Publication Type
Journal Article
Version
acceptedVersion
Publication Date
12-2018
Abstract
The intercept of the binary response model is irregularly identified when the supports of both the special regressor V and the error term ε are the whole real line. This leads to the estimator of the intercept having potentially a slower than √n convergence rate, which can result in a large estimation error in practice. This paper imposes addition tail restrictions which guarantee the regular identification of the intercept and thus the √n-consistency of its estimator. We then propose an estimator that achieves the √n rate. Finally, we extend our tail restrictions to a full-blown model with endogenous regressors.
Keywords
Extremal quantile, Tail index
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometric Theory
Volume
34
Issue
6
First Page
1180
Last Page
1206
ISSN
0266-4666
Identifier
10.1017/S026646661700041X
Publisher
Cambridge University Press
Citation
TAN, Lili and ZHANG, Yichong.
Root-n consistency of intercept estimators in a binary response model under tail restrictions. (2018). Econometric Theory. 34, (6), 1180-1206.
Available at: https://ink.library.smu.edu.sg/soe_research/2028
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/S026646661700041X