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Forecasting for the Optimal Numbers of COVID-19 Infection to Maintain Economic Circular Flows of Thailand

Author

Listed:
  • Chanamart Intapan

    (Faculty of Agriculture, Chiang Mai University, Chiang Mai 50200, Thailand
    Modern Quantitative Economic Research Centre (MQERC), Chiang Mai University, Chiang Mai 50200, Thailand
    MICE Excellence Centre, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Chukiat Chaiboonsri

    (Modern Quantitative Economic Research Centre (MQERC), Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Pairach Piboonrungroj

    (MICE Excellence Centre, Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

We evaluated the movement in the daily number of COVID-19 cases in response to the real GDP during the COVID-19 pandemic in Thailand from Q1 2020 to Q1 2021. The aim of the study was to find the number of COVID-19 cases that could maintain circulation of the country’s economy. This is the question that most of the world’s economies have been facing and trying to figure out. Our theoretical model introduced dynamic stochastic general equilibrium (DSGE) models with a special emphasis on Bayesian inference. From the results of the study, it was found that the most reasonable number of COVID-19 cases that still maintains circulation of the country’s economy is about 3000 per month or about 9000 per quarter. This demonstrates that the daily number of COVID-19 cases significantly affects the growth of Thailand’s real GDP. Economists and policymakers can use the results of empirical studies to come up with guidelines or policies that can be implemented to reduce the number of infections to satisfactory levels in order to avoid Thailand lockdown. Although the COVID-19 outbreak can be suppressed through lockdown, the country cannot be locked down all the time.

Suggested Citation

  • Chanamart Intapan & Chukiat Chaiboonsri & Pairach Piboonrungroj, 2021. "Forecasting for the Optimal Numbers of COVID-19 Infection to Maintain Economic Circular Flows of Thailand," Economies, MDPI, vol. 9(4), pages 1-22, October.
    • Handle: RePEc:gam:jecomi:v:9:y:2021:i:4:p:151-:d:654226
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    References listed on IDEAS

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    1. Can, Ufuk & Can, Zeynep Gizem & Bocuoglu, Mehmet Emin & Dogru, Muhammed Erkam, 2021. "The effectiveness of the post-Covid-19 recovery policies: Evidence from a simulated DSGE model for Turkey," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 694-708.
    2. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
    3. Ng, Wung Lik, 2020. "To lockdown? When to peak? Will there be an end? A macroeconomic analysis on COVID-19 epidemic in the United States," Journal of Macroeconomics, Elsevier, vol. 65(C).
    4. Fabio Canova, 2007. "DSGE Models, Solutions, and Approximations, from Methods for Applied Macroeconomic Research," Introductory Chapters, in: Methods for Applied Macroeconomic Research, Princeton University Press.
    5. Amiri, Hossein & Sayadi, Mohammad & Mamipour, Siab, 2021. "Oil Price Shocks and Macroeconomic Outcomes; Fresh Evidences from a scenario-based NK-DSGE analysis for oil-exporting countries," Resources Policy, Elsevier, vol. 74(C).
    6. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    7. Nakhli, Seyyed Reza & Rafat, Monireh & Dastjerdi, Rasul Bakhshi & Rafei, Meysam, 2021. "Oil sanctions and their transmission channels in the Iranian economy: A DSGE model," Resources Policy, Elsevier, vol. 70(C).
    8. Sunghae Jun, 2019. "Bayesian Structural Time Series and Regression Modeling for Sustainable Technology Management," Sustainability, MDPI, vol. 11(18), pages 1-12, September.
    9. J.E. Boscá & R. Doménech & J. Ferri & J.R. García & C. Ulloa, 2021. "The stabilizing effects of economic policies in Spain in times of COVID-19," Applied Economic Analysis, Emerald Group Publishing Limited, vol. 29(85), pages 4-20, January.
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