotically efficient for autoregressive time series. The focus of this article is the Yule–Walker estimators for time series with trends. A nonparametric detrending...
Persistent link: https://www.econbiz.de/10010594228
Saved in:
Cover Image
Non redundancy of high order moment conditions for efficient GMM estimation of weak AR processes
BROZE, Laurence; FRANCQ, Christian; ZAKOIAN, Jean-Michel - Center for Operations Research and Econometrics (CORE), … - 2000
This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent (see Kim, Qian and Schmidt (1999)), using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only...
Persistent link: https://www.econbiz.de/10005065430
Saved in:
A service of the
zbw
  • Sitemap
  • Plain language
  • Accessibility
  • Contact us
  • Imprint
  • Privacy

Loading...