Analysis of GDP in Countries allied to Indonesia using a Combination of the GSTAR Model and Verification using Statistical Quality Control

The Generalized Space-Time Autoregressive (GSTAR) model is used to model GDP growth rates in Indonesia, Malaysia, Singapore, and Brunei Darussalam, allied countries. Southeast Asian countries have cultural and historical linkages and often share economic tendencies. GSTAR is used because it can represent GDP dynamics' complex spatial and temporal relationships. Historical GDP data for the four countries from 1975 to the present is collected. The GSTAR model models regional interdependence and temporal patterns in these economies' geographical and temporal linkages. To test GSTAR model accuracy and robustness, control chart analysis is done. Control charts help monitor and assess economic model stability. The data used in this study is GDP data in Indonesia, Malaysia, Singapore, Brunei Darussalam, and Thailand, was collected from 1975 to 2021. This study discusses GSTAR model projections with actual GDP growth rate data to identify economic abnormalities in these linked countries. This research has major consequences for regional politicians, economists, and businesses. Policy decisions, investment strategies, and GSTAR model economic forecasts can benefit from understanding these countries' GDP growth interdependencies and patterns. Control chart analysis also assures the model accurately tracks economic trends over time. Finally, the GSTAR model and control chart analysis give a complete framework for modeling and testing allied GDP growth rates

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Publication Details

Journal
International Journal of Computing Science and Applied Mathematics
Published
2025-02-21
DOI
https://doi.org/10.12962/j24775401.v11i1.21007
Primary Topic
Global Trade and Competitiveness
Type
article
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article

Analysis of GDP in Countries allied to Indonesia using a Combination of the GSTAR Model and Verification using Statistical Quality Control

Nurfitri Imro’ah, Nur’ainul Miftahul Huda, Nani Fitria Arini, Tarisa Umairah et al.
International Journal of Computing Science and Applied Mathematics
Global Trade and Competitiveness
article

Analysis of GDP in Countries allied to Indonesia using a Combination of the GSTAR Model and Verification using Statistical Quality Control

Nurfitri Imro’ah, Nur’ainul Miftahul Huda, Nani Fitria Arini, Tarisa Umairah, Dewi Setyo Utami
article en

Abstract

The Generalized Space-Time Autoregressive (GSTAR) model is used to model GDP growth rates in Indonesia, Malaysia, Singapore, and Brunei Darussalam, allied countries. Southeast Asian countries have cultural and historical linkages and often share economic tendencies. GSTAR is used because it can represent GDP dynamics' complex spatial and temporal relationships. Historical GDP data for the four countries from 1975 to the present is collected. The GSTAR model models regional interdependence and temporal patterns in these economies' geographical and temporal linkages. To test GSTAR model accuracy and robustness, control chart analysis is done. Control charts help monitor and assess economic model stability. The data used in this study is GDP data in Indonesia, Malaysia, Singapore, Brunei Darussalam, and Thailand, was collected from 1975 to 2021. This study discusses GSTAR model projections with actual GDP growth rate data to identify economic abnormalities in these linked countries. This research has major consequences for regional politicians, economists, and businesses. Policy decisions, investment strategies, and GSTAR model economic forecasts can benefit from understanding these countries' GDP growth interdependencies and patterns. Control chart analysis also assures the model accurately tracks economic trends over time. Finally, the GSTAR model and control chart analysis give a complete framework for modeling and testing allied GDP growth rates

International Journal of Computing Science and Applied MathematicsVol. 11(1)
Tanjungpura University (ID)
Decent work and economic growth
Openalex Percentile: Top 91%
Global Trade and Competitiveness
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