Publication Type
Journal Article
Version
submittedVersion
Publication Date
6-2010
Abstract
Least absolute deviations (LAD) estimation of linear time series models is considered under conditional heteroskedasticity and serial correlation. The limit theory of the LAD estimator is obtained without assuming the finite density condition for the errors that is required in standard LAD asymptotics. The results are particularly useful in application of LAD estimation to financial time series data.
Keywords
Asymptotic leptokurtosis, Convex function, Infinite density, Least absolute deviations, Median, Weak convergence
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometric Theory
Volume
26
Issue
3
First Page
953
Last Page
962
ISSN
0266-4666
Identifier
10.1017/S0266466609990703
Publisher
Cambridge University Press
Citation
CHO, Jin Seo; HAN, Chirok; and Peter C. B. PHILLIPS.
LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities. (2010). Econometric Theory. 26, (3), 953-962.
Available at: https://ink.library.smu.edu.sg/soe_research/1819
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1017/S0266466609990703