Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point
In this paper we consider the problem of testing for the co-integration rank of a vector autoregressive process in the case where a trend break may potentially be present in the data. It is known that un-modelled trend breaks can result in tests which are incorrectly sized under the null hypothesis...
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Elsevier
2016
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| Online Access: | https://eprints.nottingham.ac.uk/31793/ |
| _version_ | 1848794274275000320 |
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| author | Harris, David Leybourne, Stephen J. Taylor, A.M. Robert |
| author_facet | Harris, David Leybourne, Stephen J. Taylor, A.M. Robert |
| author_sort | Harris, David |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In this paper we consider the problem of testing for the co-integration rank of a vector autoregressive process in the case where a trend break may potentially be present in the data. It is known that un-modelled trend breaks can result in tests which are incorrectly sized under the null hypothesis and inconsistent under the alternative hypothesis. Extant procedures in this literature have attempted to solve this inference problem but require the practitioner to either assume that the trend break date is known or to assume that any trend break cannot occur under the co-integration rank null hypothesis being tested. These procedures also assume the autoregressive lag length is known to the practitioner. All of these assumptions would seem unreasonable in practice. Moreover in each of these strands of the literature there is also a presumption in calculating the tests that a trend break is known to have happened. This can lead to a substantial loss in finite sample power in the case where a trend break does not in fact occur. Using information criteria based methods to select both the autoregressive lag order and to choose between the trend break and no trend break models, using a consistent estimate of the break fraction in the context of the former, we develop a number of procedures which deliver asymptotically correctly sized and consistent tests of the co-integration rank regardless of whether a trend break is present in the data or not. By selecting the no break model when no trend break is present, these procedures also avoid the potentially large power losses associated with the extant procedures in such cases. |
| first_indexed | 2025-11-14T19:13:35Z |
| format | Article |
| id | nottingham-31793 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:13:35Z |
| publishDate | 2016 |
| publisher | Elsevier |
| recordtype | eprints |
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| spelling | nottingham-317932017-10-17T11:26:10Z https://eprints.nottingham.ac.uk/31793/ Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point Harris, David Leybourne, Stephen J. Taylor, A.M. Robert In this paper we consider the problem of testing for the co-integration rank of a vector autoregressive process in the case where a trend break may potentially be present in the data. It is known that un-modelled trend breaks can result in tests which are incorrectly sized under the null hypothesis and inconsistent under the alternative hypothesis. Extant procedures in this literature have attempted to solve this inference problem but require the practitioner to either assume that the trend break date is known or to assume that any trend break cannot occur under the co-integration rank null hypothesis being tested. These procedures also assume the autoregressive lag length is known to the practitioner. All of these assumptions would seem unreasonable in practice. Moreover in each of these strands of the literature there is also a presumption in calculating the tests that a trend break is known to have happened. This can lead to a substantial loss in finite sample power in the case where a trend break does not in fact occur. Using information criteria based methods to select both the autoregressive lag order and to choose between the trend break and no trend break models, using a consistent estimate of the break fraction in the context of the former, we develop a number of procedures which deliver asymptotically correctly sized and consistent tests of the co-integration rank regardless of whether a trend break is present in the data or not. By selecting the no break model when no trend break is present, these procedures also avoid the potentially large power losses associated with the extant procedures in such cases. Elsevier 2016-06-03 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/31793/1/CVARtrendbreakR4final.pdf Harris, David, Leybourne, Stephen J. and Taylor, A.M. Robert (2016) Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point. Journal of Econometrics, 192 (24). pp. 451-467. ISSN 0304-4076 Co-integration rank; vector autoregression; error-correction model; trend break; break point estimation; information criteria http://www.sciencedirect.com/science/article/pii/S0304407616300136 doi:10.1016/j.jeconom.2016.02.010 doi:10.1016/j.jeconom.2016.02.010 |
| spellingShingle | Co-integration rank; vector autoregression; error-correction model; trend break; break point estimation; information criteria Harris, David Leybourne, Stephen J. Taylor, A.M. Robert Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point |
| title | Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point |
| title_full | Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point |
| title_fullStr | Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point |
| title_full_unstemmed | Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point |
| title_short | Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point |
| title_sort | tests of the co-integration rank in var models in the presence of a possible break in trend at an unknown point |
| topic | Co-integration rank; vector autoregression; error-correction model; trend break; break point estimation; information criteria |
| url | https://eprints.nottingham.ac.uk/31793/ https://eprints.nottingham.ac.uk/31793/ https://eprints.nottingham.ac.uk/31793/ |