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

David Harvey and Stephen Leybourne ()

Discussion Papers from University of Nottingham, Granger Centre for Time Series 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.

Keywords: Level break; Trend break; Stationary; Unit root; Locally best invariant test; confidence sets (search for similar items in EconPapers)
Date: 2014-04
New Economics Papers: this item is included in nep-ecm and nep-ets
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Related works:
Journal Article: Confidence sets for the date of a break in level and trend when the order of integration is unknown (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:not:notgts:14/04

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