Publication Type
Journal Article
Version
submittedVersion
Publication Date
7-2018
Abstract
Based on the Girsanov theorem, this paper obtains the exact distribution of the maximum likelihood estimator of structural break point in a continuous time model. The exact distribution is asymmetric and tri-modal, indicating that the estimator is biased. These two properties are also found in the finite sample distribution of the least squares (LS) estimator of structural break point in the discrete time model, suggesting the classical long-span asymptotic theory is inadequate. The paper then builds a continuous time approximation to the discrete time model and develops an in-fill asymptotic theory for the LS estimator. The in-fill asymptotic distribution is asymmetric and tri-modal and delivers good approximations to the finite sample distribution. To reduce the bias in the estimation of both the continuous time and the discrete time models, a simulation-based method based on the indirect estimation (IE) approach is proposed. Monte Carlo studies show that IE achieves substantial bias reductions.
Keywords
Structural break, Bias reduction, Indirect estimation, Exact distribution, In-fill asymptotics
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
205
Issue
1
First Page
156
Last Page
176
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2018.03.009
Publisher
Elsevier: 24 months
Citation
JIANG, Liang; WANG, Xiaohu; and YU, Jun.
New distribution theory for the estimation of structural break point in mean. (2018). Journal of Econometrics. 205, (1), 156-176.
Available at: https://ink.library.smu.edu.sg/soe_research/2221
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/10.1016/j.jeconom.2018.03.009