Publication Type
Journal Article
Version
acceptedVersion
Publication Date
4-2019
Abstract
Economic theory often predicts a “tipping point” effect due to multiple equilibria. Linear threshold regressions estimate the “tipping point” by assuming at the same time that the response variable is linear in an index of covariates. However, economic theory rarely imposes a specific functional form, but rather predicts a monotonic relationship between the response variable and the index. We propose new, rank-based, estimators for both the “tipping point” and other regression coefficients, exploiting only the monotonicity condition. We derive the asymptotic properties of these estimators by establishing a more general result for M-estimators of U-processes with a change-point due to a covariate threshold. We finally apply our method to provide new estimates of the “tipping point” of social segregation in four major cities in the United States.
Keywords
Simulation-based inference, bootstrap, monotone rank estimator, partial rank estimator
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Business and Economic Statistics
Volume
37
Issue
2
First Page
248
Last Page
259
ISSN
0735-0015
Identifier
10.1080/07350015.2017.1319373
Publisher
Taylor & Francis: STM, Behavioural Science and Public Health Titles
Citation
TAN, Lili and ZHANG, Yichong.
M-estimators of U-processes with a change-point due to a covariate threshold. (2019). Journal of Business and Economic Statistics. 37, (2), 248-259.
Available at: https://ink.library.smu.edu.sg/soe_research/1997
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/10.1080/07350015.2017.1319373