Publication Type
Journal Article
Version
submittedVersion
Publication Date
12-2020
Abstract
Limit theory for regressions involving local to unit roots (LURs) is now used extensively in time series econometric work, establishing power properties for unit root and cointegration tests, assisting the construction of uniform confidence intervals for autoregressive coefficients, and enabling the development of methods robust to departures from unit roots. The present paper shows how to generalize LUR asymptotics to cases where the localized departure from unity is a time varying function rather than a constant. Such a functional local unit root (FLUR) model has much greater generality and encompasses many cases of additional interest that appear in practical work, including structural break formulations that admit subperiods of unit root, local stationary and local explosive behavior within a given sample. Point optimal FLUR tests are constructed in the paper to accommodate such cases and demonstrate how the power envelope changes in situations of practical interest. Against FLUR alternatives, conventional constant point optimal tests can be asymptotically infinitely deficient in power, with poor finite sample power performance particularly when the departure from unity occurs early in the sample period. New analytic explanation for this phenomenon is provided. Simulation results are reported and some implications for empirical practice are examined.
Keywords
Functional local unit root, Local to unity, Uniform confidence interval, Unit root model
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
219
Issue
2
First Page
231
Last Page
259
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2020.03.003
Publisher
Elsevier: 24 months
Citation
BYKHOVSKAYA, Anna and PHILLIPS, Peter C. B..
Point optimal testing with roots that are functionally local to unity. (2020). Journal of Econometrics. 219, (2), 231-259.
Available at: https://ink.library.smu.edu.sg/soe_research/2367
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.2020.03.003