Publication Type
Journal Article
Version
submittedVersion
Publication Date
12-2016
Abstract
In this paper, we consider the problem of determining the number of structural changes in multiple linear regression models via group fused Lasso. We show that with probability tending to one, our method can correctly determine the unknown number of breaks, and the estimated break dates are sufficiently close to the true break dates. We obtain estimates of the regression coefficients via post Lasso and establish the asymptotic distributions of the estimates of both break ratios and regression coefficients. We also propose and validate a data-driven method to determine the tuning parameter. Monte Carlo simulations demonstrate that the proposed method works well in finite samples. We illustrate the use of our method with a predictive regression of the equity premium on fundamental information.
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometric Theory
Volume
32
Issue
6
First Page
1376
Last Page
1433
ISSN
0266-4666
Identifier
10.1017/S0266466615000237
Publisher
Cambridge University Press
Citation
QIAN, Junhai and SU, Liangjun.
Shrinkage estimation of regression models with multiple structural changes. (2016). Econometric Theory. 32, (6), 1376-1433.
Available at: https://ink.library.smu.edu.sg/soe_research/1910
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/S0266466615000237