The Perspective of Thailand Economy After the Effect of Coronavirus-19 Pandemics: Explication by Dynamic I-O Models and Agent-Based Simulations

Abstract

The panic surrounding the COVID-19 pandemic has collapsed world economic systems. Thailand is no exception. Evidently, domestic-industrial activities in many countries have nearly stopped, and international sectors have abruptly disintegrated. Unemployment has become critical, and business viability has run into trouble. This article illustrates the potential solutions to these issues linked to Thailand’s domestic and international-trade economies by econometrically applying sectoral forecasting analyses and simulations because the pandemic has not only caused physical damage, but also a negative chain in worldwide economic systems. Methodologically, dynamic input-output (I-O) analysis is circumspectly employed to obtain foresight on some predominantly industrial sectors that could potentially rescue the Thai domestic economy from the depression of 2020–2022. The I-O tables are sourced from official data of the Asian Development Bank (ADB). For the international-trade scenario, the agent-based model and simulations are used to forecast the future trends of macroeconomic responses. The two methods, dynamic I-O models and agent-based simulations, are the current means capable of sensibly predicting macroeconomic responses for monitoring the upcoming years. The empirical outcomes can clearly predict upcoming events that will be beneficial for policy implementations.

Using simulation modelling and systems science to help contain COVID‐19: A systematic review

“…Ten papers investigated the disruptions and uncertainties to the supply chain caused by the COVID‐19 pandemic (Achmad et al, 2021 ; Burgos & Ivanov, 2021 ; Choudhary et al, 2021 ; Duan et al, 2021 ; Ghadge et al, 2021 ; Moosavi & Hosseini, 2021 ; Nguyen, 2021 ; Sinha et al, 2020 ) and the post‐pandemic recovery strategies (Ivanov, 2021 ; Rahman et al, 2021 ). Twenty papers explored the other sectors at the national and regional levels, including industrial network (Song et al, 2020 ), tourism (Gu et al, 2021 ; Luo et al, 2021 ), national security (Prikazchikov et al, 2021 ), food–energy–water (Calder et al, 2021 ), economy (Chen et al, 2021 ; Fosco & Zurita, 2021 ; Inoue et al, 2021 ; Inoue & Todo, 2020 ; Sharma et al, 2021 ), financial (Spelta et al, 2021 ), social activity (de Brito Jr et al, 2021 ; Schmidt & Albert, 2021 ; Weibrecht et al, 2021 ), healthcare (Schlüter et al, 2021 ), employment (Marreros et al, 2021 ) and transport and land‐use (Habib & Anik, 2021 ). As the pandemic led to great collateral damage or process disruption to a variety of organizations, including banks (Shahabi et al, 2021 ), airlines (Delcea et al, 2020 ; Milne et al, 2020 , 2021 ), ambulatory endoscopy centres (Das, 2020 ), heart clinics (Zeinalnezhad et al, 2020 ), laboratories (Lim et al, 2020 ) and outpatient dialysis services (Allen, Bhanji, et al, 2020 ), necessary countermeasures were adopted to lower the risk of transmission and to improve effectiveness of these measures.…”

The Impact of Gastronomic Tourism on Thailand Economy: Under the Situation of COVID-19 Pandemic

“…In the second term of Equation 7 was represented by the time changing for a new output ( i ) was employed to be the capital input to produce the output ( j ) of economic sectors in the economy. Because of the time changing impact on every economic sector ( Šafr, 2016 ) especially 89 sectors in Thailand ( Chen et al, 2021 ), which it is can be written the mathematical formula by Equation 9…”