Skip to main content

Research Repository

Advanced Search

Confidence sets for the date of a break in level and trend when the order of integration is unknown

Harvey, David I.; Leybourne, Stephen J.

Authors

DAVID HARVEY dave.harvey@nottingham.ac.uk
Professor of Econometrics



Abstract

We propose methods for constructing confidence sets for the timing of a break in level and/or trend that have asymptotically correct coverage for both I(0) and I(1) processes. These are based on inverting a sequence of tests for the break location, evaluated across all possible break dates. We separately derive locally best invariant tests for the I(0) and I(1) cases; under their respective assumptions, the resulting confidence sets provide correct asymptotic coverage regardless of the magnitude of the break. We suggest use of a pre-test procedure to select between the I(0)- and I(1)-based confidence sets, and Monte Carlo evidence demonstrates that our recommended procedure achieves good finite sample properties in terms of coverage and length across both I(0) and I(1) environments. An application using US macroeconomic data is provided which further evinces the value of these procedures.

Citation

Harvey, D. I., & Leybourne, S. J. (2015). Confidence sets for the date of a break in level and trend when the order of integration is unknown. Journal of Econometrics, 184(2), https://doi.org/10.1016/j.jeconom.2014.09.004

Journal Article Type Article
Publication Date Feb 1, 2015
Deposit Date Apr 6, 2016
Publicly Available Date Apr 6, 2016
Journal Journal of Econometrics
Print ISSN 0304-4076
Electronic ISSN 0304-4076
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 184
Issue 2
DOI https://doi.org/10.1016/j.jeconom.2014.09.004
Keywords Level break; Trend break; Stationary; Unit root; Locally best invariant test; Confidence sets
Public URL https://nottingham-repository.worktribe.com/output/985100
Publisher URL http://www.sciencedirect.com/science/article/pii/S0304407614001894

Files





You might also like



Downloadable Citations