Hu, Xiaohua and Zhang, Zhongwei 
ORCID: https://orcid.org/0000-0001-6622-0346
(2019)
Application of generalized intervention analysis model.
Scholars Journal of Economics, Business and Management, 6 (1).
pp. 17-23.
ISSN 2348-8875
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Text (Published version)
SJEBM-61-17-23-c.pdf Available under License Creative Commons Attribution 4.0. Download (313kB) | Preview |
Abstract
In this paper, the intervention analysis model has been generalized in the sense that its intervention function either being a jumping function used to describe the continuing intervention or a unit impulse function used to describe the transient intervention has been replaced with a unified function, which represents an intervention process, denotes the amplitude (or strength) of the impact of intervention events at intervention time, denotes the decay factor of continuing process. Applying the generalized model to predict the Gross Domestic Product (GDP) of Hainan province from 1989 to 2016, as a Government intervention was introduced in 2010, results in a 60% of improvement in terms of the Root Mean Square Error (RMSE), when compared with the original model.
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| Item Type: | Article (Commonwealth Reporting Category C) |
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| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Published version made available in accordance with a Creative Commons Attribution license 4.0. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019) |
| Date Deposited: | 29 May 2019 05:18 |
| Last Modified: | 25 Jun 2019 01:09 |
| Uncontrolled Keywords: | intervention event, jump function, unit impulsive function, generalized intervention analysis model, Hainan GDP |
| Fields of Research (2008): | 01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics 14 Economics > 1403 Econometrics > 140303 Economic Models and Forecasting |
| Fields of Research (2020): | 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490501 Applied statistics 38 ECONOMICS > 3802 Econometrics > 380203 Economic models and forecasting |
| Identification Number or DOI: | doi:10.21276/sjebm.2019.6.1.4 |
| URI: | http://eprints.usq.edu.au/id/eprint/35767 |
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