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Access type: UnknownSubject: search.filters.subject.Bayesian vector autoregression

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    ICT and Thai Economic Growth Nexus in the Bayesian VAR Model
    (2021-07-08)
    Rojniruttikul, Nuttawut
    ;
    Vajrapatkul, Adirek
    This work presents the effects of internet usage, mobile subscription, ICT export, and ICT import on Gross Domestic Product in the context of Thailand by utilizing the Bayesian vector autoregression (BVAR) model with the 24 periods of annual modified data running from 1993 to 2016. This model shows the interactions between these five variables and the forecast of GDP. The results from this work revealed that internet usage, mobile subscription, and ICT export positively affect GDP in the short run manner. Whereas ICT import showed little evidence of a negative effect on GDP. Also, this work confirms the superior forecast performance of BVER over traditional VAR. According to the results of the analysis, we hence recommend that government authorities should 1) invest or support the investments in ICT infrastructure related to internet and mobile utilization, 2) reduce the cost of acquiring internet and mobile equipment and the cost of accessing the internet and mobile service, and 3) support the ICT exporters.
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    On the Forecast of Thai Industry Value Added
    (2021-07-08)
    Rojniruttikul, Nuttawut
    ;
    Vajrapatkul, Adirek
    Industry value added is a crucial factor that keep the manufacturers to survive in the high business competitive environment. Also it encourage the economic growth by offering the opportunity to generate high income from international trade. Thus achieving in creating high level of value added become the point of interest for both manufacturers and governments. Hence, to investigate what determine such value added. This work is designed to present the effects of some business and economic variables, namely gross domestic product, consumer price index, domestic credit to the private sector, and gross capital formation on industry value added in the context of Thailand by utilizing the Bayesian vector autoregression (BVAR) model with the 58 periods of annual modified data running from 1960 to 2019. This model shows the interactions between these five variables and the forecast of industry value-added. The results from this work revealed that there exist the Granger Causality and reactions between domestic credit to private, domestic capital formulation, domestic general price level, growth of the gross domestic product, and industry value-added. Thus, we recommend that government authorities should 1) encourage more credit to manufacturers, 2) invest more in industrial-facilitate infrastructure and support more on private investment in capital formulation, 3) induce more country income, and 4) control the general price level within the country.