A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model
Smooth Transition Autogressive (STAR) model has been employed in a number of current studies dealing with non-linearities. The usefulness of this model has been documented in these studies. However, the population statistical properties of the parameters in this model remain unknown. This study atte...
| Main Authors: | , , , |
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| Format: | Working Paper |
| Language: | English |
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Universiti Putra Malaysia
2013
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| Online Access: | http://ir.unimas.my/id/eprint/189/ http://ir.unimas.my/id/eprint/189/1/A_Non_parametric_Bootstrap_Simulation_Study_in_ESTAR_Model.pdf |
| _version_ | 1848834494206836736 |
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| author | Liew, Khim Sen Ahmad Zubaidi, Baharumshah Choo, Wei Chong Habshah, Midi |
| author_facet | Liew, Khim Sen Ahmad Zubaidi, Baharumshah Choo, Wei Chong Habshah, Midi |
| author_sort | Liew, Khim Sen |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Smooth Transition Autogressive (STAR) model has been employed in a number of current studies dealing with non-linearities. The usefulness of this model has been documented in these studies. However, the population statistical properties of the parameters in this model remain unknown. This study attempts to investigate these properties through a non-parametric bootstrap simulation study. The exponential STAR model of order one, which is sufficient in providing us the necessary information on the linear and non-linear parameters as well as the speed of transition of the STAR model despite its simplicity, is employed in this study. This study also investigates the size effect of the bootstrapped estimators and their confidence intervals by varying the number of bootstrap replications. Results of this study show that their empirical distribution are asymmetrical in nature with the linear parameter being positively skewed and the non-linear and transition parameters being negatively skewed. Besides, we find that the normality theory over rejects the significance of the estimated transition parameter. Another interesting point worth mentioning is that the minimum number of replications needed for the bootstrap confidence interval to be a good approximate of the standard normal one is 500. |
| first_indexed | 2025-11-15T05:52:52Z |
| format | Working Paper |
| id | unimas-189 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T05:52:52Z |
| publishDate | 2013 |
| publisher | Universiti Putra Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-1892020-08-12T07:10:56Z http://ir.unimas.my/id/eprint/189/ A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model Liew, Khim Sen Ahmad Zubaidi, Baharumshah Choo, Wei Chong Habshah, Midi H Social Sciences (General) HB Economic Theory HG Finance Smooth Transition Autogressive (STAR) model has been employed in a number of current studies dealing with non-linearities. The usefulness of this model has been documented in these studies. However, the population statistical properties of the parameters in this model remain unknown. This study attempts to investigate these properties through a non-parametric bootstrap simulation study. The exponential STAR model of order one, which is sufficient in providing us the necessary information on the linear and non-linear parameters as well as the speed of transition of the STAR model despite its simplicity, is employed in this study. This study also investigates the size effect of the bootstrapped estimators and their confidence intervals by varying the number of bootstrap replications. Results of this study show that their empirical distribution are asymmetrical in nature with the linear parameter being positively skewed and the non-linear and transition parameters being negatively skewed. Besides, we find that the normality theory over rejects the significance of the estimated transition parameter. Another interesting point worth mentioning is that the minimum number of replications needed for the bootstrap confidence interval to be a good approximate of the standard normal one is 500. Universiti Putra Malaysia 2013-12-05 Working Paper NonPeerReviewed text en http://ir.unimas.my/id/eprint/189/1/A_Non_parametric_Bootstrap_Simulation_Study_in_ESTAR_Model.pdf Liew, Khim Sen and Ahmad Zubaidi, Baharumshah and Choo, Wei Chong and Habshah, Midi (2013) A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model. [Working Paper] (Submitted) |
| spellingShingle | H Social Sciences (General) HB Economic Theory HG Finance Liew, Khim Sen Ahmad Zubaidi, Baharumshah Choo, Wei Chong Habshah, Midi A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model |
| title | A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model |
| title_full | A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model |
| title_fullStr | A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model |
| title_full_unstemmed | A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model |
| title_short | A Non-parametric Bootstrap Simulation Study in ESTAR (1) Model |
| title_sort | non-parametric bootstrap simulation study in estar (1) model |
| topic | H Social Sciences (General) HB Economic Theory HG Finance |
| url | http://ir.unimas.my/id/eprint/189/ http://ir.unimas.my/id/eprint/189/1/A_Non_parametric_Bootstrap_Simulation_Study_in_ESTAR_Model.pdf |