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

Harvey and Leybourne (2015) construct confidence sets for the timing of a break in level and/or trend, based on inverting sequences of test statistics for a break at all possible dates. These are valid, in the sense of yielding correct asymptotic coverage, for I(0) or I(1) errors. In constructing th...

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Main Authors: Harvey, David I., Leybourne, Stephen J.
Format: Article
Published: Elsevier 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/34999/
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author Harvey, David I.
Leybourne, Stephen J.
author_facet Harvey, David I.
Leybourne, Stephen J.
author_sort Harvey, David I.
building Nottingham Research Data Repository
collection Online Access
description Harvey and Leybourne (2015) construct confidence sets for the timing of a break in level and/or trend, based on inverting sequences of test statistics for a break at all possible dates. These are valid, in the sense of yielding correct asymptotic coverage, for I(0) or I(1) errors. In constructing the tests, location-dependent weights are chosen for values of the break magnitude parameter such that each test conveniently has the same limit null distribution. By not imposing such a scheme, we show that it is generally possible to significantly shorten the length of the confidence sets, whilst maintaining accurate coverage properties.
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spelling nottingham-349992020-05-04T17:55:34Z https://eprints.nottingham.ac.uk/34999/ Improving the length of 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. Harvey and Leybourne (2015) construct confidence sets for the timing of a break in level and/or trend, based on inverting sequences of test statistics for a break at all possible dates. These are valid, in the sense of yielding correct asymptotic coverage, for I(0) or I(1) errors. In constructing the tests, location-dependent weights are chosen for values of the break magnitude parameter such that each test conveniently has the same limit null distribution. By not imposing such a scheme, we show that it is generally possible to significantly shorten the length of the confidence sets, whilst maintaining accurate coverage properties. Elsevier 2016-06-22 Article PeerReviewed Harvey, David I. and Leybourne, Stephen J. (2016) Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown. Economics Letters, 145 . pp. 239-245. ISSN 0165-1765 Level break; Trend break; Stationary; Unit root; Confidence sets http://www.sciencedirect.com/science/article/pii/S0165176516302191 doi:10.1016/j.econlet.2016.06.015 doi:10.1016/j.econlet.2016.06.015
spellingShingle Level break; Trend break; Stationary; Unit root; Confidence sets
Harvey, David I.
Leybourne, Stephen J.
Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
title Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
title_full Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
title_fullStr Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
title_full_unstemmed Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
title_short Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
title_sort improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown
topic Level break; Trend break; Stationary; Unit root; Confidence sets
url https://eprints.nottingham.ac.uk/34999/
https://eprints.nottingham.ac.uk/34999/
https://eprints.nottingham.ac.uk/34999/