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A quantile approach to US GNP

Yuzhi Cai Orcid Logo

Economic Modelling, Volume: 24

Swansea University Author: Yuzhi Cai Orcid Logo

Abstract

In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model tothe growth rate of real US GNP. We also presented a forecasting method for QSETAR models. Thisforecasting method makes it possible to obtain the predictive quantiles and predictive distribution fun...

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Published in: Economic Modelling
Published: 2007
URI: https://cronfa.swan.ac.uk/Record/cronfa15293
first_indexed 2013-08-22T01:57:37Z
last_indexed 2018-02-09T04:47:08Z
id cronfa15293
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spelling 2013-07-30T10:51:08.1020381 v2 15293 2013-07-30 A quantile approach to US GNP eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2013-07-30 CBAE In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model tothe growth rate of real US GNP. We also presented a forecasting method for QSETAR models. Thisforecasting method makes it possible to obtain the predictive quantiles and predictive distribution functionof xt+m given xt for mN0, and hence any quantities of interest can be derived. Therefore, this new approachallows us to study the US GNP from a distribution point view, rather than from a mean point of view. Theresults obtained in this paper show that the method works very well in practice.© 2007 Elsevier B.V. All rights reserved. Journal Article Economic Modelling 24 979 Bayesian inference; Predictive quantiles; Predictive density functions; QSETAR model; US GNP 30 9 2007 2007-09-30 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University 2013-07-30T10:51:08.1020381 2013-07-30T10:51:08.1030147 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Yuzhi Cai 0000-0003-3509-9787 1
title A quantile approach to US GNP
spellingShingle A quantile approach to US GNP
Yuzhi Cai
title_short A quantile approach to US GNP
title_full A quantile approach to US GNP
title_fullStr A quantile approach to US GNP
title_full_unstemmed A quantile approach to US GNP
title_sort A quantile approach to US GNP
author_id_str_mv eff7b8626ab4cc6428eef52516fda7d6
author_id_fullname_str_mv eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai
author Yuzhi Cai
author2 Yuzhi Cai
format Journal article
container_title Economic Modelling
container_volume 24
publishDate 2007
institution Swansea University
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
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description In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model tothe growth rate of real US GNP. We also presented a forecasting method for QSETAR models. Thisforecasting method makes it possible to obtain the predictive quantiles and predictive distribution functionof xt+m given xt for mN0, and hence any quantities of interest can be derived. Therefore, this new approachallows us to study the US GNP from a distribution point view, rather than from a mean point of view. Theresults obtained in this paper show that the method works very well in practice.© 2007 Elsevier B.V. All rights reserved.
published_date 2007-09-30T06:26:01Z
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score 11.058331

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