Spatiotemporal Impact of Trade Policy Variables on Asian Manufacturing Hubs: Bayesian Global Vector Autoregression Model
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866916660333510656 |
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| author | Sua, Lutfu S. Wang, Haibo Huang, Jun |
| author_facet | Sua, Lutfu S. Wang, Haibo Huang, Jun |
| contents | A novel spatiotemporal framework using diverse econometric approaches is proposed in this research to analyze relationships among eight economy-wide variables in varying market conditions. Employing Vector Autoregression (VAR) and Granger causality, we explore trade policy effects on emerging manufacturing hubs in China, India, Malaysia, Singapore, and Vietnam. A Bayesian Global Vector Autoregression (BGVAR) model also assesses interaction of cross unit and perform Unconditional and Conditional Forecasts. Utilizing time-series data from the Asian Development Bank, our study reveals multi-way cointegration and dynamic connectedness relationships among key economy-wide variables. This innovative framework enhances investment decisions and policymaking through a data-driven approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_17790 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Spatiotemporal Impact of Trade Policy Variables on Asian Manufacturing Hubs: Bayesian Global Vector Autoregression Model Sua, Lutfu S. Wang, Haibo Huang, Jun Econometrics A novel spatiotemporal framework using diverse econometric approaches is proposed in this research to analyze relationships among eight economy-wide variables in varying market conditions. Employing Vector Autoregression (VAR) and Granger causality, we explore trade policy effects on emerging manufacturing hubs in China, India, Malaysia, Singapore, and Vietnam. A Bayesian Global Vector Autoregression (BGVAR) model also assesses interaction of cross unit and perform Unconditional and Conditional Forecasts. Utilizing time-series data from the Asian Development Bank, our study reveals multi-way cointegration and dynamic connectedness relationships among key economy-wide variables. This innovative framework enhances investment decisions and policymaking through a data-driven approach. |
| title | Spatiotemporal Impact of Trade Policy Variables on Asian Manufacturing Hubs: Bayesian Global Vector Autoregression Model |
| topic | Econometrics |
| url | https://arxiv.org/abs/2503.17790 |