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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ruoyu Chen | en_US |
dc.contributor.author | Chukiat Chaiboonsri | en_US |
dc.contributor.author | Satawat Wannapan | en_US |
dc.date.accessioned | 2022-10-16T06:59:51Z | - |
dc.date.available | 2022-10-16T06:59:51Z | - |
dc.date.issued | 2021-01-01 | en_US |
dc.identifier.issn | 21582440 | en_US |
dc.identifier.other | 2-s2.0-85107396986 | en_US |
dc.identifier.other | 10.1177/21582440211021841 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85107396986&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/75478 | - |
dc.description.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. | en_US |
dc.subject | Arts and Humanities | en_US |
dc.subject | Social Sciences | en_US |
dc.title | The Perspective of Thailand Economy After the Effect of Coronavirus-19 Pandemics: Explication by Dynamic I-O Models and Agent-Based Simulations | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | SAGE Open | en_US |
article.volume | 11 | en_US |
article.stream.affiliations | Anhui University of Finance and Economics | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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