Description
Title: Forecasting for the Optimal COVID-19 Infection Rates to Maintain Thailand’s Economic Circular Flows
Abstract: During the COVID-19 pandemic in Thailand from Q1 2020 to Q1 2021, we examined the changes in the daily number of COVID-19 cases in response to the real GDP. The study’s objective was to determine the maximum number of COVID-19 cases necessary to keep the nation’s economy operating smoothly. The majority of the economies around the world have been focusing on and attempting to answer this question. Dynamic stochastic general equilibrium (DSGE) models were introduced in our theoretical model, with a focus on Bayesian inference. According to the study’s findings, 3000 cases per month or 9000 cases per quarter are the most reasonable number of COVID-19 cases that still maintain the country’s economy’s circulation. This demonstrates how the growth of Thailand’s real GDP is significantly impacted by the number of COVID-19 cases reported each day. The findings of empirical studies can be used by economists and policymakers to develop guidelines or policies that can be put into place to reduce the number of infections to acceptable levels in order to prevent a lockdown in Thailand. Although lockdown can be used to contain the COVID-19 outbreak, it cannot be used continuously.
Keywords: Bayesian; DSGE; COVID-19; Thailand’s economy circulation; number of coronavirus disease 2019 cases; the optimal number of COVID-19 cases
Paper Quality: SCOPUS / Web of Science Level Research Paper
Subject: Economics
Writer Experience: 20+ Years
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