Publication Type
Journal Article
Version
submittedVersion
Publication Date
5-2025
Abstract
Limit theory for functional coefficient cointegrating regression was recently found to be considerably more complex than earlier understood. The issues were explained and correct limit theory derived for the kernel weighted local level estimator in Phillips and Wang (2023b). The present paper provides complete limit theory for the general kernel weighted local th order polynomial estimators of the functional coefficient and the coefficient derivatives. Both stationary and nonstationary regressors are allowed. Implications for bandwidth selection are discussed. An adaptive procedure to select the fit order is proposed and found to work well. A robust -ratio is constructed following the new limit theory, which corrects and improves the usual -ratio in the literature. The robust -ratio is valid and works well regardless of the properties of the regressors, thereby providing a unified procedure to compute the -ratio and facilitating practical inference. Testing constancy of the functional coefficient is also considered. Finite sample studies are provided that corroborate the new asymptotic theory.
Keywords
bandwidth selection, functional-coefficient cointegration, local p-th order polynomial approximation, robust t-ratio
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
249
First Page
1
Last Page
30
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2025.106007
Publisher
Elsevier
Citation
Wang, Ying and PHILLIPS, Peter C. B..
Limit theory for local polynomial estimation of functional coefficient models with possibly integrated regressors. (2025). Journal of Econometrics. 249, 1-30.
Available at: https://ink.library.smu.edu.sg/soe_research/2868
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.2025.106007